{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "CoronaForecast.ipynb",
"provenance": [],
"collapsed_sections": []
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
}
},
"cells": [
{
"cell_type": "code",
"metadata": {
"id": "DUPB4tucl_pb",
"colab_type": "code",
"outputId": "a533cc80-69ea-4cfa-f924-d2085136b97b",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
}
},
"source": [
"import os\n",
"import pandas as pd\n",
"from google.colab import auth\n",
"from datetime import datetime\n",
"auth.authenticate_user()\n",
"!gcloud source repos clone github_aistream-peelout_flow-forecast --project=gmap-997\n",
"os.chdir('/content/github_aistream-peelout_flow-forecast')\n",
"!git checkout -t origin/covid_fixes\n",
"!python setup.py develop\n",
"!pip install -r requirements.txt\n",
"!mkdir data\n",
"from flood_forecast.trainer import train_function\n",
"!pip install git+https://github.com/CoronaWhy/task-geo.git\n",
"!wandb login"
],
"execution_count": 0,
"outputs": [
{
"output_type": "stream",
"text": [
"\u001b[1;33mWARNING:\u001b[0m Repository \"github_aistream-peelout_flow-forecast\" in project \"gmap-997\" is a mirror. Pushing to this clone will have no effect. Instead, clone the mirrored repository directly with \n",
"$ git clone https://github.com/AIStream-Peelout/flow-forecast\n",
"Cloning into '/content/github_aistream-peelout_flow-forecast'...\n",
"remote: Total 3703 (delta 2463), reused 3703 (delta 2463)\u001b[K\n",
"Receiving objects: 100% (3703/3703), 2.63 MiB | 13.23 MiB/s, done.\n",
"Resolving deltas: 100% (2463/2463), done.\n",
"Project [gmap-997] repository [github_aistream-peelout_flow-forecast] was cloned to [/content/github_aistream-peelout_flow-forecast].\n",
"Branch 'covid_fixes' set up to track remote branch 'covid_fixes' from 'origin'.\n",
"Switched to a new branch 'covid_fixes'\n",
"/usr/local/lib/python3.6/dist-packages/setuptools/dist.py:454: UserWarning: Normalizing '0.01dev' to '0.1.dev0'\n",
" warnings.warn(tmpl.format(**locals()))\n",
"running develop\n",
"running egg_info\n",
"creating flood_forecast.egg-info\n",
"writing flood_forecast.egg-info/PKG-INFO\n",
"writing dependency_links to flood_forecast.egg-info/dependency_links.txt\n",
"writing requirements to flood_forecast.egg-info/requires.txt\n",
"writing top-level names to flood_forecast.egg-info/top_level.txt\n",
"writing manifest file 'flood_forecast.egg-info/SOURCES.txt'\n",
"package init file 'flood_forecast/__init__.py' not found (or not a regular file)\n",
"package init file 'flood_forecast/transformer_xl/__init__.py' not found (or not a regular file)\n",
"package init file 'flood_forecast/preprocessing/__init__.py' not found (or not a regular file)\n",
"package init file 'flood_forecast/da_rnn/__init__.py' not found (or not a regular file)\n",
"package init file 'flood_forecast/basic/__init__.py' not found (or not a regular file)\n",
"package init file 'flood_forecast/custom/__init__.py' not found (or not a regular file)\n",
"writing manifest file 'flood_forecast.egg-info/SOURCES.txt'\n",
"running build_ext\n",
"Creating /usr/local/lib/python3.6/dist-packages/flood-forecast.egg-link (link to .)\n",
"Adding flood-forecast 0.1.dev0 to easy-install.pth file\n",
"\n",
"Installed /content/github_aistream-peelout_flow-forecast\n",
"Processing dependencies for flood-forecast==0.1.dev0\n",
"Searching for google-cloud\n",
"Reading https://pypi.org/simple/google-cloud/\n",
"Downloading https://files.pythonhosted.org/packages/ba/b1/7c54d1950e7808df06642274e677dbcedba57f75307adf2e5ad8d39e5e0e/google_cloud-0.34.0-py2.py3-none-any.whl#sha256=fb1ab7b0548fe44b3d538041f0a374505b7f990d448a935ea36649c5ccab5acf\n",
"Best match: google-cloud 0.34.0\n",
"Processing google_cloud-0.34.0-py2.py3-none-any.whl\n",
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"Adding google-cloud 0.34.0 to easy-install.pth file\n",
"\n",
"Installed /usr/local/lib/python3.6/dist-packages/google_cloud-0.34.0-py3.6.egg\n",
"Searching for pandas==1.0.3\n",
"Best match: pandas 1.0.3\n",
"Adding pandas 1.0.3 to easy-install.pth file\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for tensorflow==2.2.0rc4\n",
"Best match: tensorflow 2.2.0rc4\n",
"Adding tensorflow 2.2.0rc4 to easy-install.pth file\n",
"Installing estimator_ckpt_converter script to /usr/local/bin\n",
"Installing saved_model_cli script to /usr/local/bin\n",
"Installing tensorboard script to /usr/local/bin\n",
"Installing tf_upgrade_v2 script to /usr/local/bin\n",
"Installing tflite_convert script to /usr/local/bin\n",
"Installing toco script to /usr/local/bin\n",
"Installing toco_from_protos script to /usr/local/bin\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for torch==1.5.0+cu101\n",
"Best match: torch 1.5.0+cu101\n",
"Adding torch 1.5.0+cu101 to easy-install.pth file\n",
"Installing convert-caffe2-to-onnx script to /usr/local/bin\n",
"Installing convert-onnx-to-caffe2 script to /usr/local/bin\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for scikit-learn==0.22.2.post1\n",
"Best match: scikit-learn 0.22.2.post1\n",
"Adding scikit-learn 0.22.2.post1 to easy-install.pth file\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for python-dateutil==2.8.1\n",
"Best match: python-dateutil 2.8.1\n",
"Adding python-dateutil 2.8.1 to easy-install.pth file\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for numpy==1.18.4\n",
"Best match: numpy 1.18.4\n",
"Adding numpy 1.18.4 to easy-install.pth file\n",
"Installing f2py script to /usr/local/bin\n",
"Installing f2py3 script to /usr/local/bin\n",
"Installing f2py3.6 script to /usr/local/bin\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for pytz==2018.9\n",
"Best match: pytz 2018.9\n",
"Adding pytz 2018.9 to easy-install.pth file\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for wrapt==1.12.1\n",
"Best match: wrapt 1.12.1\n",
"Adding wrapt 1.12.1 to easy-install.pth file\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for wheel==0.34.2\n",
"Best match: wheel 0.34.2\n",
"Adding wheel 0.34.2 to easy-install.pth file\n",
"Installing wheel script to /usr/local/bin\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for h5py==2.10.0\n",
"Best match: h5py 2.10.0\n",
"Adding h5py 2.10.0 to easy-install.pth file\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for six==1.12.0\n",
"Best match: six 1.12.0\n",
"Adding six 1.12.0 to easy-install.pth file\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for absl-py==0.9.0\n",
"Best match: absl-py 0.9.0\n",
"Adding absl-py 0.9.0 to easy-install.pth file\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for Keras-Preprocessing==1.1.0\n",
"Best match: Keras-Preprocessing 1.1.0\n",
"Adding Keras-Preprocessing 1.1.0 to easy-install.pth file\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for google-pasta==0.2.0\n",
"Best match: google-pasta 0.2.0\n",
"Adding google-pasta 0.2.0 to easy-install.pth file\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for scipy==1.4.1\n",
"Best match: scipy 1.4.1\n",
"Adding scipy 1.4.1 to easy-install.pth file\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for gast==0.3.3\n",
"Best match: gast 0.3.3\n",
"Adding gast 0.3.3 to easy-install.pth file\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for opt-einsum==3.2.1\n",
"Best match: opt-einsum 3.2.1\n",
"Adding opt-einsum 3.2.1 to easy-install.pth file\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for protobuf==3.10.0\n",
"Best match: protobuf 3.10.0\n",
"Adding protobuf 3.10.0 to easy-install.pth file\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for grpcio==1.28.1\n",
"Best match: grpcio 1.28.1\n",
"Adding grpcio 1.28.1 to easy-install.pth file\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for tensorflow-estimator==2.2.0\n",
"Best match: tensorflow-estimator 2.2.0\n",
"Adding tensorflow-estimator 2.2.0 to easy-install.pth file\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for tensorboard==2.2.1\n",
"Best match: tensorboard 2.2.1\n",
"Adding tensorboard 2.2.1 to easy-install.pth file\n",
"Installing tensorboard script to /usr/local/bin\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for astunparse==1.6.3\n",
"Best match: astunparse 1.6.3\n",
"Adding astunparse 1.6.3 to easy-install.pth file\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for termcolor==1.1.0\n",
"Best match: termcolor 1.1.0\n",
"Adding termcolor 1.1.0 to easy-install.pth file\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for future==0.16.0\n",
"Best match: future 0.16.0\n",
"Adding future 0.16.0 to easy-install.pth file\n",
"Installing futurize script to /usr/local/bin\n",
"Installing pasteurize script to /usr/local/bin\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for joblib==0.14.1\n",
"Best match: joblib 0.14.1\n",
"Adding joblib 0.14.1 to easy-install.pth file\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for setuptools==46.1.3\n",
"Best match: setuptools 46.1.3\n",
"Adding setuptools 46.1.3 to easy-install.pth file\n",
"Installing easy_install script to /usr/local/bin\n",
"Installing easy_install-3.8 script to /usr/local/bin\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for Werkzeug==1.0.1\n",
"Best match: Werkzeug 1.0.1\n",
"Adding Werkzeug 1.0.1 to easy-install.pth file\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for google-auth==1.7.2\n",
"Best match: google-auth 1.7.2\n",
"Adding google-auth 1.7.2 to easy-install.pth file\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for google-auth-oauthlib==0.4.1\n",
"Best match: google-auth-oauthlib 0.4.1\n",
"Adding google-auth-oauthlib 0.4.1 to easy-install.pth file\n",
"Installing google-oauthlib-tool script to /usr/local/bin\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for Markdown==3.2.1\n",
"Best match: Markdown 3.2.1\n",
"Adding Markdown 3.2.1 to easy-install.pth file\n",
"Installing markdown_py script to /usr/local/bin\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for tensorboard-plugin-wit==1.6.0.post3\n",
"Best match: tensorboard-plugin-wit 1.6.0.post3\n",
"Adding tensorboard-plugin-wit 1.6.0.post3 to easy-install.pth file\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for requests==2.23.0\n",
"Best match: requests 2.23.0\n",
"Adding requests 2.23.0 to easy-install.pth file\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for cachetools==3.1.1\n",
"Best match: cachetools 3.1.1\n",
"Adding cachetools 3.1.1 to easy-install.pth file\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for rsa==4.0\n",
"Best match: rsa 4.0\n",
"Adding rsa 4.0 to easy-install.pth file\n",
"Installing pyrsa-decrypt script to /usr/local/bin\n",
"Installing pyrsa-encrypt script to /usr/local/bin\n",
"Installing pyrsa-keygen script to /usr/local/bin\n",
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"Installing pyrsa-sign script to /usr/local/bin\n",
"Installing pyrsa-verify script to /usr/local/bin\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for pyasn1-modules==0.2.8\n",
"Best match: pyasn1-modules 0.2.8\n",
"Adding pyasn1-modules 0.2.8 to easy-install.pth file\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for requests-oauthlib==1.3.0\n",
"Best match: requests-oauthlib 1.3.0\n",
"Adding requests-oauthlib 1.3.0 to easy-install.pth file\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for chardet==3.0.4\n",
"Best match: chardet 3.0.4\n",
"Adding chardet 3.0.4 to easy-install.pth file\n",
"Installing chardetect script to /usr/local/bin\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for urllib3==1.24.3\n",
"Best match: urllib3 1.24.3\n",
"Adding urllib3 1.24.3 to easy-install.pth file\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for idna==2.9\n",
"Best match: idna 2.9\n",
"Adding idna 2.9 to easy-install.pth file\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for certifi==2020.4.5.1\n",
"Best match: certifi 2020.4.5.1\n",
"Adding certifi 2020.4.5.1 to easy-install.pth file\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for pyasn1==0.4.8\n",
"Best match: pyasn1 0.4.8\n",
"Adding pyasn1 0.4.8 to easy-install.pth file\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Searching for oauthlib==3.1.0\n",
"Best match: oauthlib 3.1.0\n",
"Adding oauthlib 3.1.0 to easy-install.pth file\n",
"\n",
"Using /usr/local/lib/python3.6/dist-packages\n",
"Finished processing dependencies for flood-forecast==0.1.dev0\n",
"Requirement already satisfied: scikit-learn in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 1)) (0.22.2.post1)\n",
"Requirement already satisfied: pandas in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 2)) (1.0.3)\n",
"Requirement already satisfied: torch in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 3)) (1.5.0+cu101)\n",
"Collecting tb-nightly\n",
"\u001b[?25l Downloading https://files.pythonhosted.org/packages/ba/68/c413fa084dfcb95cb1b3fe9ea9d9de072e6c4acac3c3763a0ce50e1d8daf/tb_nightly-2.3.0a20200509-py3-none-any.whl (2.9MB)\n",
"\u001b[K |████████████████████████████████| 3.0MB 3.5MB/s \n",
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"Collecting wandb\n",
"\u001b[?25l Downloading https://files.pythonhosted.org/packages/2d/c9/ebbcefa6ef2ba14a7c62a4ee4415a5fecef8fac5e4d1b4e22af26fd9fe22/wandb-0.8.35-py2.py3-none-any.whl (1.4MB)\n",
"\u001b[K |████████████████████████████████| 1.4MB 47.1MB/s \n",
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"Requirement already satisfied: six>=1.10.0 in /usr/local/lib/python3.6/dist-packages (from tb-nightly->-r requirements.txt (line 4)) (1.12.0)\n",
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"Requirement already satisfied: setuptools>=41.0.0 in /usr/local/lib/python3.6/dist-packages (from tb-nightly->-r requirements.txt (line 4)) (46.1.3)\n",
"Requirement already satisfied: google-auth<2,>=1.6.3 in /usr/local/lib/python3.6/dist-packages (from tb-nightly->-r requirements.txt (line 4)) (1.7.2)\n",
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"Requirement already satisfied: matplotlib>=2.1.2 in /usr/local/lib/python3.6/dist-packages (from seaborn->-r requirements.txt (line 5)) (3.2.1)\n",
"Collecting gql==0.2.0\n",
" Downloading https://files.pythonhosted.org/packages/c4/6f/cf9a3056045518f06184e804bae89390eb706168349daa9dff8ac609962a/gql-0.2.0.tar.gz\n",
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"\u001b[?25l Downloading https://files.pythonhosted.org/packages/20/7e/19545324e83db4522b885808cd913c3b93ecc0c88b03e037b78c6a417fa8/sentry_sdk-0.14.3-py2.py3-none-any.whl (103kB)\n",
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"Collecting shortuuid>=0.5.0\n",
" Downloading https://files.pythonhosted.org/packages/25/a6/2ecc1daa6a304e7f1b216f0896b26156b78e7c38e1211e9b798b4716c53d/shortuuid-1.0.1-py3-none-any.whl\n",
"Collecting configparser>=3.8.1\n",
" Downloading https://files.pythonhosted.org/packages/4b/6b/01baa293090240cf0562cc5eccb69c6f5006282127f2b846fad011305c79/configparser-5.0.0-py3-none-any.whl\n",
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"\u001b[?25l Downloading https://files.pythonhosted.org/packages/b0/89/00ad5e07524d8c523b14d70c685e0299a8b0de6d0727e368c41b89b7ed0b/graphql-core-1.1.tar.gz (70kB)\n",
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" Downloading https://files.pythonhosted.org/packages/e7/7f/470d6fcdf23f9f3518f6b0b76be9df16dcc8630ad409947f8be2eb0ed13a/pathtools-0.1.2.tar.gz\n",
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"\u001b[?25l Downloading https://files.pythonhosted.org/packages/48/11/d1800bca0a3bae820b84b7d813ad1eff15a48a64caea9c823fc8c1b119e8/gitdb-4.0.5-py3-none-any.whl (63kB)\n",
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"Collecting smmap<4,>=3.0.1\n",
" Downloading https://files.pythonhosted.org/packages/b0/9a/4d409a6234eb940e6a78dfdfc66156e7522262f5f2fecca07dc55915952d/smmap-3.0.4-py2.py3-none-any.whl\n",
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"Building wheels for collected packages: gql, subprocess32, watchdog, graphql-core, pathtools\n",
" Building wheel for gql (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
" Created wheel for gql: filename=gql-0.2.0-cp36-none-any.whl size=7630 sha256=efdb6942864b790a728bf5da03b8f5217618c33f4db086398a4e65c0702548c9\n",
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" Building wheel for subprocess32 (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
" Created wheel for subprocess32: filename=subprocess32-3.5.4-cp36-none-any.whl size=6489 sha256=5ad23f1ec1134b6b82eca206bdd195eeedf3fab18493700cff5834ff8ee37041\n",
" Stored in directory: /root/.cache/pip/wheels/68/39/1a/5e402bdfdf004af1786c8b853fd92f8c4a04f22aad179654d1\n",
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" Created wheel for watchdog: filename=watchdog-0.10.2-cp36-none-any.whl size=73605 sha256=4f13410c32204b416349c9f898ad95f5a3c89ff1b3e07d3724dfd9de0898886c\n",
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" Created wheel for graphql-core: filename=graphql_core-1.1-cp36-none-any.whl size=104650 sha256=990e5fb8fe2bece99f37b18a8bcc3ebe91f66b477f239cae3791e95b2058d7df\n",
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" Created wheel for pathtools: filename=pathtools-0.1.2-cp36-none-any.whl size=8784 sha256=1959d68adefe6f08809257d74c1bbe351986b205e7cc04b9ad84ad3e024d075b\n",
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"Installing collected packages: tb-nightly, graphql-core, gql, sentry-sdk, shortuuid, configparser, subprocess32, pathtools, watchdog, docker-pycreds, smmap, gitdb, GitPython, wandb\n",
"Successfully installed GitPython-3.1.2 configparser-5.0.0 docker-pycreds-0.4.0 gitdb-4.0.5 gql-0.2.0 graphql-core-1.1 pathtools-0.1.2 sentry-sdk-0.14.3 shortuuid-1.0.1 smmap-3.0.4 subprocess32-3.5.4 tb-nightly-2.3.0a20200509 wandb-0.8.35 watchdog-0.10.2\n",
"Collecting git+https://github.com/CoronaWhy/task-geo.git\n",
" Cloning https://github.com/CoronaWhy/task-geo.git to /tmp/pip-req-build-xptgbhwy\n",
" Running command git clone -q https://github.com/CoronaWhy/task-geo.git /tmp/pip-req-build-xptgbhwy\n",
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"\u001b[?25l Downloading https://files.pythonhosted.org/packages/79/32/7033d6d9ff01fd592ec649756f78460dc66640c1001f39c2d421037866f3/hdx_python_api-4.5.8-py2.py3-none-any.whl (67kB)\n",
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" Downloading https://files.pythonhosted.org/packages/07/c6/50449e18aaf1600dfda955805c58aa7462493511f3ebbb20d0a65874397c/ckanapi-4.3.tar.gz\n",
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"\u001b[?25l Downloading https://files.pythonhosted.org/packages/9e/de/f8342b68fa9e981d348039954657bdf681b2ab93de27443be51865ffa310/pyOpenSSL-19.1.0-py2.py3-none-any.whl (53kB)\n",
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"Collecting hdx-python-country>=2.5.6\n",
" Downloading https://files.pythonhosted.org/packages/24/45/684ec41e237b3e185c268b4ad4cd71581c3dfdb9c3e279d7777473edb8c2/hdx_python_country-2.5.6-py2.py3-none-any.whl\n",
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"Collecting cryptography>=2.8\n",
"\u001b[?25l Downloading https://files.pythonhosted.org/packages/3c/04/686efee2dcdd25aecf357992e7d9362f443eb182ecd623f882bc9f7a6bba/cryptography-2.9.2-cp35-abi3-manylinux2010_x86_64.whl (2.7MB)\n",
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"\u001b[?25l Downloading https://files.pythonhosted.org/packages/eb/a2/ea800689730732e27711c41beed4b2a129b34974435bdc450377ec407738/num2words-0.5.10-py3-none-any.whl (101kB)\n",
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"\u001b[?25l Downloading https://files.pythonhosted.org/packages/d1/bb/7713720c382aad5260694fd5875fe013ee7ccef771e41a3298f661c01c84/libhxl-4.19.tar.gz (77kB)\n",
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"\u001b[?25l Downloading https://files.pythonhosted.org/packages/13/0c/dd417c960de745a129d6c0cf63bb0215b179c29674e45ca041c75cf76baf/hdx_python_utilities-2.3.4-py2.py3-none-any.whl (46kB)\n",
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"\u001b[K |████████████████████████████████| 245kB 48.8MB/s \n",
"\u001b[?25hCollecting python-io-wrapper\n",
" Downloading https://files.pythonhosted.org/packages/76/81/88e02bc603e55883a087811a641fd3836749b7509365778fea29d74fd58c/python-io-wrapper-0.1.tar.gz\n",
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" Downloading https://files.pythonhosted.org/packages/71/7c/45001b1f19af8c4478489fbae4fc657b21c4c669d7a5a036a86882581d85/jsonpath-rw-1.4.0.tar.gz\n",
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"\u001b[?25l Downloading https://files.pythonhosted.org/packages/a3/58/35da89ee790598a0700ea49b2a66594140f44dec458c07e8e3d4979137fc/ply-3.11-py2.py3-none-any.whl (49kB)\n",
"\u001b[K |████████████████████████████████| 51kB 5.4MB/s \n",
"\u001b[?25hCollecting sshtunnel\n",
"\u001b[?25l Downloading https://files.pythonhosted.org/packages/c5/5c/4b320d7ec4b0d5d4d6df1fdf66a5799625b3623d0ce4efe81719c6f8dfb3/sshtunnel-0.1.5.tar.gz (49kB)\n",
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"Collecting ratelimit\n",
" Downloading https://files.pythonhosted.org/packages/ab/38/ff60c8fc9e002d50d48822cc5095deb8ebbc5f91a6b8fdd9731c87a147c9/ratelimit-2.2.1.tar.gz\n",
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"Collecting basicauth\n",
" Downloading https://files.pythonhosted.org/packages/76/47/08d21ffcc837bebf3306b8295f5d179f9bc498f6235ebf4a4e38be57839c/basicauth-0.4.1-py2.py3-none-any.whl\n",
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"\u001b[?25l Downloading https://files.pythonhosted.org/packages/d3/8a/a7ed55c2c55bd4f5844d72734fedc0cef8a74518a0a19105a21c15628f1e/psycopg2_binary-2.8.5-cp36-cp36m-manylinux1_x86_64.whl (2.9MB)\n",
"\u001b[K |████████████████████████████████| 2.9MB 35.6MB/s \n",
"\u001b[?25hCollecting yamlloader\n",
" Downloading https://files.pythonhosted.org/packages/93/a2/2f0c2394af1559021703c8cbb1bc7419bb5a94ea6bde0ab8cd1e973bb605/yamlloader-0.5.5-py3-none-any.whl\n",
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"\u001b[?25l Downloading https://files.pythonhosted.org/packages/57/82/517ec480d4cfadb0e6d6d441e11a349d7d607f929f2f34f7777d65b1e421/tabulator-1.44.0-py2.py3-none-any.whl (69kB)\n",
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" Downloading https://files.pythonhosted.org/packages/00/0d/22c73c2eccb21dd3498df7d22c0b1d4a30f5a5fb3feb64e1ce06bc247747/colorlog-4.1.0-py2.py3-none-any.whl\n",
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" Downloading https://files.pythonhosted.org/packages/15/c4/1310a054d33abc318426a956e7d6df0df76a6ddfa9c66f6310274fb75d42/pyaml-20.4.0-py2.py3-none-any.whl\n",
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"Collecting paramiko>=1.15.2\n",
"\u001b[?25l Downloading https://files.pythonhosted.org/packages/06/1e/1e08baaaf6c3d3df1459fd85f0e7d2d6aa916f33958f151ee1ecc9800971/paramiko-2.7.1-py2.py3-none-any.whl (206kB)\n",
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"\u001b[?25hCollecting dnspython>=1.15.0\n",
"\u001b[?25l Downloading https://files.pythonhosted.org/packages/ec/d3/3aa0e7213ef72b8585747aa0e271a9523e713813b9a20177ebe1e939deb0/dnspython-1.16.0-py2.py3-none-any.whl (188kB)\n",
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"Collecting openpyxl>=2.6\n",
"\u001b[?25l Downloading https://files.pythonhosted.org/packages/95/8c/83563c60489954e5b80f9e2596b93a68e1ac4e4a730deb1aae632066d704/openpyxl-3.0.3.tar.gz (172kB)\n",
"\u001b[K |████████████████████████████████| 174kB 46.9MB/s \n",
"\u001b[?25hCollecting linear-tsv>=1.0\n",
" Downloading https://files.pythonhosted.org/packages/82/e5/03207a0f11e1d60df85b97b61704ed701b725a7c2feaf83f7bfbd0c2d83e/linear-tsv-1.1.0.tar.gz\n",
"Collecting jsonlines>=1.1\n",
" Downloading https://files.pythonhosted.org/packages/4f/9a/ab96291470e305504aa4b7a2e0ec132e930da89eb3ca7a82fbe03167c131/jsonlines-1.2.0-py2.py3-none-any.whl\n",
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"\u001b[?25l Downloading https://files.pythonhosted.org/packages/75/38/e2d650844fd69ced9fb8d2804ffd3cd76d43bcc1950c266367aaf9a456f6/ijson-3.0.3-cp36-cp36m-manylinux1_x86_64.whl (96kB)\n",
"\u001b[K |████████████████████████████████| 102kB 8.2MB/s \n",
"\u001b[?25hCollecting unicodecsv>=0.14\n",
" Downloading https://files.pythonhosted.org/packages/6f/a4/691ab63b17505a26096608cc309960b5a6bdf39e4ba1a793d5f9b1a53270/unicodecsv-0.14.1.tar.gz\n",
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"Collecting cchardet>=2.0; extra == \"cchardet\"\n",
"\u001b[?25l Downloading https://files.pythonhosted.org/packages/1e/c5/7e1a0d7b4afd83d6f8de794fce82820ec4c5136c6d52e14000822681a842/cchardet-2.1.6-cp36-cp36m-manylinux2010_x86_64.whl (241kB)\n",
"\u001b[K |████████████████████████████████| 245kB 35.6MB/s \n",
"\u001b[?25hCollecting pynacl>=1.0.1\n",
"\u001b[?25l Downloading https://files.pythonhosted.org/packages/27/15/2cd0a203f318c2240b42cd9dd13c931ddd61067809fee3479f44f086103e/PyNaCl-1.3.0-cp34-abi3-manylinux1_x86_64.whl (759kB)\n",
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"\u001b[?25hCollecting bcrypt>=3.1.3\n",
"\u001b[?25l Downloading https://files.pythonhosted.org/packages/8b/1d/82826443777dd4a624e38a08957b975e75df859b381ae302cfd7a30783ed/bcrypt-3.1.7-cp34-abi3-manylinux1_x86_64.whl (56kB)\n",
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"Requirement already satisfied: et_xmlfile in /usr/local/lib/python3.6/dist-packages (from openpyxl>=2.6->tabulator[cchardet]>=1.42.0->hdx-python-utilities>=2.3.4->hdx-python-country>=2.5.6->hdx-python-api->task-geo==0.1.0.dev0) (1.0.1)\n",
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"Requirement already satisfied: docutils<0.16,>=0.10 in /usr/local/lib/python3.6/dist-packages (from botocore<1.17.0,>=1.16.3->boto3>=1.9->tabulator[cchardet]>=1.42.0->hdx-python-utilities>=2.3.4->hdx-python-country>=2.5.6->hdx-python-api->task-geo==0.1.0.dev0) (0.15.2)\n",
"Building wheels for collected packages: task-geo, ckanapi, libhxl, python-io-wrapper, jsonpath-rw, sshtunnel, ratelimit, openpyxl, linear-tsv, unicodecsv\n",
" Building wheel for task-geo (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
" Created wheel for task-geo: filename=task_geo-0.1.0.dev0-py2.py3-none-any.whl size=177461 sha256=0715f4a9dc29541d20496dcf78309daca37dcecc0766292fd97b6013d48fc64e\n",
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" Created wheel for ckanapi: filename=ckanapi-4.3-cp36-none-any.whl size=38647 sha256=166b963560cbf1edd246d53404ba0507436fb0958384d80cce630caaf3520117\n",
" Stored in directory: /root/.cache/pip/wheels/41/f2/fb/c8ce857007de64cc6b36b8f1048272396bc0817c35ee3a3e73\n",
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" Stored in directory: /root/.cache/pip/wheels/99/4e/75/2c1d5d8cd3c34a42dcd9a388562d3dd3fb2197adbb47e20503\n",
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" Stored in directory: /root/.cache/pip/wheels/6b/26/be/da3c0a774901c557a0bee985e7aade5b9db75fe4dc8ef99ced\n",
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" Created wheel for jsonpath-rw: filename=jsonpath_rw-1.4.0-cp36-none-any.whl size=15146 sha256=d5daeb5cf825d4b7f450ca43c889d1d2ae8c9767d9c5bf70cbe25e44c872a0c9\n",
" Stored in directory: /root/.cache/pip/wheels/5c/00/9a/82822db383c2d96dcebf839786665a185f92d37e5026f9806f\n",
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" Created wheel for sshtunnel: filename=sshtunnel-0.1.5-py2.py3-none-any.whl size=23243 sha256=fd7eb4dd7d7fe19108857f707f017972fcbea90a053e1856c4431746003fc41a\n",
" Stored in directory: /root/.cache/pip/wheels/e8/d2/38/b9791b7391f634099194ec6697fa671194f3353906d94c8f92\n",
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" Created wheel for ratelimit: filename=ratelimit-2.2.1-cp36-none-any.whl size=5893 sha256=89b5a5ec5d39b5432f0338b114fce29ea2e1fb09d7dee74c0547102660f13e89\n",
" Stored in directory: /root/.cache/pip/wheels/05/d9/82/3c6044cf1a54aab9151612458446d9b17a38416869e1b1d9b8\n",
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" Created wheel for openpyxl: filename=openpyxl-3.0.3-py2.py3-none-any.whl size=241262 sha256=e8124e8bea3e1eea2ed30c228a40eabb8003d9803813984a602fbde0b46c136f\n",
" Stored in directory: /root/.cache/pip/wheels/b5/85/ca/e768ac132e57e75e645a151f8badac71cc0089e7225dddf76b\n",
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" Created wheel for linear-tsv: filename=linear_tsv-1.1.0-cp36-none-any.whl size=7383 sha256=8b473779da3f1baccf57e16557a6ca83195947f8f2d7d03b26a3ccd7b7b620f8\n",
" Stored in directory: /root/.cache/pip/wheels/3f/8a/cb/38917fd1ef4356b9870ace7331b83417dc594bf2c029bd991f\n",
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" Created wheel for unicodecsv: filename=unicodecsv-0.14.1-cp36-none-any.whl size=10768 sha256=52517a383a97e3efcdf4a77de6f33a714ce97cc4565733dd3d95f67cbb8caa52\n",
" Stored in directory: /root/.cache/pip/wheels/a6/09/e9/e800279c98a0a8c94543f3de6c8a562f60e51363ed26e71283\n",
"Successfully built task-geo ckanapi libhxl python-io-wrapper jsonpath-rw sshtunnel ratelimit openpyxl linear-tsv unicodecsv\n",
"\u001b[31mERROR: hdx-python-utilities 2.3.4 has requirement six>=1.14.0, but you'll have six 1.12.0 which is incompatible.\u001b[0m\n",
"Installing collected packages: ckanapi, cryptography, pyOpenSSL, num2words, quantulum3, ndg-httpsclient, unidecode, python-io-wrapper, ply, jsonpath-rw, libhxl, pynacl, bcrypt, paramiko, sshtunnel, ratelimit, basicauth, dnspython, email-validator, psycopg2-binary, yamlloader, openpyxl, linear-tsv, jsonlines, ijson, unicodecsv, cchardet, tabulator, colorlog, pyaml, hdx-python-utilities, hdx-python-country, hdx-python-api, task-geo\n",
" Found existing installation: openpyxl 2.5.9\n",
" Uninstalling openpyxl-2.5.9:\n",
" Successfully uninstalled openpyxl-2.5.9\n",
"Successfully installed basicauth-0.4.1 bcrypt-3.1.7 cchardet-2.1.6 ckanapi-4.3 colorlog-4.1.0 cryptography-2.9.2 dnspython-1.16.0 email-validator-1.1.0 hdx-python-api-4.5.8 hdx-python-country-2.5.6 hdx-python-utilities-2.3.4 ijson-3.0.3 jsonlines-1.2.0 jsonpath-rw-1.4.0 libhxl-4.19 linear-tsv-1.1.0 ndg-httpsclient-0.5.1 num2words-0.5.10 openpyxl-3.0.3 paramiko-2.7.1 ply-3.11 psycopg2-binary-2.8.5 pyOpenSSL-19.1.0 pyaml-20.4.0 pynacl-1.3.0 python-io-wrapper-0.1 quantulum3-0.7.3 ratelimit-2.2.1 sshtunnel-0.1.5 tabulator-1.44.0 task-geo-0.1.0.dev0 unicodecsv-0.14.1 unidecode-1.1.1 yamlloader-0.5.5\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: You can find your API key in your browser here: https://app.wandb.ai/authorize\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: Paste an API key from your profile and hit enter: 936f243deff8f026e476a495792f87a7942c65bf\n",
"\u001b[34m\u001b[1mwandb\u001b[0m: Appending key for api.wandb.ai to your netrc file: /root/.netrc\n",
"\u001b[32mSuccessfully logged in to Weights & Biases!\u001b[0m\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "jIvlu81jmNTm",
"colab_type": "code",
"colab": {}
},
"source": [
"def make_config_file(file_path, df_len, weight_path=None):\n",
" run = wandb.init(project=\"covid-forecast\")\n",
" wandb_config = wandb.config\n",
" train_number = df_len * .7\n",
" validation_number = df_len *.9\n",
" config_default={ \n",
" \"model_name\": \"MultiAttnHeadSimple\",\n",
" \"model_type\": \"PyTorch\",\n",
" \"model_params\": {\n",
" \"number_time_series\":3,\n",
" \"seq_len\":wandb_config[\"forecast_history\"], \n",
" \"output_seq_len\":wandb_config[\"out_seq_length\"],\n",
" \"forecast_length\":wandb_config[\"out_seq_length\"]\n",
" },\n",
" \"dataset_params\":\n",
" { \"class\": \"default\",\n",
" \"training_path\": file_path,\n",
" \"validation_path\": file_path,\n",
" \"test_path\": file_path,\n",
" \"batch_size\":wandb_config[\"batch_size\"],\n",
" \"forecast_history\":wandb_config[\"forecast_history\"],\n",
" \"forecast_length\":wandb_config[\"out_seq_length\"],\n",
" \"train_end\": int(train_number),\n",
" \"valid_start\":int(train_number+1),\n",
" \"valid_end\": int(validation_number),\n",
" \"target_col\": [\"new_cases\"],\n",
" \"relevant_cols\": [\"new_cases\", \"month\", \"weekday\"],\n",
" \"scaler\": \"StandardScaler\", \n",
" \"interpolate\": False\n",
" },\n",
" \"training_params\":\n",
" {\n",
" \"criterion\":\"MSE\",\n",
" \"optimizer\": wandb_config[\"optimizer\"],\n",
" \"optim_params\":\n",
" {\n",
" \"lr\": wandb_config[\"lr\"]\n",
" },\n",
" \n",
" \"epochs\": 10,\n",
" \"batch_size\":wandb_config[\"batch_size\"]\n",
" \n",
" },\n",
" \"GCS\": False,\n",
" \n",
" \"sweep\":True,\n",
" \"wandb\":False,\n",
" \"forward_params\":{},\n",
" \"metrics\":[\"MSE\"],\n",
" \"inference_params\":\n",
" { \n",
" \"datetime_start\":\"2020-04-21\",\n",
" \"hours_to_forecast\":10, \n",
" \"test_csv_path\":file_path,\n",
" \"decoder_params\":{\n",
" \"decoder_function\": \"simple_decode\", \n",
" \"unsqueeze_dim\": 1\n",
" },\n",
" \"dataset_params\":{\n",
" \"file_path\": file_path,\n",
" \"forecast_history\":wandb_config[\"forecast_history\"],\n",
" \"forecast_length\":wandb_config[\"out_seq_length\"],\n",
" \"relevant_cols\": [\"new_cases\", \"month\", \"weekday\"],\n",
" \"target_col\": [\"new_cases\"],\n",
" \"scaling\": \"StandardScaler\",\n",
" \"interpolate_param\": False\n",
" }\n",
" }\n",
" }\n",
" if weight_path: \n",
" config_default[\"weight_path\"] = weight_path\n",
" wandb.config.update(config_default)\n",
" return config_default\n",
"\n",
"sweep_config = {\n",
" \"name\": \"Default sweep\",\n",
" \"method\": \"grid\",\n",
" \"parameters\": {\n",
" \"batch_size\": {\n",
" \"values\": [2, 3, 4, 5]\n",
" },\n",
" \"lr\":{\n",
" \"values\":[0.001, 0.002, 0.004, 0.01]\n",
" },\n",
" \"optimizer\":{\n",
" \"values\":[\"Adam\"]\n",
" },\n",
" \"forecast_history\":{\n",
" \"values\":[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]\n",
" },\n",
" \n",
" \"out_seq_length\":{\n",
" \"values\":[1, 2, 3]\n",
" }\n",
" \n",
" }\n",
"}"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "6BHGcmwcn82q",
"colab_type": "code",
"colab": {}
},
"source": [
"def format_corona_data(region_df:pd.DataFrame, region_name:str):\n",
" \"\"\"\n",
" Format data for a specific region into \n",
" a format that can be used with flow forecast. \n",
" \"\"\"\n",
" if region_name == 'county':\n",
" region_name = region_df['full_county'].iloc[0]\n",
" else:\n",
" region_name = region_df['state'].iloc[0]\n",
" #else:\n",
" #region_name = region_df['country'].iloc[0]\n",
" print(region_name)\n",
" region_df['datetime'] = region_df['date']\n",
" region_df['precip'] = 0\n",
" region_df['temp'] = 0\n",
" region_df = region_df.fillna(0)\n",
" region_df['new_cases'] = region_df['cases'].diff()\n",
" region_df.iloc[0]['new_cases'] = 0\n",
" region_df= region_df.fillna(0)\n",
" region_df.to_csv(region_name+\".csv\")\n",
" return region_df, len(region_df), region_name+\".csv\"\n",
"\n",
"def loop_through_geo_codes(df, column='full_county'):\n",
" df_county_list = []\n",
" df['full_county'] = df['state'] + \"_\" + df['county'] \n",
" for code in df['full_county'].unique():\n",
" mask = df['full_county'] == code\n",
" df_code = df[mask]\n",
" ts_count = len(df_code)\n",
" if ts_count > 60:\n",
" df_county_list.append(df_code)\n",
" return df_county_list \n",
"\n",
"def fetch_time_series() -> pd.DataFrame:\n",
" \"\"\"Fetch raw time series data from coronadatascraper.com\n",
" Returns:\n",
" pd.DataFrame: raw timeseries data at county/sub-region level\n",
" \"\"\"\n",
" if 1==1:\n",
" url = \"https://coronadatascraper.com/timeseries.csv\"\n",
" urllib.request.urlretrieve(url, \"timeseries.csv\")\n",
"\n",
" time_series_df = pd.read_csv(\"timeseries.csv\")\n",
" return time_series_df"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "fcUXAwnypgC_",
"colab_type": "code",
"outputId": "723888eb-2772-4194-947f-1e1f92b8ff25",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 71
}
},
"source": [
"import urllib\n",
"df = fetch_time_series()\n",
"df['month'] = pd.to_datetime(df['date']).map(lambda x: x.month)\n",
"df['weekday'] = pd.to_datetime(df['date']).map(lambda x: x.weekday())\n",
"df_list = loop_through_geo_codes(df)"
],
"execution_count": 0,
"outputs": [
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py:2822: DtypeWarning: Columns (2) have mixed types.Specify dtype option on import or set low_memory=False.\n",
" if self.run_code(code, result):\n"
],
"name": "stderr"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "jlGrTTFm2GwI",
"colab_type": "text"
},
"source": [
"Run sweep"
]
},
{
"cell_type": "code",
"metadata": {
"id": "OqpXvjXKqtcl",
"colab_type": "code",
"outputId": "72a4b222-93cb-4918-c275-1225a6d90593",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
}
},
"source": [
"import wandb\n",
"def sweep_all_geo(df_list, region_level, start_index=0, end_index=38):\n",
" for array_index in range(start_index, end_index):\n",
" region_df, full_len, file_path = format_corona_data(df_list[array_index], region_level)\n",
" sweep_id = wandb.sweep(sweep_config, project=\"covid-forecast\")\n",
" wandb.agent(sweep_id, lambda:train_function(\"PyTorch\", make_config_file(file_path, full_len)))\n",
"print(len(df_list))\n",
"sweep_all_geo(df_list, 'county', 40, len(df_list))"
],
"execution_count": 0,
"outputs": [
{
"output_type": "stream",
"text": [
"173\n",
"Colorado_Douglas County\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:13: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" del sys.path[0]\n",
"/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:14: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" \n",
"/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:15: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" from ipykernel import kernelapp as app\n",
"/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:18: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Create sweep with ID: dmjolbmp\n",
"Sweep URL: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp\n",
"wandb: Agent Starting Run: ikjglsrm with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 1\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: ikjglsrm\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/ikjglsrm
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 1\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 1\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 1\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 1\n",
" number_time_series: 3\n",
" output_seq_len: 1\n",
" seq_len: 1\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 1\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"22.209745293483138\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 0\n",
"1.0576069187372923\n",
"The running loss is:\n",
"25.875566819682717\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 1\n",
"1.23216984855632\n",
"The running loss is:\n",
"16.456275817006826\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 2\n",
"0.7836321817622298\n",
"The running loss is:\n",
"16.631219685077667\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 3\n",
"0.7919628421465555\n",
"The running loss is:\n",
"15.837834678590298\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 4\n",
"0.7541826037423951\n",
"The running loss is:\n",
"14.741810627281666\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 5\n",
"0.7019909822515079\n",
"The running loss is:\n",
"15.050849847495556\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 6\n",
"0.7167071355950265\n",
"The running loss is:\n",
"15.953906068578362\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 7\n",
"0.7597098127894458\n",
"The running loss is:\n",
"16.0874502658844\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 8\n",
"0.7660690602802095\n",
"The running loss is:\n",
"15.227701779454947\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 9\n",
"0.7251286561645213\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 11.894448\n",
"48 30755 ... 11.626228\n",
"49 30756 ... 11.733383\n",
"50 30757 ... 12.008819\n",
"51 30758 ... 12.359694\n",
"52 30759 ... 12.744390\n",
"53 30760 ... 13.144247\n",
"54 30761 ... 11.959114\n",
"55 30762 ... 11.655218\n",
"56 30763 ... 11.746380\n",
"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: ikjglsrm \n",
"\n",
"wandb: Agent Starting Run: sccle7in with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 1\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: sccle7in\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/sccle7in
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
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" scaler: StandardScaler\n",
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" test_path: Colorado_Douglas County.csv\n",
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" training_path: Colorado_Douglas County.csv\n",
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" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 1\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
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" desc: null\n",
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" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"32.99953880906105\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 0\n",
"1.5714066099552881\n",
"The running loss is:\n",
"34.578114688396454\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 1\n",
"1.6465768899236406\n",
"The running loss is:\n",
"25.18665075302124\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 2\n",
"1.19936432157244\n",
"The running loss is:\n",
"24.97196725010872\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 3\n",
"1.1891412976242246\n",
"The running loss is:\n",
"24.43036612868309\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 4\n",
"1.1633507680325281\n",
"The running loss is:\n",
"24.190653383731842\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 5\n",
"1.151935875415802\n",
"The running loss is:\n",
"23.219544798135757\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 6\n",
"1.1056926094350361\n",
"The running loss is:\n",
"22.971314638853073\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 7\n",
"1.0938721256596702\n",
"The running loss is:\n",
"21.56657423079014\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 8\n",
"1.026979725275721\n",
"The running loss is:\n",
"22.224213495850563\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 9\n",
"1.0582958807547886\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 15.966778\n",
"48 30755 ... 17.588491\n",
"49 30756 ... 18.489956\n",
"50 30757 ... 19.005741\n",
"51 30758 ... 19.315006\n",
"52 30759 ... 19.513683\n",
"53 30760 ... 19.653145\n",
"54 30761 ... 19.529381\n",
"55 30762 ... 19.496183\n",
"56 30763 ... 19.511480\n",
"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: sccle7in \n",
"\n",
"wandb: Agent Starting Run: 1kbxwatt with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 1\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
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],
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{
"output_type": "display_data",
"data": {
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"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/1kbxwatt
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 1\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
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"forward_params:\n",
" desc: null\n",
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"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 1\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
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"\n",
"Torch is using cpu\n",
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"The number of items in train is: \n",
"20\n",
"The loss for epoch 0\n",
"1.3737239494919777\n",
"The running loss is:\n",
"35.779832273721695\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 1\n",
"1.7889916136860848\n",
"The running loss is:\n",
"23.186582028865814\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 2\n",
"1.1593291014432907\n",
"The running loss is:\n",
"22.105967074632645\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 3\n",
"1.1052983537316323\n",
"The running loss is:\n",
"21.186039209365845\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 4\n",
"1.0593019604682923\n",
"The running loss is:\n",
"21.136306032538414\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 5\n",
"1.0568153016269206\n",
"The running loss is:\n",
"20.87136097252369\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 6\n",
"1.0435680486261845\n",
"The running loss is:\n",
"20.777209982275963\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 7\n",
"1.0388604991137982\n",
"The running loss is:\n",
"20.66132915019989\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 8\n",
"1.0330664575099946\n",
"The running loss is:\n",
"20.37255945801735\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 9\n",
"1.0186279729008674\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 6.496966\n",
"48 30755 ... 3.573092\n",
"49 30756 ... 2.030942\n",
"50 30757 ... 1.022203\n",
"51 30758 ... 0.219382\n",
"52 30759 ... -0.503940\n",
"53 30760 ... -1.196578\n",
"54 30761 ... 1.016424\n",
"55 30762 ... 1.457347\n",
"56 30763 ... 1.214166\n",
"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 1kbxwatt \n",
"\n",
"wandb: Agent Starting Run: yr7zkt33 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 1\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
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"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
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"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/yr7zkt33
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"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 1\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 1\n",
"forward_params:\n",
" desc: null\n",
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"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 1\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 1\n",
" number_time_series: 3\n",
" output_seq_len: 1\n",
" seq_len: 1\n",
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" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
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" desc: null\n",
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" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"17.944366239011288\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 0\n",
"0.854493630429109\n",
"The running loss is:\n",
"34.34139671176672\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 1\n",
"1.6353046053222247\n",
"The running loss is:\n",
"27.00930019468069\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 2\n",
"1.286157152127652\n",
"The running loss is:\n",
"17.550274595618248\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 3\n",
"0.8357273616961071\n",
"The running loss is:\n",
"15.303298708051443\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 4\n",
"0.7287285099072116\n",
"The running loss is:\n",
"16.061053287237883\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 5\n",
"0.764812061297042\n",
"The running loss is:\n",
"15.270921267569065\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 6\n",
"0.7271867270270983\n",
"The running loss is:\n",
"15.990724802017212\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 7\n",
"0.7614630858103434\n",
"The running loss is:\n",
"15.62948726862669\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 8\n",
"0.7442612985060328\n",
"The running loss is:\n",
"15.671696230769157\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 9\n",
"0.7462712490842456\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 11.829262\n",
"48 30755 ... 11.559772\n",
"49 30756 ... 11.661650\n",
"50 30757 ... 11.916553\n",
"51 30758 ... 12.234512\n",
"52 30759 ... 12.578454\n",
"53 30760 ... 12.933103\n",
"54 30761 ... 11.801696\n",
"55 30762 ... 11.548413\n",
"56 30763 ... 11.656969\n",
"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: yr7zkt33 \n",
"\n",
"wandb: Agent Starting Run: 64pwuc2m with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 1\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: 64pwuc2m\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/64pwuc2m
\n",
" "
],
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""
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},
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 1\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 1\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 1\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
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" seq_len: 1\n",
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" desc: null\n",
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" desc: null\n",
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"sweep:\n",
" desc: null\n",
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" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"27.359292954206467\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 0\n",
"1.3028234740098317\n",
"The running loss is:\n",
"43.42585930228233\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 1\n",
"2.0678980620134446\n",
"The running loss is:\n",
"33.279954731464386\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 2\n",
"1.5847597491173517\n",
"The running loss is:\n",
"25.072028666734695\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 3\n",
"1.1939061269873665\n",
"The running loss is:\n",
"22.292101874947548\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 4\n",
"1.061528660711788\n",
"The running loss is:\n",
"23.1343837082386\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 5\n",
"1.1016373194399334\n",
"The running loss is:\n",
"21.76330964267254\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 6\n",
"1.0363480782225019\n",
"The running loss is:\n",
"21.404461607336998\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 7\n",
"1.019260076539857\n",
"The running loss is:\n",
"19.915255278348923\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 8\n",
"0.9483454894451868\n",
"The running loss is:\n",
"19.895478509366512\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 9\n",
"0.9474037385412625\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 14.941013\n",
"48 30755 ... 15.908203\n",
"49 30756 ... 16.418524\n",
"50 30757 ... 16.714504\n",
"51 30758 ... 16.909929\n",
"52 30759 ... 17.058176\n",
"53 30760 ... 17.184292\n",
"54 30761 ... 16.904070\n",
"55 30762 ... 16.829170\n",
"56 30763 ... 16.850595\n",
"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
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"name": "stderr"
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{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 64pwuc2m \n",
"\n",
"wandb: Agent Starting Run: s51msur4 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 1\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: s51msur4\n"
],
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{
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"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/s51msur4
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"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
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" framework: torch\n",
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" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
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" interpolate: false\n",
" relevant_cols:\n",
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" scaler: StandardScaler\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
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" desc: null\n",
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" - MSE\n",
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" value: MultiAttnHeadSimple\n",
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" seq_len: 1\n",
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" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"20.703781209886074\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 0\n",
"1.0351890604943037\n",
"The running loss is:\n",
"47.7876605540514\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 1\n",
"2.38938302770257\n",
"The running loss is:\n",
"35.47767253220081\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 2\n",
"1.7738836266100406\n",
"The running loss is:\n",
"23.832139432430267\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 3\n",
"1.1916069716215134\n",
"The running loss is:\n",
"21.081158697605133\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 4\n",
"1.0540579348802566\n",
"The running loss is:\n",
"20.350356683135033\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 5\n",
"1.0175178341567517\n",
"The running loss is:\n",
"19.832687944173813\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 6\n",
"0.9916343972086906\n",
"The running loss is:\n",
"19.82853750884533\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 7\n",
"0.9914268754422665\n",
"The running loss is:\n",
"19.4885743111372\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 8\n",
"0.97442871555686\n",
"The running loss is:\n",
"18.965040057897568\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 9\n",
"0.9482520028948784\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
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{
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"test_data scale\n",
"Un-transforming data\n"
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{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
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{
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"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"47 30754 ... 7.287391\n",
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"49 30756 ... 3.617318\n",
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"52 30759 ... 1.509749\n",
"53 30760 ... 0.913731\n",
"54 30761 ... 2.950763\n",
"55 30762 ... 3.306514\n",
"56 30763 ... 3.059012\n",
"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
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"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
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{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: s51msur4 \n",
"\n",
"wandb: Agent Starting Run: wx5xxkqb with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 1\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: wx5xxkqb\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/wx5xxkqb
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
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" desc: null\n",
" value:\n",
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" class: default\n",
" forecast_history: 1\n",
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" relevant_cols:\n",
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" scaler: StandardScaler\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
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" file_path: Colorado_Douglas County.csv\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
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" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
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" desc: null\n",
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" - MSE\n",
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"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"20.458090774714947\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 0\n",
"0.9741947987959498\n",
"The running loss is:\n",
"24.059880753979087\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 1\n",
"1.1457086073323375\n",
"The running loss is:\n",
"23.21456527709961\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 2\n",
"1.1054554893856956\n",
"The running loss is:\n",
"28.819509647786617\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 3\n",
"1.3723576022755533\n",
"The running loss is:\n",
"31.193957291543484\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 4\n",
"1.4854265376925468\n",
"The running loss is:\n",
"27.668494045734406\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 5\n",
"1.3175473355111622\n",
"The running loss is:\n",
"25.656272009015083\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 6\n",
"1.2217272385245277\n",
"The running loss is:\n",
"20.36942693591118\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 7\n",
"0.9699727112338656\n",
"The running loss is:\n",
"15.879903003573418\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 8\n",
"0.7561858573130199\n",
"The running loss is:\n",
"16.215510118752718\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 9\n",
"0.7721671485120342\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 12.331620\n",
"48 30755 ... 12.283362\n",
"49 30756 ... 12.453766\n",
"50 30757 ... 12.701273\n",
"51 30758 ... 12.975966\n",
"52 30759 ... 13.260247\n",
"53 30760 ... 13.547908\n",
"54 30761 ... 12.524818\n",
"55 30762 ... 12.351486\n",
"56 30763 ... 12.477787\n",
"\n",
"[11 rows x 32 columns]\n"
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"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: wx5xxkqb \n",
"\n",
"wandb: Agent Starting Run: 0wqxnael with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 1\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: 0wqxnael\n"
],
"name": "stdout"
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{
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"data": {
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"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/0wqxnael
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
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" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
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" class: default\n",
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" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
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" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
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"forward_params:\n",
" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 1\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
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" value: MultiAttnHeadSimple\n",
"model_params:\n",
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" forecast_length: 2\n",
" number_time_series: 3\n",
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" seq_len: 1\n",
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" desc: null\n",
" value: PyTorch\n",
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" value: Adam\n",
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" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"25.328899294137955\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 0\n",
"1.206138061625617\n",
"The running loss is:\n",
"28.402115911245346\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 1\n",
"1.3524817100593023\n",
"The running loss is:\n",
"27.489022433757782\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 2\n",
"1.3090010682741802\n",
"The running loss is:\n",
"32.18459129333496\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 3\n",
"1.532599585396903\n",
"The running loss is:\n",
"33.80143202841282\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 4\n",
"1.6095920013529914\n",
"The running loss is:\n",
"32.85577954351902\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 5\n",
"1.564560930643763\n",
"The running loss is:\n",
"30.47883702814579\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 6\n",
"1.4513731918164663\n",
"The running loss is:\n",
"25.70555293187499\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 7\n",
"1.2240739491369044\n",
"The running loss is:\n",
"20.333487920463085\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 8\n",
"0.9682613295458612\n",
"The running loss is:\n",
"18.726626021787524\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 9\n",
"0.8917440962755964\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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{
"output_type": "stream",
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
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{
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"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 13.114093\n",
"48 30755 ... 13.178655\n",
"49 30756 ... 13.227503\n",
"50 30757 ... 13.271365\n",
"51 30758 ... 13.313645\n",
"52 30759 ... 13.355424\n",
"53 30760 ... 13.397043\n",
"54 30761 ... 13.240062\n",
"55 30762 ... 13.218620\n",
"56 30763 ... 13.240183\n",
"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 0wqxnael \n",
"\n",
"wandb: Agent Starting Run: vi2glmaj with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 1\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: vi2glmaj\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/vi2glmaj
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" "
],
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""
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 1\n",
" forecast_length: 3\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
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"forward_params:\n",
" desc: null\n",
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"inference_params:\n",
" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 1\n",
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" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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" desc: null\n",
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" - MSE\n",
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" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"20.522139191627502\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 0\n",
"1.0261069595813752\n",
"The running loss is:\n",
"28.824470579624176\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 1\n",
"1.4412235289812088\n",
"The running loss is:\n",
"26.96215519309044\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 2\n",
"1.348107759654522\n",
"The running loss is:\n",
"24.277756571769714\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 3\n",
"1.2138878285884858\n",
"The running loss is:\n",
"39.18795786798\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 4\n",
"1.9593978933990002\n",
"The running loss is:\n",
"27.062116272747517\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 5\n",
"1.353105813637376\n",
"The running loss is:\n",
"31.32304859161377\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 6\n",
"1.5661524295806886\n",
"The running loss is:\n",
"25.954569905996323\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 7\n",
"1.297728495299816\n",
"The running loss is:\n",
"20.310090392827988\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 8\n",
"1.0155045196413994\n",
"The running loss is:\n",
"18.296321973204613\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 9\n",
"0.9148160986602306\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 8.719911\n",
"48 30755 ... 7.223289\n",
"49 30756 ... 6.481489\n",
"50 30757 ... 5.944383\n",
"51 30758 ... 5.462785\n",
"52 30759 ... 4.996240\n",
"53 30760 ... 4.533777\n",
"54 30761 ... 6.424037\n",
"55 30762 ... 6.600693\n",
"56 30763 ... 6.312653\n",
"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: vi2glmaj \n",
"\n",
"wandb: Agent Starting Run: t6tt7nnl with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 1\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: t6tt7nnl\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/t6tt7nnl
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 1\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 1\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
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" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 1\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 1\n",
" number_time_series: 3\n",
" output_seq_len: 1\n",
" seq_len: 1\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
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"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"61.04869698733091\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 0\n",
"2.9070808089205196\n",
"The running loss is:\n",
"24.786502487957478\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 1\n",
"1.1803096422836894\n",
"The running loss is:\n",
"30.512474812567234\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 2\n",
"1.4529749910746301\n",
"The running loss is:\n",
"22.967344410717487\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 3\n",
"1.0936830671770232\n",
"The running loss is:\n",
"25.316022649407387\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 4\n",
"1.2055248880670184\n",
"The running loss is:\n",
"23.791697189211845\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 5\n",
"1.1329379613910402\n",
"The running loss is:\n",
"20.797373056411743\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 6\n",
"0.9903510979243687\n",
"The running loss is:\n",
"18.34804441407323\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 7\n",
"0.8737164006701538\n",
"The running loss is:\n",
"16.632033981382847\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 8\n",
"0.7920016181610879\n",
"The running loss is:\n",
"16.302831880748272\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 9\n",
"0.7763253276546797\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 11.427103\n",
"48 30755 ... 11.119713\n",
"49 30756 ... 11.244295\n",
"50 30757 ... 11.516330\n",
"51 30758 ... 11.838696\n",
"52 30759 ... 12.178244\n",
"53 30760 ... 12.523656\n",
"54 30761 ... 11.264505\n",
"55 30762 ... 11.064211\n",
"56 30763 ... 11.225350\n",
"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: t6tt7nnl \n",
"\n",
"wandb: Agent Starting Run: i0dy7151 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 1\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: i0dy7151\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/i0dy7151
\n",
" "
],
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""
]
},
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{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 1\n",
" forecast_length: 2\n",
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" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 1\n",
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" desc: null\n",
" value: {}\n",
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" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 1\n",
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" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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" desc: null\n",
" value:\n",
" - MSE\n",
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" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"69.45899105072021\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 0\n",
"3.3075710024152483\n",
"The running loss is:\n",
"24.351533740758896\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 1\n",
"1.1595968447980427\n",
"The running loss is:\n",
"38.97736042737961\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 2\n",
"1.8560647822561718\n",
"The running loss is:\n",
"25.299872055649757\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 3\n",
"1.204755812173798\n",
"The running loss is:\n",
"23.097379501909018\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 4\n",
"1.09987521437662\n",
"The running loss is:\n",
"25.473997458815575\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 5\n",
"1.2130474980388368\n",
"The running loss is:\n",
"22.643349528312683\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 6\n",
"1.0782547394434612\n",
"The running loss is:\n",
"18.14205700904131\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 7\n",
"0.8639074766210147\n",
"The running loss is:\n",
"16.48433183133602\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 8\n",
"0.7849681824445724\n",
"The running loss is:\n",
"16.34719529747963\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 9\n",
"0.7784378713085538\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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},
{
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"Un-transforming data\n"
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"name": "stdout"
},
{
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"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
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" Unnamed: 0 ... preds\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 11.766082\n",
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"49 30756 ... 11.440730\n",
"50 30757 ... 11.526842\n",
"51 30758 ... 11.645089\n",
"52 30759 ... 11.773837\n",
"53 30760 ... 11.906017\n",
"54 30761 ... 11.408577\n",
"55 30762 ... 11.336123\n",
"56 30763 ... 11.402551\n",
"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: i0dy7151 \n",
"\n",
"wandb: Agent Starting Run: 4tuwhbc3 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 1\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
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],
"name": "stdout"
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{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/4tuwhbc3
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
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" framework: torch\n",
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" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
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" file_path: Colorado_Douglas County.csv\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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" desc: null\n",
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" - MSE\n",
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"model_params:\n",
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" seq_len: 1\n",
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" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"73.17438182234764\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 0\n",
"3.658719091117382\n",
"The running loss is:\n",
"24.5871611982584\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 1\n",
"1.22935805991292\n",
"The running loss is:\n",
"48.73001056909561\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 2\n",
"2.4365005284547805\n",
"The running loss is:\n",
"35.53122544288635\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 3\n",
"1.7765612721443176\n",
"The running loss is:\n",
"24.193623542785645\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 4\n",
"1.2096811771392821\n",
"The running loss is:\n",
"31.478034928441048\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 5\n",
"1.5739017464220524\n",
"The running loss is:\n",
"26.469323992729187\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 6\n",
"1.3234661996364594\n",
"The running loss is:\n",
"21.868590533733368\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 7\n",
"1.0934295266866685\n",
"The running loss is:\n",
"17.746363550424576\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 8\n",
"0.8873181775212288\n",
"The running loss is:\n",
"16.37228138744831\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 9\n",
"0.8186140693724155\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
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{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 10.991632\n",
"48 30755 ... 9.842609\n",
"49 30756 ... 8.999443\n",
"50 30757 ... 8.265136\n",
"51 30758 ... 7.569574\n",
"52 30759 ... 6.887804\n",
"53 30760 ... 6.210940\n",
"54 30761 ... 8.575280\n",
"55 30762 ... 8.982585\n",
"56 30763 ... 8.693344\n",
"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 4tuwhbc3 \n",
"\n",
"wandb: Agent Starting Run: 0r1mvx0k with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 2\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: 0r1mvx0k\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/0r1mvx0k
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" "
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""
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
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" desc: null\n",
" value:\n",
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" forecast_history: 2\n",
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" relevant_cols:\n",
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" - month\n",
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" test_path: Colorado_Douglas County.csv\n",
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" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 2\n",
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" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
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" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
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" desc: null\n",
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" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"23.008637461811304\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 0\n",
"1.0956494029433954\n",
"The running loss is:\n",
"32.2327605355531\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 1\n",
"1.5348933588358618\n",
"The running loss is:\n",
"17.726538762450218\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 2\n",
"0.8441208934500104\n",
"The running loss is:\n",
"12.940901616588235\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 3\n",
"0.6162334103137255\n",
"The running loss is:\n",
"16.331525344401598\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 4\n",
"0.7776916830667427\n",
"The running loss is:\n",
"12.3541901409626\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 5\n",
"0.5882947686172667\n",
"The running loss is:\n",
"12.735355507582426\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 6\n",
"0.6064455003610679\n",
"The running loss is:\n",
"13.34062596410513\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 7\n",
"0.6352679030526251\n",
"The running loss is:\n",
"11.95759018138051\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 8\n",
"0.5694090562562147\n",
"The running loss is:\n",
"12.26656811311841\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 9\n",
"0.5841222911008767\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 2, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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},
{
"output_type": "stream",
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
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"48 30755 ... 15.381114\n",
"49 30756 ... 14.857310\n",
"50 30757 ... 15.986811\n",
"51 30758 ... 15.042921\n",
"52 30759 ... 14.311747\n",
"53 30760 ... 12.546846\n",
"54 30761 ... 14.352466\n",
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"56 30763 ... 16.995480\n",
"\n",
"[12 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
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{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 0r1mvx0k \n",
"\n",
"wandb: Agent Starting Run: e62ibr45 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 2\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: e62ibr45\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/e62ibr45
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 2\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 2\n",
"forward_params:\n",
" desc: null\n",
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" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 2\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 2\n",
" number_time_series: 3\n",
" output_seq_len: 2\n",
" seq_len: 2\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 2\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"22.77712646126747\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 0\n",
"1.1388563230633735\n",
"The running loss is:\n",
"30.30465880036354\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 1\n",
"1.515232940018177\n",
"The running loss is:\n",
"19.663687139749527\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 2\n",
"0.9831843569874763\n",
"The running loss is:\n",
"17.537601500749588\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 3\n",
"0.8768800750374794\n",
"The running loss is:\n",
"17.679495960474014\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 4\n",
"0.8839747980237007\n",
"The running loss is:\n",
"15.744170039892197\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 5\n",
"0.7872085019946098\n",
"The running loss is:\n",
"15.426739200949669\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 6\n",
"0.7713369600474834\n",
"The running loss is:\n",
"14.944714151322842\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 7\n",
"0.7472357075661421\n",
"The running loss is:\n",
"14.250869244337082\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 8\n",
"0.712543462216854\n",
"The running loss is:\n",
"14.41989190876484\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 9\n",
"0.720994595438242\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 2, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 10.836431\n",
"48 30755 ... 14.815100\n",
"49 30756 ... 13.822679\n",
"50 30757 ... 14.759495\n",
"51 30758 ... 13.484217\n",
"52 30759 ... 12.383018\n",
"53 30760 ... 10.215312\n",
"54 30761 ... 12.387611\n",
"55 30762 ... 13.979239\n",
"56 30763 ... 14.619460\n",
"\n",
"[12 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
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{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: e62ibr45 \n",
"\n",
"wandb: Agent Starting Run: 0g2cidja with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 2\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: 0g2cidja\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/0g2cidja
\n",
" "
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""
]
},
"metadata": {
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{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 2\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 2\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 2\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 2\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
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"training_params:\n",
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" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
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" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"21.578702680766582\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 0\n",
"1.078935134038329\n",
"The running loss is:\n",
"28.895316019654274\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 1\n",
"1.4447658009827138\n",
"The running loss is:\n",
"17.934798389673233\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 2\n",
"0.8967399194836616\n",
"The running loss is:\n",
"15.32413261756301\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 3\n",
"0.7662066308781504\n",
"The running loss is:\n",
"15.212896093726158\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 4\n",
"0.7606448046863079\n",
"The running loss is:\n",
"13.6849125623703\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 5\n",
"0.684245628118515\n",
"The running loss is:\n",
"15.095305874943733\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 6\n",
"0.7547652937471867\n",
"The running loss is:\n",
"13.407148011028767\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 7\n",
"0.6703574005514383\n",
"The running loss is:\n",
"14.454618975520134\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 8\n",
"0.7227309487760067\n",
"The running loss is:\n",
"13.429822385311127\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 9\n",
"0.6714911192655564\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 2, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 11.413411\n",
"48 30755 ... 15.669946\n",
"49 30756 ... 17.122110\n",
"50 30757 ... 18.615124\n",
"51 30758 ... 19.127787\n",
"52 30759 ... 19.283003\n",
"53 30760 ... 18.859772\n",
"54 30761 ... 21.885056\n",
"55 30762 ... 23.855570\n",
"56 30763 ... 25.221436\n",
"\n",
"[12 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 0g2cidja \n",
"\n",
"wandb: Agent Starting Run: rjep75dc with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 2\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: rjep75dc\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/rjep75dc
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 2\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 2\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 2\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 1\n",
" number_time_series: 3\n",
" output_seq_len: 1\n",
" seq_len: 2\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 1\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"18.55631679482758\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 0\n",
"0.8836341330870277\n",
"The running loss is:\n",
"39.76102647557855\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 1\n",
"1.893382213122788\n",
"The running loss is:\n",
"31.392640566453338\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 2\n",
"1.4948876460215874\n",
"The running loss is:\n",
"21.55244082212448\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 3\n",
"1.0263067058154516\n",
"The running loss is:\n",
"13.321244258899242\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 4\n",
"0.6343449647094876\n",
"The running loss is:\n",
"16.369411423802376\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 5\n",
"0.7794957820858274\n",
"The running loss is:\n",
"12.878714980557561\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 6\n",
"0.6132721419313124\n",
"The running loss is:\n",
"15.277130480855703\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 7\n",
"0.7274824038502716\n",
"The running loss is:\n",
"12.423281671479344\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 8\n",
"0.5915848414990164\n",
"The running loss is:\n",
"13.389100320637226\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 9\n",
"0.6375762057446298\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 2, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 13.093603\n",
"48 30755 ... 15.438350\n",
"49 30756 ... 15.362393\n",
"50 30757 ... 15.736447\n",
"51 30758 ... 15.006408\n",
"52 30759 ... 14.255008\n",
"53 30760 ... 12.908654\n",
"54 30761 ... 14.277620\n",
"55 30762 ... 15.742886\n",
"56 30763 ... 16.026230\n",
"\n",
"[12 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: rjep75dc \n",
"\n",
"wandb: Agent Starting Run: 1hy1myeb with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 2\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: 1hy1myeb\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/1hy1myeb
\n",
" "
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""
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 2\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 2\n",
"forward_params:\n",
" desc: null\n",
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" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 2\n",
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" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 2\n",
" number_time_series: 3\n",
" output_seq_len: 2\n",
" seq_len: 2\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 2\n",
"sweep:\n",
" desc: null\n",
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"training_params:\n",
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" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"19.790002673864365\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 0\n",
"0.9895001336932182\n",
"The running loss is:\n",
"35.51101356744766\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 1\n",
"1.7755506783723831\n",
"The running loss is:\n",
"29.900236278772354\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 2\n",
"1.4950118139386177\n",
"The running loss is:\n",
"20.32610148191452\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 3\n",
"1.016305074095726\n",
"The running loss is:\n",
"17.535978391766548\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 4\n",
"0.8767989195883275\n",
"The running loss is:\n",
"15.788296699523926\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 5\n",
"0.7894148349761962\n",
"The running loss is:\n",
"15.298003315925598\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 6\n",
"0.76490016579628\n",
"The running loss is:\n",
"14.471397161483765\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 7\n",
"0.7235698580741883\n",
"The running loss is:\n",
"15.182393252849579\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 8\n",
"0.759119662642479\n",
"The running loss is:\n",
"15.049454137682915\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 9\n",
"0.7524727068841457\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 2, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 10.637438\n",
"48 30755 ... 13.303226\n",
"49 30756 ... 12.201837\n",
"50 30757 ... 12.177489\n",
"51 30758 ... 10.806701\n",
"52 30759 ... 9.582183\n",
"53 30760 ... 7.934246\n",
"54 30761 ... 8.110060\n",
"55 30762 ... 10.489552\n",
"56 30763 ... 10.417169\n",
"\n",
"[12 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 1hy1myeb \n",
"\n",
"wandb: Agent Starting Run: izha8psp with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 2\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: izha8psp\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/izha8psp
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 2\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 2\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 2\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 2\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"16.73946076631546\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 0\n",
"0.836973038315773\n",
"The running loss is:\n",
"34.69972918741405\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 1\n",
"1.7349864593707025\n",
"The running loss is:\n",
"28.933668479323387\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 2\n",
"1.4466834239661694\n",
"The running loss is:\n",
"20.98772995173931\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 3\n",
"1.0493864975869656\n",
"The running loss is:\n",
"14.910560678690672\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 4\n",
"0.7455280339345336\n",
"The running loss is:\n",
"13.784054175019264\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 5\n",
"0.6892027087509632\n",
"The running loss is:\n",
"14.498991958796978\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 6\n",
"0.7249495979398489\n",
"The running loss is:\n",
"13.606230936944485\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 7\n",
"0.6803115468472243\n",
"The running loss is:\n",
"14.566328644752502\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 8\n",
"0.7283164322376251\n",
"The running loss is:\n",
"12.793043170124292\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 9\n",
"0.6396521585062146\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 2, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 11.115752\n",
"48 30755 ... 14.251652\n",
"49 30756 ... 15.619260\n",
"50 30757 ... 16.408094\n",
"51 30758 ... 16.587444\n",
"52 30759 ... 16.368526\n",
"53 30760 ... 15.831397\n",
"54 30761 ... 17.615082\n",
"55 30762 ... 19.396448\n",
"56 30763 ... 20.256659\n",
"\n",
"[12 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: izha8psp \n",
"\n",
"wandb: Agent Starting Run: j4p3rea7 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 2\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: j4p3rea7\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/j4p3rea7
\n",
" "
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""
]
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{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 2\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 2\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 2\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 1\n",
" number_time_series: 3\n",
" output_seq_len: 1\n",
" seq_len: 2\n",
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" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"17.612260351888835\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 0\n",
"0.8386790643756589\n",
"The running loss is:\n",
"27.575611753884004\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 1\n",
"1.3131243692325716\n",
"The running loss is:\n",
"19.56693585170433\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 2\n",
"0.9317588500811586\n",
"The running loss is:\n",
"29.6243880931288\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 3\n",
"1.4106851472918476\n",
"The running loss is:\n",
"31.01244868338108\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 4\n",
"1.4767832706371944\n",
"The running loss is:\n",
"30.337950587272644\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 5\n",
"1.4446643136796498\n",
"The running loss is:\n",
"20.72286257147789\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 6\n",
"0.9868029795941853\n",
"The running loss is:\n",
"13.726178638637066\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 7\n",
"0.6536275542208126\n",
"The running loss is:\n",
"15.882041074335575\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 8\n",
"0.7562876702064559\n",
"The running loss is:\n",
"13.951960653066635\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 9\n",
"0.6643790787174588\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 2, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
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"48 30755 ... 14.173787\n",
"49 30756 ... 13.942454\n",
"50 30757 ... 14.106256\n",
"51 30758 ... 13.663309\n",
"52 30759 ... 13.262284\n",
"53 30760 ... 12.640742\n",
"54 30761 ... 13.062532\n",
"55 30762 ... 14.247359\n",
"56 30763 ... 14.199184\n",
"\n",
"[12 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: j4p3rea7 \n",
"\n",
"wandb: Agent Starting Run: oyn5vyw0 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 2\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: oyn5vyw0\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/oyn5vyw0
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
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" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
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" desc: null\n",
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" class: default\n",
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" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
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" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
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"forward_params:\n",
" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
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" interpolate_param: false\n",
" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
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" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"19.16664184629917\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 0\n",
"0.9583320923149585\n",
"The running loss is:\n",
"24.30276045203209\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 1\n",
"1.2151380226016044\n",
"The running loss is:\n",
"21.017927818000317\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 2\n",
"1.0508963909000157\n",
"The running loss is:\n",
"25.24866795539856\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 3\n",
"1.262433397769928\n",
"The running loss is:\n",
"29.989633813500404\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 4\n",
"1.4994816906750201\n",
"The running loss is:\n",
"27.833610378205776\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 5\n",
"1.3916805189102888\n",
"The running loss is:\n",
"20.38179862499237\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 6\n",
"1.0190899312496184\n",
"The running loss is:\n",
"19.694613575935364\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 7\n",
"0.9847306787967682\n",
"The running loss is:\n",
"16.29368768632412\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 8\n",
"0.8146843843162059\n",
"The running loss is:\n",
"16.283535540103912\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 9\n",
"0.8141767770051956\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 2, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 10.646613\n",
"48 30755 ... 12.670735\n",
"49 30756 ... 12.202353\n",
"50 30757 ... 12.349521\n",
"51 30758 ... 11.980251\n",
"52 30759 ... 11.627564\n",
"53 30760 ... 11.168602\n",
"54 30761 ... 11.710465\n",
"55 30762 ... 12.506949\n",
"56 30763 ... 12.491008\n",
"\n",
"[12 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: oyn5vyw0 \n",
"\n",
"wandb: Agent Starting Run: ard0kcgk with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 2\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: ard0kcgk\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/ard0kcgk
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" "
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""
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 2\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
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"Torch is using cpu\n",
"The running loss is:\n",
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"The number of items in train is: \n",
"20\n",
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"0.8663033854216338\n",
"The running loss is:\n",
"26.125781033188105\n",
"The number of items in train is: \n",
"20\n",
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"1.3062890516594052\n",
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"20.05863458663225\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 2\n",
"1.0029317293316127\n",
"The running loss is:\n",
"26.94086644053459\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 3\n",
"1.3470433220267295\n",
"The running loss is:\n",
"27.031484097242355\n",
"The number of items in train is: \n",
"20\n",
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"1.3515742048621178\n",
"The running loss is:\n",
"26.107848599553108\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 5\n",
"1.3053924299776554\n",
"The running loss is:\n",
"19.87912854552269\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 6\n",
"0.9939564272761345\n",
"The running loss is:\n",
"19.120233863592148\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 7\n",
"0.9560116931796074\n",
"The running loss is:\n",
"18.272066473960876\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 8\n",
"0.9136033236980439\n",
"The running loss is:\n",
"16.09623235464096\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 9\n",
"0.804811617732048\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 2, 3])\n",
"Add debugging crap below\n"
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"name": "stdout"
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{
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"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
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"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
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"Un-transforming data\n"
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{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
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{
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"53 30760 ... 9.338076\n",
"54 30761 ... 8.713398\n",
"55 30762 ... 9.319012\n",
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"[12 rows x 32 columns]\n"
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"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
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"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
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{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: ard0kcgk \n",
"\n",
"wandb: Agent Starting Run: qm4xgxw1 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 2\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
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],
"name": "stdout"
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{
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"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/qm4xgxw1
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"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
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" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
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" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
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"\n",
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"4.198461220200572\n",
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"The number of items in train is: \n",
"21\n",
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"1.5428274936441864\n",
"The running loss is:\n",
"44.084197610616684\n",
"The number of items in train is: \n",
"21\n",
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"2.0992475052674613\n",
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"31.271542832255363\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 3\n",
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"24.642942052334547\n",
"The number of items in train is: \n",
"21\n",
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"1.17347343106355\n",
"The running loss is:\n",
"25.46325683966279\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 5\n",
"1.2125360399839424\n",
"The running loss is:\n",
"22.69593182578683\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 6\n",
"1.0807586583708013\n",
"The running loss is:\n",
"22.1004674769938\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 7\n",
"1.0524032131901808\n",
"The running loss is:\n",
"21.082351729273796\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 8\n",
"1.0039215109178\n",
"The running loss is:\n",
"20.709456760436296\n",
"The number of items in train is: \n",
"21\n",
"The loss for epoch 9\n",
"0.9861646076398236\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 2, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
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"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
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{
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"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
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{
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"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 11.968234\n",
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"50 30757 ... 12.427336\n",
"51 30758 ... 12.384806\n",
"52 30759 ... 12.386845\n",
"53 30760 ... 12.371067\n",
"54 30761 ... 11.455049\n",
"55 30762 ... 12.432656\n",
"56 30763 ... 12.267653\n",
"\n",
"[12 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
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"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
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{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: qm4xgxw1 \n",
"\n",
"wandb: Agent Starting Run: xau7eqeu with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 2\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: xau7eqeu\n"
],
"name": "stdout"
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{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/xau7eqeu
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
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" training_path: Colorado_Douglas County.csv\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
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" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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"metrics:\n",
" desc: null\n",
" value:\n",
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" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"51.44850631058216\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 0\n",
"2.572425315529108\n",
"The running loss is:\n",
"26.536537259817123\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 1\n",
"1.3268268629908562\n",
"The running loss is:\n",
"25.394971758127213\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 2\n",
"1.2697485879063606\n",
"The running loss is:\n",
"26.157265178859234\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 3\n",
"1.3078632589429617\n",
"The running loss is:\n",
"26.907141968607903\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 4\n",
"1.345357098430395\n",
"The running loss is:\n",
"23.60898245871067\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 5\n",
"1.1804491229355336\n",
"The running loss is:\n",
"21.588230818510056\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 6\n",
"1.0794115409255027\n",
"The running loss is:\n",
"23.299431294202805\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 7\n",
"1.1649715647101402\n",
"The running loss is:\n",
"17.95345228165388\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 8\n",
"0.897672614082694\n",
"The running loss is:\n",
"21.56754533946514\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 9\n",
"1.078377266973257\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 2, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"49 30756 ... 8.578013\n",
"50 30757 ... 8.423813\n",
"51 30758 ... 8.186283\n",
"52 30759 ... 8.086294\n",
"53 30760 ... 7.967240\n",
"54 30761 ... 8.324524\n",
"55 30762 ... 8.337108\n",
"56 30763 ... 8.307590\n",
"\n",
"[12 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: xau7eqeu \n",
"\n",
"wandb: Agent Starting Run: falknk2c with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 2\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
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],
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{
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"data": {
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"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
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" value:\n",
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" class: default\n",
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" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
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" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
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" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
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" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
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"\n",
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"The number of items in train is: \n",
"20\n",
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"1.406201571971178\n",
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"24.375909984111786\n",
"The number of items in train is: \n",
"20\n",
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"1.2187954992055894\n",
"The running loss is:\n",
"22.562284395098686\n",
"The number of items in train is: \n",
"20\n",
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"1.1281142197549343\n",
"The running loss is:\n",
"28.00324049592018\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 4\n",
"1.4001620247960092\n",
"The running loss is:\n",
"21.4647678732872\n",
"The number of items in train is: \n",
"20\n",
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"1.0732383936643601\n",
"The running loss is:\n",
"21.226560071110725\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 6\n",
"1.0613280035555364\n",
"The running loss is:\n",
"20.05168192088604\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 7\n",
"1.002584096044302\n",
"The running loss is:\n",
"19.073723807930946\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 8\n",
"0.9536861903965473\n",
"The running loss is:\n",
"20.08955078572035\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 9\n",
"1.0044775392860175\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 2, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
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"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
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"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 10.038617\n",
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"50 30757 ... 10.665849\n",
"51 30758 ... 10.829441\n",
"52 30759 ... 10.893164\n",
"53 30760 ... 11.022404\n",
"54 30761 ... 9.990615\n",
"55 30762 ... 10.360154\n",
"56 30763 ... 10.527678\n",
"\n",
"[12 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: falknk2c \n",
"\n",
"wandb: Agent Starting Run: 6sarts3o with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 3\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: 6sarts3o\n"
],
"name": "stdout"
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{
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"data": {
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"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/6sarts3o
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"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 3\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 3\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 3\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 1\n",
" number_time_series: 3\n",
" output_seq_len: 1\n",
" seq_len: 3\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 1\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"13.16620772331953\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 0\n",
"0.6583103861659765\n",
"The running loss is:\n",
"47.089191913604736\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 1\n",
"2.354459595680237\n",
"The running loss is:\n",
"20.295180901885033\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 2\n",
"1.0147590450942516\n",
"The running loss is:\n",
"14.66391147999093\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 3\n",
"0.7331955739995465\n",
"The running loss is:\n",
"14.51472514308989\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 4\n",
"0.7257362571544945\n",
"The running loss is:\n",
"11.414592620916665\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 5\n",
"0.5707296310458332\n",
"The running loss is:\n",
"10.380168374627829\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 6\n",
"0.5190084187313915\n",
"The running loss is:\n",
"10.854458432644606\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 7\n",
"0.5427229216322302\n",
"The running loss is:\n",
"9.902051273267716\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 8\n",
"0.4951025636633858\n",
"The running loss is:\n",
"11.478069743141532\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 9\n",
"0.5739034871570766\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 3, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 4.791970\n",
"48 30755 ... 4.017214\n",
"49 30756 ... 9.296926\n",
"50 30757 ... 8.501606\n",
"51 30758 ... 7.561368\n",
"52 30759 ... 6.628009\n",
"53 30760 ... 4.479429\n",
"54 30761 ... 3.208868\n",
"55 30762 ... 2.426350\n",
"56 30763 ... 6.978889\n",
"\n",
"[13 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 6sarts3o \n",
"\n",
"wandb: Agent Starting Run: u7zvotqr with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 3\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: u7zvotqr\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/u7zvotqr
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 3\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 3\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 3\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 2\n",
" number_time_series: 3\n",
" output_seq_len: 2\n",
" seq_len: 3\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
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" desc: null\n",
" value: 2\n",
"sweep:\n",
" desc: null\n",
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"training_params:\n",
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" batch_size: 2\n",
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" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"20.250229328870773\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 0\n",
"1.0125114664435386\n",
"The running loss is:\n",
"36.03919892013073\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 1\n",
"1.8019599460065365\n",
"The running loss is:\n",
"21.369008541107178\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 2\n",
"1.068450427055359\n",
"The running loss is:\n",
"16.745819223113358\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 3\n",
"0.8372909611556679\n",
"The running loss is:\n",
"16.19626347720623\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 4\n",
"0.8098131738603115\n",
"The running loss is:\n",
"15.289014890789986\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 5\n",
"0.7644507445394992\n",
"The running loss is:\n",
"14.291767127811909\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 6\n",
"0.7145883563905955\n",
"The running loss is:\n",
"13.00631546229124\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 7\n",
"0.650315773114562\n",
"The running loss is:\n",
"12.850601639598608\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 8\n",
"0.6425300819799304\n",
"The running loss is:\n",
"11.07451168447733\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 9\n",
"0.5537255842238664\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 3, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 7.846800\n",
"48 30755 ... 8.844935\n",
"49 30756 ... 11.833019\n",
"50 30757 ... 11.595754\n",
"51 30758 ... 10.915969\n",
"52 30759 ... 9.609382\n",
"53 30760 ... 6.918744\n",
"54 30761 ... 7.512626\n",
"55 30762 ... 9.482866\n",
"56 30763 ... 11.247615\n",
"\n",
"[13 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: u7zvotqr \n",
"\n",
"wandb: Agent Starting Run: cf5ckshz with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 3\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: cf5ckshz\n"
],
"name": "stdout"
},
{
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"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/cf5ckshz
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"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
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" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 3\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 3\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
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" forecast_length: 3\n",
" number_time_series: 3\n",
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" seq_len: 3\n",
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" desc: null\n",
" value: PyTorch\n",
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" desc: null\n",
" value: Adam\n",
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" batch_size: 2\n",
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" epochs: 10\n",
" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"16.24230197072029\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 0\n",
"0.8548579984589627\n",
"The running loss is:\n",
"33.577625170350075\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 1\n",
"1.767243430018425\n",
"The running loss is:\n",
"17.50975675880909\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 2\n",
"0.9215661452004784\n",
"The running loss is:\n",
"15.19348393380642\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 3\n",
"0.7996570491477063\n",
"The running loss is:\n",
"14.183778703212738\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 4\n",
"0.7465146685901441\n",
"The running loss is:\n",
"13.036552771925926\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 5\n",
"0.686134356417154\n",
"The running loss is:\n",
"12.580513373017311\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 6\n",
"0.6621322827903848\n",
"The running loss is:\n",
"12.409655019640923\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 7\n",
"0.653139737875838\n",
"The running loss is:\n",
"12.531418025493622\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 8\n",
"0.6595483171312433\n",
"The running loss is:\n",
"11.11167886853218\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 9\n",
"0.5848252036069569\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 3, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 9.913255\n",
"48 30755 ... 10.473210\n",
"49 30756 ... 13.590547\n",
"50 30757 ... 14.313401\n",
"51 30758 ... 14.773838\n",
"52 30759 ... 15.313439\n",
"53 30760 ... 15.069212\n",
"54 30761 ... 17.728813\n",
"55 30762 ... 18.329552\n",
"56 30763 ... 21.203745\n",
"\n",
"[13 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: cf5ckshz \n",
"\n",
"wandb: Agent Starting Run: olx3ydle with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 3\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: olx3ydle\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/olx3ydle
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" "
],
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""
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 3\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
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" scaler: StandardScaler\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 3\n",
"forward_params:\n",
" desc: null\n",
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" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
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" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
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"sweep:\n",
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" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"16.871346639934927\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 0\n",
"0.8435673319967464\n",
"The running loss is:\n",
"38.40473223477602\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 1\n",
"1.920236611738801\n",
"The running loss is:\n",
"31.12108042370528\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 2\n",
"1.556054021185264\n",
"The running loss is:\n",
"24.62357160821557\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 3\n",
"1.2311785804107784\n",
"The running loss is:\n",
"12.468314666301012\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 4\n",
"0.6234157333150506\n",
"The running loss is:\n",
"13.174285745597444\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 5\n",
"0.6587142872798722\n",
"The running loss is:\n",
"11.788977996446192\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 6\n",
"0.5894488998223096\n",
"The running loss is:\n",
"11.11843922547996\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 7\n",
"0.5559219612739981\n",
"The running loss is:\n",
"9.287355293519795\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 8\n",
"0.4643677646759897\n",
"The running loss is:\n",
"9.838816735893488\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 9\n",
"0.4919408367946744\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 3, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 7.513413\n",
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"\n",
"[13 rows x 32 columns]\n"
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"name": "stdout"
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{
"output_type": "stream",
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"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: olx3ydle \n",
"\n",
"wandb: Agent Starting Run: 6d8tazmf with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 3\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: 6d8tazmf\n"
],
"name": "stdout"
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{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/6d8tazmf
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 3\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 3\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 3\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
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" forecast_length: 2\n",
" number_time_series: 3\n",
" output_seq_len: 2\n",
" seq_len: 3\n",
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" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
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" desc: null\n",
" value: 2\n",
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" batch_size: 2\n",
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" epochs: 10\n",
" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"18.881873853504658\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 0\n",
"0.9440936926752329\n",
"The running loss is:\n",
"33.3425434269011\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 1\n",
"1.667127171345055\n",
"The running loss is:\n",
"29.829890869557858\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 2\n",
"1.4914945434778928\n",
"The running loss is:\n",
"25.49375832080841\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 3\n",
"1.2746879160404205\n",
"The running loss is:\n",
"17.11493468284607\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 4\n",
"0.8557467341423035\n",
"The running loss is:\n",
"14.997745260596275\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 5\n",
"0.7498872630298138\n",
"The running loss is:\n",
"14.11250153183937\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 6\n",
"0.7056250765919685\n",
"The running loss is:\n",
"12.541615918278694\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 7\n",
"0.6270807959139347\n",
"The running loss is:\n",
"11.791180847212672\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 8\n",
"0.5895590423606336\n",
"The running loss is:\n",
"11.034595467150211\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 9\n",
"0.5517297733575106\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 3, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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{
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
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{
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"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"49 30756 ... 14.576173\n",
"50 30757 ... 16.192913\n",
"51 30758 ... 17.393833\n",
"52 30759 ... 18.037010\n",
"53 30760 ... 17.864153\n",
"54 30761 ... 22.358480\n",
"55 30762 ... 24.322353\n",
"56 30763 ... 28.962704\n",
"\n",
"[13 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 6d8tazmf \n",
"\n",
"wandb: Agent Starting Run: tsnek2xz with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 3\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: tsnek2xz\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/tsnek2xz
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" "
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""
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},
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
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" desc: null\n",
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" batch_size: 2\n",
" class: default\n",
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" forecast_length: 3\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 3\n",
"forward_params:\n",
" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 3\n",
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" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
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" - MSE\n",
"model_name:\n",
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" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"15.180935945361853\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 0\n",
"0.7989966287032554\n",
"The running loss is:\n",
"32.76849117875099\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 1\n",
"1.7246574304605786\n",
"The running loss is:\n",
"29.06931023299694\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 2\n",
"1.5299636964735233\n",
"The running loss is:\n",
"19.419804587960243\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 3\n",
"1.022094978313697\n",
"The running loss is:\n",
"15.750009074807167\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 4\n",
"0.8289478460424825\n",
"The running loss is:\n",
"13.63320517539978\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 5\n",
"0.7175371144947252\n",
"The running loss is:\n",
"12.82888300716877\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 6\n",
"0.6752043687983563\n",
"The running loss is:\n",
"12.820624247193336\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 7\n",
"0.6747696972207019\n",
"The running loss is:\n",
"12.8362637758255\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 8\n",
"0.6755928303066053\n",
"The running loss is:\n",
"12.048322603106499\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 9\n",
"0.6341222422687631\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 3, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
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"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
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"name": "stderr"
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" Unnamed: 0 ... preds\n",
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"49 30756 ... 14.634971\n",
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"51 30758 ... 15.261534\n",
"52 30759 ... 15.495893\n",
"53 30760 ... 15.244351\n",
"54 30761 ... 18.465002\n",
"55 30762 ... 18.929951\n",
"56 30763 ... 19.493837\n",
"\n",
"[13 rows x 32 columns]\n"
],
"name": "stdout"
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{
"output_type": "stream",
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"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
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{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: tsnek2xz \n",
"\n",
"wandb: Agent Starting Run: ouepskbi with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 3\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
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{
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"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/ouepskbi
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"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
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" python_version: 3.6.9\n",
"batch_size:\n",
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" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
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" file_path: Colorado_Douglas County.csv\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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" desc: null\n",
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" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"25.258195054717362\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 0\n",
"1.2629097527358681\n",
"The running loss is:\n",
"28.71645049750805\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 1\n",
"1.4358225248754024\n",
"The running loss is:\n",
"21.496938847005367\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 2\n",
"1.0748469423502685\n",
"The running loss is:\n",
"32.175556898117065\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 3\n",
"1.6087778449058532\n",
"The running loss is:\n",
"31.53068858385086\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 4\n",
"1.576534429192543\n",
"The running loss is:\n",
"25.01493700221181\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 5\n",
"1.2507468501105905\n",
"The running loss is:\n",
"20.540104411542416\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 6\n",
"1.0270052205771207\n",
"The running loss is:\n",
"13.346534442156553\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 7\n",
"0.6673267221078276\n",
"The running loss is:\n",
"14.965123616158962\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 8\n",
"0.7482561808079481\n",
"The running loss is:\n",
"12.449737954884768\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 9\n",
"0.6224868977442384\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 3, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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{
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"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 8.540903\n",
"48 30755 ... 8.264866\n",
"49 30756 ... 11.485750\n",
"50 30757 ... 10.229491\n",
"51 30758 ... 9.189299\n",
"52 30759 ... 8.309838\n",
"53 30760 ... 6.608351\n",
"54 30761 ... 6.017721\n",
"55 30762 ... 5.683835\n",
"56 30763 ... 8.788109\n",
"\n",
"[13 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: ouepskbi \n",
"\n",
"wandb: Agent Starting Run: hvnouxk7 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 3\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: hvnouxk7\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/hvnouxk7
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" "
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
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" value:\n",
" batch_size: 2\n",
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" forecast_history: 3\n",
" forecast_length: 2\n",
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" relevant_cols:\n",
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" scaler: StandardScaler\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
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"forward_params:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
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" optimizer: Adam\n",
"wandb:\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"22.307929329574108\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 0\n",
"1.1153964664787055\n",
"The running loss is:\n",
"24.764474764466286\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 1\n",
"1.2382237382233143\n",
"The running loss is:\n",
"20.000230103731155\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 2\n",
"1.0000115051865577\n",
"The running loss is:\n",
"27.805497139692307\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 3\n",
"1.3902748569846153\n",
"The running loss is:\n",
"25.04505816102028\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 4\n",
"1.2522529080510139\n",
"The running loss is:\n",
"27.622999258339405\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 5\n",
"1.3811499629169703\n",
"The running loss is:\n",
"21.294054619967937\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 6\n",
"1.064702730998397\n",
"The running loss is:\n",
"18.15154094994068\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 7\n",
"0.907577047497034\n",
"The running loss is:\n",
"18.175693213939667\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 8\n",
"0.9087846606969834\n",
"The running loss is:\n",
"16.293617084622383\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 9\n",
"0.8146808542311191\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 3, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
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"48 30755 ... 11.301517\n",
"49 30756 ... 12.338721\n",
"50 30757 ... 12.630889\n",
"51 30758 ... 12.970084\n",
"52 30759 ... 13.607054\n",
"53 30760 ... 14.193722\n",
"54 30761 ... 14.774322\n",
"55 30762 ... 14.798644\n",
"56 30763 ... 14.683531\n",
"\n",
"[13 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: hvnouxk7 \n",
"\n",
"wandb: Agent Starting Run: j32zrla3 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 3\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: j32zrla3\n"
],
"name": "stdout"
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{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/j32zrla3
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 3\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 3\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 3\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 3\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"17.678802952170372\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 0\n",
"0.9304633132721248\n",
"The running loss is:\n",
"23.775851890444756\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 1\n",
"1.2513606258128818\n",
"The running loss is:\n",
"19.22152805328369\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 2\n",
"1.0116593712254573\n",
"The running loss is:\n",
"22.740102007985115\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 3\n",
"1.1968474741044797\n",
"The running loss is:\n",
"23.430920630693436\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 4\n",
"1.233206348983865\n",
"The running loss is:\n",
"20.96139857172966\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 5\n",
"1.1032315037752454\n",
"The running loss is:\n",
"16.538328647613525\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 6\n",
"0.8704383498743961\n",
"The running loss is:\n",
"16.061340644955635\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 7\n",
"0.8453337181555597\n",
"The running loss is:\n",
"12.803979389369488\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 8\n",
"0.6738936520720783\n",
"The running loss is:\n",
"13.952543005347252\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 9\n",
"0.734344368702487\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 3, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 8.579448\n",
"48 30755 ... 8.149343\n",
"49 30756 ... 9.415684\n",
"50 30757 ... 8.551306\n",
"51 30758 ... 7.895852\n",
"52 30759 ... 7.565929\n",
"53 30760 ... 6.785355\n",
"54 30761 ... 6.457073\n",
"55 30762 ... 6.417875\n",
"56 30763 ... 7.045417\n",
"\n",
"[13 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: j32zrla3 \n",
"\n",
"wandb: Agent Starting Run: vwt7qbzu with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 3\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: vwt7qbzu\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/vwt7qbzu
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
"tags": []
}
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{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 3\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 3\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 3\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 1\n",
" number_time_series: 3\n",
" output_seq_len: 1\n",
" seq_len: 3\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 1\n",
"sweep:\n",
" desc: null\n",
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"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"109.38623917661607\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 0\n",
"5.4693119588308035\n",
"The running loss is:\n",
"36.06812307983637\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 1\n",
"1.8034061539918185\n",
"The running loss is:\n",
"27.07236859574914\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 2\n",
"1.353618429787457\n",
"The running loss is:\n",
"19.878866678103805\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 3\n",
"0.9939433339051902\n",
"The running loss is:\n",
"36.85931820055703\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 4\n",
"1.8429659100278513\n",
"The running loss is:\n",
"19.018329231534153\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 5\n",
"0.9509164615767076\n",
"The running loss is:\n",
"22.288700968027115\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 6\n",
"1.1144350484013557\n",
"The running loss is:\n",
"30.49784292280674\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 7\n",
"1.524892146140337\n",
"The running loss is:\n",
"21.91693382896483\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 8\n",
"1.0958466914482414\n",
"The running loss is:\n",
"15.250084459781647\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 9\n",
"0.7625042229890824\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 3, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 9.705070\n",
"48 30755 ... 10.367969\n",
"49 30756 ... 13.145773\n",
"50 30757 ... 12.067879\n",
"51 30758 ... 11.397724\n",
"52 30759 ... 11.419276\n",
"53 30760 ... 10.288182\n",
"54 30761 ... 8.814781\n",
"55 30762 ... 10.714540\n",
"56 30763 ... 12.394072\n",
"\n",
"[13 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: vwt7qbzu \n",
"\n",
"wandb: Agent Starting Run: d9ptfhot with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 3\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: d9ptfhot\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/d9ptfhot
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 3\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 3\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
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" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 3\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 2\n",
" number_time_series: 3\n",
" output_seq_len: 2\n",
" seq_len: 3\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
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" desc: null\n",
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"sweep:\n",
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"training_params:\n",
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" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
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" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"68.95865529216826\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 0\n",
"3.447932764608413\n",
"The running loss is:\n",
"27.954812914133072\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 1\n",
"1.3977406457066537\n",
"The running loss is:\n",
"21.58340122550726\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 2\n",
"1.079170061275363\n",
"The running loss is:\n",
"27.75279625505209\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 3\n",
"1.3876398127526044\n",
"The running loss is:\n",
"29.550814539194107\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 4\n",
"1.4775407269597054\n",
"The running loss is:\n",
"26.29482465982437\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 5\n",
"1.3147412329912185\n",
"The running loss is:\n",
"23.998366855084896\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 6\n",
"1.1999183427542448\n",
"The running loss is:\n",
"20.050680205225945\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 7\n",
"1.0025340102612972\n",
"The running loss is:\n",
"20.464960746467113\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 8\n",
"1.0232480373233557\n",
"The running loss is:\n",
"19.200842931866646\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 9\n",
"0.9600421465933323\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 3, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 11.980211\n",
"48 30755 ... 11.990289\n",
"49 30756 ... 12.143848\n",
"50 30757 ... 12.068938\n",
"51 30758 ... 12.045371\n",
"52 30759 ... 12.029554\n",
"53 30760 ... 12.001999\n",
"54 30761 ... 11.946033\n",
"55 30762 ... 11.977056\n",
"56 30763 ... 12.094289\n",
"\n",
"[13 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: d9ptfhot \n",
"\n",
"wandb: Agent Starting Run: x2eijjhc with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 3\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: x2eijjhc\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/x2eijjhc
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" "
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""
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 3\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 3\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 3\n",
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" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
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" value:\n",
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" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 3\n",
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" desc: null\n",
" value: PyTorch\n",
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" desc: null\n",
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"sweep:\n",
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" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"51.38577203452587\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 0\n",
"2.7045143176066246\n",
"The running loss is:\n",
"26.914206624031067\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 1\n",
"1.4165371907384772\n",
"The running loss is:\n",
"27.34442164748907\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 2\n",
"1.4391800867099511\n",
"The running loss is:\n",
"21.851982936263084\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 3\n",
"1.1501043650664782\n",
"The running loss is:\n",
"19.491085931658745\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 4\n",
"1.0258466279820393\n",
"The running loss is:\n",
"20.605526842176914\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 5\n",
"1.0845014127461534\n",
"The running loss is:\n",
"17.233258858323097\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 6\n",
"0.9070136241222683\n",
"The running loss is:\n",
"16.62893322110176\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 7\n",
"0.8752070116369348\n",
"The running loss is:\n",
"14.914175763726234\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 8\n",
"0.784956619143486\n",
"The running loss is:\n",
"16.455472081899643\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 9\n",
"0.866077477994718\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 3, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 12.186721\n",
"48 30755 ... 12.263892\n",
"49 30756 ... 15.433131\n",
"50 30757 ... 14.697458\n",
"51 30758 ... 13.453771\n",
"52 30759 ... 13.202712\n",
"53 30760 ... 11.757782\n",
"54 30761 ... 13.192609\n",
"55 30762 ... 13.191557\n",
"56 30763 ... 15.276033\n",
"\n",
"[13 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: x2eijjhc \n",
"\n",
"wandb: Agent Starting Run: ayj47mls with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 4\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: ayj47mls\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/ayj47mls
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 4\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 4\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 4\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 1\n",
" number_time_series: 3\n",
" output_seq_len: 1\n",
" seq_len: 4\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 1\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"18.244433240033686\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 0\n",
"0.9122216620016843\n",
"The running loss is:\n",
"30.7520240098238\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 1\n",
"1.5376012004911899\n",
"The running loss is:\n",
"15.300197042524815\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 2\n",
"0.7650098521262407\n",
"The running loss is:\n",
"12.945850990712643\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 3\n",
"0.6472925495356321\n",
"The running loss is:\n",
"11.861743465065956\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 4\n",
"0.5930871732532979\n",
"The running loss is:\n",
"10.992941904813051\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 5\n",
"0.5496470952406526\n",
"The running loss is:\n",
"11.330213017761707\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 6\n",
"0.5665106508880854\n",
"The running loss is:\n",
"9.959945164620876\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 7\n",
"0.4979972582310438\n",
"The running loss is:\n",
"8.969771122094244\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 8\n",
"0.44848855610471217\n",
"The running loss is:\n",
"9.06965771317482\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 9\n",
"0.453482885658741\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 4, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 8.373440\n",
"48 30755 ... 10.899719\n",
"49 30756 ... 13.438485\n",
"50 30757 ... 13.496451\n",
"51 30758 ... 13.684741\n",
"52 30759 ... 14.650225\n",
"53 30760 ... 16.323957\n",
"54 30761 ... 15.094393\n",
"55 30762 ... 18.117064\n",
"56 30763 ... 19.815842\n",
"\n",
"[14 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: ayj47mls \n",
"\n",
"wandb: Agent Starting Run: ovsyk6z6 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 4\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: ovsyk6z6\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/ovsyk6z6
\n",
" "
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""
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 4\n",
" forecast_length: 2\n",
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" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 4\n",
"forward_params:\n",
" desc: null\n",
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"inference_params:\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 4\n",
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" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
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" seq_len: 4\n",
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" desc: null\n",
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" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 2\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
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" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"21.05331265926361\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 0\n",
"1.1080690873296637\n",
"The running loss is:\n",
"26.215594351291656\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 1\n",
"1.3797681237521924\n",
"The running loss is:\n",
"14.164807230234146\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 2\n",
"0.7455161700123235\n",
"The running loss is:\n",
"12.458269132301211\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 3\n",
"0.6556983753842743\n",
"The running loss is:\n",
"10.816738000139594\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 4\n",
"0.5693020000073471\n",
"The running loss is:\n",
"10.055854829028249\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 5\n",
"0.5292555173172763\n",
"The running loss is:\n",
"9.955036200582981\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 6\n",
"0.5239492737148937\n",
"The running loss is:\n",
"10.308482509106398\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 7\n",
"0.5425517110055998\n",
"The running loss is:\n",
"11.734940055757761\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 8\n",
"0.6176284239872506\n",
"The running loss is:\n",
"11.233778834342957\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 9\n",
"0.5912515175969977\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 4, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
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"47 30754 ... 8.582728\n",
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"49 30756 ... 8.558024\n",
"50 30757 ... 7.619164\n",
"51 30758 ... 7.354745\n",
"52 30759 ... 7.545932\n",
"53 30760 ... 8.023136\n",
"54 30761 ... 7.720142\n",
"55 30762 ... 7.814631\n",
"56 30763 ... 7.839913\n",
"\n",
"[14 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: ovsyk6z6 \n",
"\n",
"wandb: Agent Starting Run: 47aj1nt6 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 4\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: 47aj1nt6\n"
],
"name": "stdout"
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{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/47aj1nt6
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
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" framework: torch\n",
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" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 4\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
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"forward_params:\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 4\n",
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" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
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" value: MultiAttnHeadSimple\n",
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" seq_len: 4\n",
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" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"18.88846641778946\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 0\n",
"0.9941298114626032\n",
"The running loss is:\n",
"32.47899427264929\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 1\n",
"1.7094207511920678\n",
"The running loss is:\n",
"15.767253905534744\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 2\n",
"0.8298554687123549\n",
"The running loss is:\n",
"14.174503304064274\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 3\n",
"0.7460264896875933\n",
"The running loss is:\n",
"12.41873462498188\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 4\n",
"0.6536176118411516\n",
"The running loss is:\n",
"11.58222109079361\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 5\n",
"0.6095905837259794\n",
"The running loss is:\n",
"11.454800620675087\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 6\n",
"0.6028842431934256\n",
"The running loss is:\n",
"10.778091475367546\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 7\n",
"0.5672679723877656\n",
"The running loss is:\n",
"11.654729049652815\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 8\n",
"0.6134067920869902\n",
"The running loss is:\n",
"11.17945396900177\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 9\n",
"0.5883923141579879\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 4, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 8.925244\n",
"48 30755 ... 9.496317\n",
"49 30756 ... 9.974865\n",
"50 30757 ... 9.552412\n",
"51 30758 ... 9.775986\n",
"52 30759 ... 10.380938\n",
"53 30760 ... 11.176371\n",
"54 30761 ... 11.189506\n",
"55 30762 ... 11.451692\n",
"56 30763 ... 11.802545\n",
"\n",
"[14 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 47aj1nt6 \n",
"\n",
"wandb: Agent Starting Run: z76wnyg2 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 4\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: z76wnyg2\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/z76wnyg2
\n",
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""
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 4\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 4\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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" desc: null\n",
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" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"14.582077455706894\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 0\n",
"0.7291038727853447\n",
"The running loss is:\n",
"36.46464059967548\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 1\n",
"1.8232320299837739\n",
"The running loss is:\n",
"26.12745802849531\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 2\n",
"1.3063729014247656\n",
"The running loss is:\n",
"15.507666435092688\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 3\n",
"0.7753833217546344\n",
"The running loss is:\n",
"13.647030219435692\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 4\n",
"0.6823515109717846\n",
"The running loss is:\n",
"12.357491072267294\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 5\n",
"0.6178745536133647\n",
"The running loss is:\n",
"12.394297644495964\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 6\n",
"0.6197148822247982\n",
"The running loss is:\n",
"12.705570708960295\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 7\n",
"0.6352785354480147\n",
"The running loss is:\n",
"11.57705445960164\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 8\n",
"0.5788527229800821\n",
"The running loss is:\n",
"11.144980823621154\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 9\n",
"0.5572490411810577\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 4, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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{
"output_type": "stream",
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
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"47 30754 ... 10.404851\n",
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"49 30756 ... 12.778332\n",
"50 30757 ... 13.997534\n",
"51 30758 ... 15.216475\n",
"52 30759 ... 16.760254\n",
"53 30760 ... 17.938425\n",
"54 30761 ... 19.327490\n",
"55 30762 ... 20.218571\n",
"56 30763 ... 20.834126\n",
"\n",
"[14 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: z76wnyg2 \n",
"\n",
"wandb: Agent Starting Run: e8mr8uwe with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 4\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: e8mr8uwe\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/e8mr8uwe
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
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" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
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" desc: null\n",
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" class: default\n",
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" relevant_cols:\n",
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" - month\n",
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" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
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" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
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" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"14.169267039746046\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 0\n",
"0.7457508968287393\n",
"The running loss is:\n",
"37.72724857926369\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 1\n",
"1.9856446620665098\n",
"The running loss is:\n",
"24.199124343693256\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 2\n",
"1.2736381233522767\n",
"The running loss is:\n",
"16.194256775081158\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 3\n",
"0.8523293039516399\n",
"The running loss is:\n",
"13.103187538683414\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 4\n",
"0.6896414494043902\n",
"The running loss is:\n",
"11.879832331091166\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 5\n",
"0.6252543332153245\n",
"The running loss is:\n",
"10.950798781588674\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 6\n",
"0.5763578306099302\n",
"The running loss is:\n",
"13.645143084228039\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 7\n",
"0.7181654254856863\n",
"The running loss is:\n",
"10.349268220365047\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 8\n",
"0.5446983273876341\n",
"The running loss is:\n",
"10.853834997862577\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 9\n",
"0.5712544735717145\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 4, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 9.738805\n",
"48 30755 ... 9.343151\n",
"49 30756 ... 9.593056\n",
"50 30757 ... 7.918449\n",
"51 30758 ... 7.861307\n",
"52 30759 ... 8.376973\n",
"53 30760 ... 9.427421\n",
"54 30761 ... 9.342373\n",
"55 30762 ... 9.391384\n",
"56 30763 ... 9.584616\n",
"\n",
"[14 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: e8mr8uwe \n",
"\n",
"wandb: Agent Starting Run: s3zxbtg0 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 4\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: s3zxbtg0\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/s3zxbtg0
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""
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{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
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" optimizer: Adam\n",
"wandb:\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"13.212389975786209\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 0\n",
"0.695388946094011\n",
"The running loss is:\n",
"38.891341254115105\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 1\n",
"2.0469126975850056\n",
"The running loss is:\n",
"29.096228800714016\n",
"The number of items in train is: \n",
"19\n",
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"1.5313804631954746\n",
"The running loss is:\n",
"16.55887496471405\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 3\n",
"0.8715197349849501\n",
"The running loss is:\n",
"14.256739430129528\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 4\n",
"0.7503547068489226\n",
"The running loss is:\n",
"12.388054355978966\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 5\n",
"0.6520028608409982\n",
"The running loss is:\n",
"10.843463119119406\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 6\n",
"0.5707085852168108\n",
"The running loss is:\n",
"10.851479662582278\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 7\n",
"0.571130508556962\n",
"The running loss is:\n",
"10.446336604654789\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 8\n",
"0.5498071897186732\n",
"The running loss is:\n",
"14.638044934719801\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 9\n",
"0.7704234176168316\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 4, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"50 30757 ... 10.763280\n",
"51 30758 ... 11.245664\n",
"52 30759 ... 12.068069\n",
"53 30760 ... 13.055459\n",
"54 30761 ... 12.345917\n",
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"\n",
"[14 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
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{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: s3zxbtg0 \n",
"\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"\u001b[34m\u001b[1mwandb\u001b[0m: Network error resolved after 0:00:14.038303, resuming normal operation.\n"
],
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{
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"text": [
"wandb: Agent Starting Run: maiell3o with config:\n",
"\tbatch_size: 2\n",
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"\tlr: 0.004\n",
"\toptimizer: Adam\n",
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
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" desc: null\n",
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" scaler: StandardScaler\n",
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" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
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" unsqueeze_dim: 1\n",
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" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
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"wandb:\n",
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"\n",
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"19\n",
"The loss for epoch 0\n",
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"The number of items in train is: \n",
"19\n",
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"1.3865663352373399\n",
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"24.001122549176216\n",
"The number of items in train is: \n",
"19\n",
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"1.2632169762724323\n",
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"19.9936896674335\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 3\n",
"1.0522994561807106\n",
"The running loss is:\n",
"17.85635165683925\n",
"The number of items in train is: \n",
"19\n",
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"0.939807981938908\n",
"The running loss is:\n",
"19.134501039981842\n",
"The number of items in train is: \n",
"19\n",
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"1.0070790021043075\n",
"The running loss is:\n",
"16.33119323849678\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 6\n",
"0.8595364862366727\n",
"The running loss is:\n",
"17.35211842507124\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 7\n",
"0.9132693907932231\n",
"The running loss is:\n",
"16.150467596948147\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 8\n",
"0.850024610365692\n",
"The running loss is:\n",
"15.309038482606411\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 9\n",
"0.8057388675056005\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 4, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 8.779421\n",
"48 30755 ... 8.413671\n",
"49 30756 ... 8.781001\n",
"50 30757 ... 7.955806\n",
"51 30758 ... 6.871974\n",
"52 30759 ... 6.721382\n",
"53 30760 ... 6.816398\n",
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"56 30763 ... 6.823972\n",
"\n",
"[14 rows x 32 columns]\n"
],
"name": "stdout"
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: maiell3o \n",
"\n",
"wandb: Agent Starting Run: 1s257vao with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 4\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: 1s257vao\n"
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"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/1s257vao
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" "
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"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 4\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 4\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 4\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 4\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
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" desc: null\n",
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" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"15.950616918504238\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 0\n",
"0.8395061536054862\n",
"The running loss is:\n",
"25.045804142951965\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 1\n",
"1.3182002180501033\n",
"The running loss is:\n",
"28.8318188264966\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 2\n",
"1.517464148762979\n",
"The running loss is:\n",
"20.126703716814518\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 3\n",
"1.0593001956218167\n",
"The running loss is:\n",
"17.79351157695055\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 4\n",
"0.9365006093131868\n",
"The running loss is:\n",
"17.524609372019768\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 5\n",
"0.922347861685251\n",
"The running loss is:\n",
"18.517031900584698\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 6\n",
"0.9745806263465631\n",
"The running loss is:\n",
"16.52970390021801\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 7\n",
"0.8699844158009479\n",
"The running loss is:\n",
"15.491389200091362\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 8\n",
"0.8153362736890191\n",
"The running loss is:\n",
"16.75063694268465\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 9\n",
"0.8816124706676132\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 4, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 9.217892\n",
"48 30755 ... 9.550221\n",
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"50 30757 ... 10.430239\n",
"51 30758 ... 10.068516\n",
"52 30759 ... 10.002805\n",
"53 30760 ... 10.005158\n",
"54 30761 ... 8.552078\n",
"55 30762 ... 9.498129\n",
"56 30763 ... 10.014200\n",
"\n",
"[14 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 1s257vao \n",
"\n",
"wandb: Agent Starting Run: gdwm1mi5 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 4\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: gdwm1mi5\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/gdwm1mi5
\n",
" "
],
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""
]
},
"metadata": {
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 4\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 4\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 4\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
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" seq_len: 4\n",
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" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
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" desc: null\n",
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"sweep:\n",
" desc: null\n",
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"training_params:\n",
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" batch_size: 2\n",
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" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"61.71031776070595\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 0\n",
"3.0855158880352973\n",
"The running loss is:\n",
"22.180610413313843\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 1\n",
"1.109030520665692\n",
"The running loss is:\n",
"23.172951824963093\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 2\n",
"1.1586475912481546\n",
"The running loss is:\n",
"18.153760477900505\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 3\n",
"0.9076880238950252\n",
"The running loss is:\n",
"17.846179999411106\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 4\n",
"0.8923089999705553\n",
"The running loss is:\n",
"16.6478939242661\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 5\n",
"0.832394696213305\n",
"The running loss is:\n",
"22.557837568223476\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 6\n",
"1.1278918784111738\n",
"The running loss is:\n",
"21.72391752898693\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 7\n",
"1.0861958764493465\n",
"The running loss is:\n",
"18.882404036819935\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 8\n",
"0.9441202018409968\n",
"The running loss is:\n",
"16.341234251856804\n",
"The number of items in train is: \n",
"20\n",
"The loss for epoch 9\n",
"0.8170617125928402\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 4, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 9.028555\n",
"48 30755 ... 10.223789\n",
"49 30756 ... 10.591708\n",
"50 30757 ... 12.109409\n",
"51 30758 ... 10.868167\n",
"52 30759 ... 10.671272\n",
"53 30760 ... 10.249063\n",
"54 30761 ... 9.258160\n",
"55 30762 ... 10.242380\n",
"56 30763 ... 10.538944\n",
"\n",
"[14 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: gdwm1mi5 \n",
"\n",
"wandb: Agent Starting Run: w0lg5o37 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 4\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: w0lg5o37\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/w0lg5o37
\n",
" "
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""
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 4\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 4\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 4\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 2\n",
" number_time_series: 3\n",
" output_seq_len: 2\n",
" seq_len: 4\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 2\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"41.49641283042729\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 0\n",
"2.1840217279172256\n",
"The running loss is:\n",
"19.970189593732357\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 1\n",
"1.0510626101964398\n",
"The running loss is:\n",
"24.242495357990265\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 2\n",
"1.275920808315277\n",
"The running loss is:\n",
"22.579135298728943\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 3\n",
"1.1883755420383655\n",
"The running loss is:\n",
"20.04605047404766\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 4\n",
"1.0550552881077717\n",
"The running loss is:\n",
"19.928060449659824\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 5\n",
"1.0488452868242013\n",
"The running loss is:\n",
"20.826875373721123\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 6\n",
"1.0961513354590064\n",
"The running loss is:\n",
"17.959194883704185\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 7\n",
"0.9452207833528519\n",
"The running loss is:\n",
"19.45036144554615\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 8\n",
"1.0237032339761132\n",
"The running loss is:\n",
"19.660989113152027\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 9\n",
"1.034788900692212\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 4, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 11.188835\n",
"48 30755 ... 10.382625\n",
"49 30756 ... 10.807488\n",
"50 30757 ... 10.160336\n",
"51 30758 ... 10.386367\n",
"52 30759 ... 10.618712\n",
"53 30760 ... 10.833608\n",
"54 30761 ... 10.601640\n",
"55 30762 ... 10.604479\n",
"56 30763 ... 10.606827\n",
"\n",
"[14 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: w0lg5o37 \n",
"\n",
"wandb: Agent Starting Run: y5e4tm4j with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 4\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: y5e4tm4j\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/y5e4tm4j
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 4\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 4\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 4\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 4\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"52.42885746061802\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 0\n",
"2.7594135505588433\n",
"The running loss is:\n",
"24.32117458432913\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 1\n",
"1.2800618202278489\n",
"The running loss is:\n",
"30.122551828622818\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 2\n",
"1.585397464664359\n",
"The running loss is:\n",
"20.29300230368972\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 3\n",
"1.0680527528257746\n",
"The running loss is:\n",
"18.420647092163563\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 4\n",
"0.9695077416928191\n",
"The running loss is:\n",
"17.05812880396843\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 5\n",
"0.8977962528404436\n",
"The running loss is:\n",
"17.698757626116276\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 6\n",
"0.9315135592692777\n",
"The running loss is:\n",
"15.643727265298367\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 7\n",
"0.8233540665946508\n",
"The running loss is:\n",
"17.527575224637985\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 8\n",
"0.9225039591914729\n",
"The running loss is:\n",
"13.784894995391369\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 9\n",
"0.7255207892311247\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 4, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
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"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"\n",
"[14 rows x 32 columns]\n"
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"name": "stdout"
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"output_type": "stream",
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"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: y5e4tm4j \n",
"\n",
"wandb: Agent Starting Run: yw3yr804 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 5\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: yw3yr804\n"
],
"name": "stdout"
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{
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"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/yw3yr804
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
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" framework: torch\n",
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" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
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" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
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" - month\n",
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" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
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"forward_params:\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 5\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
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" value: MultiAttnHeadSimple\n",
"model_params:\n",
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" seq_len: 5\n",
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" desc: null\n",
" value: PyTorch\n",
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" desc: null\n",
" value: Adam\n",
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" desc: null\n",
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"training_params:\n",
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" batch_size: 2\n",
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" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"23.151611974462867\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 0\n",
"1.2185058933927824\n",
"The running loss is:\n",
"24.21296002715826\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 1\n",
"1.2743663172188557\n",
"The running loss is:\n",
"14.147806107997894\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 2\n",
"0.7446213741051523\n",
"The running loss is:\n",
"11.688982851803303\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 3\n",
"0.6152096237791213\n",
"The running loss is:\n",
"11.189231188967824\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 4\n",
"0.588906904682517\n",
"The running loss is:\n",
"10.066100733820349\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 5\n",
"0.5297947754642289\n",
"The running loss is:\n",
"9.523541389033198\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 6\n",
"0.5012390204754315\n",
"The running loss is:\n",
"10.919814303517342\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 7\n",
"0.5747270686061758\n",
"The running loss is:\n",
"9.636709606507793\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 8\n",
"0.5071952424477786\n",
"The running loss is:\n",
"10.427344053983688\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 9\n",
"0.5488075817886152\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 5, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 8.963048\n",
"48 30755 ... 7.921071\n",
"49 30756 ... 7.497608\n",
"50 30757 ... 7.718255\n",
"51 30758 ... 7.543673\n",
"52 30759 ... 7.132375\n",
"53 30760 ... 6.909460\n",
"54 30761 ... 6.758762\n",
"55 30762 ... 6.579365\n",
"56 30763 ... 6.642597\n",
"\n",
"[15 rows x 32 columns]\n"
],
"name": "stdout"
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: yw3yr804 \n",
"\n",
"wandb: Agent Starting Run: sfugzwzq with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 5\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: sfugzwzq\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/sfugzwzq
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" "
],
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""
]
},
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
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" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 5\n",
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" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 5\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 5\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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" desc: null\n",
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" - MSE\n",
"model_name:\n",
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" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"19.778223261237144\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 0\n",
"1.0409591190124814\n",
"The running loss is:\n",
"32.143462881445885\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 1\n",
"1.6917612042866255\n",
"The running loss is:\n",
"16.04269601404667\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 2\n",
"0.8443524217919299\n",
"The running loss is:\n",
"14.474790960550308\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 3\n",
"0.7618311031868583\n",
"The running loss is:\n",
"12.12663073092699\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 4\n",
"0.6382437226803679\n",
"The running loss is:\n",
"11.022467166185379\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 5\n",
"0.5801298508518621\n",
"The running loss is:\n",
"10.14216186851263\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 6\n",
"0.5337979930796122\n",
"The running loss is:\n",
"10.681325320154428\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 7\n",
"0.5621750168502331\n",
"The running loss is:\n",
"11.375485748052597\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 8\n",
"0.5987097762132946\n",
"The running loss is:\n",
"9.121527703478932\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 9\n",
"0.4800804054462596\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 5, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"42 30749 ... 0.000000\n",
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"49 30756 ... 9.865327\n",
"50 30757 ... 11.112760\n",
"51 30758 ... 11.969445\n",
"52 30759 ... 13.426899\n",
"53 30760 ... 15.257719\n",
"54 30761 ... 15.186352\n",
"55 30762 ... 14.411901\n",
"56 30763 ... 15.222851\n",
"\n",
"[15 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: sfugzwzq \n",
"\n",
"wandb: Agent Starting Run: zorqe447 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 5\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: zorqe447\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/zorqe447
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 5\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 5\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 5\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 5\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"19.629800878465176\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 0\n",
"1.0905444932480652\n",
"The running loss is:\n",
"25.255747854709625\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 1\n",
"1.4030971030394237\n",
"The running loss is:\n",
"15.05001075565815\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 2\n",
"0.836111708647675\n",
"The running loss is:\n",
"13.016271352767944\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 3\n",
"0.7231261862648858\n",
"The running loss is:\n",
"12.27754981070757\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 4\n",
"0.682086100594865\n",
"The running loss is:\n",
"11.391240701079369\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 5\n",
"0.6328467056155205\n",
"The running loss is:\n",
"11.72953286767006\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 6\n",
"0.6516407148705589\n",
"The running loss is:\n",
"11.442858997732401\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 7\n",
"0.6357143887629112\n",
"The running loss is:\n",
"12.431051224470139\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 8\n",
"0.6906139569150077\n",
"The running loss is:\n",
"11.048863388597965\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 9\n",
"0.6138257438109981\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 5, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 10.032237\n",
"48 30755 ... 12.643246\n",
"49 30756 ... 6.603610\n",
"50 30757 ... 6.592432\n",
"51 30758 ... 4.413502\n",
"52 30759 ... 3.218659\n",
"53 30760 ... 2.618341\n",
"54 30761 ... 1.748638\n",
"55 30762 ... 1.638597\n",
"56 30763 ... 0.533958\n",
"\n",
"[15 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: zorqe447 \n",
"\n",
"wandb: Agent Starting Run: 3un1inbj with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 5\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: 3un1inbj\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/3un1inbj
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 5\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 5\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 5\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 1\n",
" number_time_series: 3\n",
" output_seq_len: 1\n",
" seq_len: 5\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 1\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"14.982001293450594\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 0\n",
"0.7885263838658207\n",
"The running loss is:\n",
"33.174809351563454\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 1\n",
"1.7460425974507081\n",
"The running loss is:\n",
"21.882377948611975\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 2\n",
"1.151704102558525\n",
"The running loss is:\n",
"15.876857874915004\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 3\n",
"0.8356240986797371\n",
"The running loss is:\n",
"13.362504370510578\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 4\n",
"0.703289703711083\n",
"The running loss is:\n",
"10.210133947432041\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 5\n",
"0.5373754709174758\n",
"The running loss is:\n",
"10.241281794384122\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 6\n",
"0.5390148312833748\n",
"The running loss is:\n",
"9.936604705639184\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 7\n",
"0.5229791950336412\n",
"The running loss is:\n",
"11.438727487111464\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 8\n",
"0.6020382887953403\n",
"The running loss is:\n",
"12.369946470251307\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 9\n",
"0.651049814223753\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 5, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
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"45 30752 ... 0.000000\n",
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"49 30756 ... 13.174330\n",
"50 30757 ... 13.520782\n",
"51 30758 ... 14.763544\n",
"52 30759 ... 15.160839\n",
"53 30760 ... 15.549007\n",
"54 30761 ... 15.544765\n",
"55 30762 ... 15.403012\n",
"56 30763 ... 15.567816\n",
"\n",
"[15 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 3un1inbj \n",
"\n",
"wandb: Agent Starting Run: or2ftbf5 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 5\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: or2ftbf5\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/or2ftbf5
\n",
" "
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 5\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 5\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 5\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 2\n",
" number_time_series: 3\n",
" output_seq_len: 2\n",
" seq_len: 5\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 2\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"13.938185892999172\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 0\n",
"0.7335887312104827\n",
"The running loss is:\n",
"34.40718472003937\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 1\n",
"1.8109044589494403\n",
"The running loss is:\n",
"27.414366364479065\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 2\n",
"1.4428613876041614\n",
"The running loss is:\n",
"16.21256609261036\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 3\n",
"0.8532929522426504\n",
"The running loss is:\n",
"13.721442848443985\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 4\n",
"0.7221812025496834\n",
"The running loss is:\n",
"11.4379528388381\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 5\n",
"0.6019975178335842\n",
"The running loss is:\n",
"9.260038580745459\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 6\n",
"0.48737045161818204\n",
"The running loss is:\n",
"12.055675242096186\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 7\n",
"0.6345092232682203\n",
"The running loss is:\n",
"10.1099742539227\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 8\n",
"0.5321039081011948\n",
"The running loss is:\n",
"11.101317666471004\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 9\n",
"0.5842798771826845\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 5, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 14.715038\n",
"48 30755 ... 13.290008\n",
"49 30756 ... 10.847966\n",
"50 30757 ... 12.697416\n",
"51 30758 ... 13.276269\n",
"52 30759 ... 14.771571\n",
"53 30760 ... 17.032900\n",
"54 30761 ... 16.310585\n",
"55 30762 ... 14.025554\n",
"56 30763 ... 16.796951\n",
"\n",
"[15 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: or2ftbf5 \n",
"\n",
"wandb: Agent Starting Run: qyjq7c0a with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 5\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: qyjq7c0a\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/qyjq7c0a
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
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}
},
{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 5\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 5\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 5\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 5\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"14.219057638198137\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 0\n",
"0.7899476465665631\n",
"The running loss is:\n",
"32.766083881258965\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 1\n",
"1.8203379934032757\n",
"The running loss is:\n",
"22.88953396677971\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 2\n",
"1.2716407759322061\n",
"The running loss is:\n",
"15.694544300436974\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 3\n",
"0.871919127802054\n",
"The running loss is:\n",
"13.966531410813332\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 4\n",
"0.7759184117118517\n",
"The running loss is:\n",
"11.931890279054642\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 5\n",
"0.6628827932808135\n",
"The running loss is:\n",
"11.502507656812668\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 6\n",
"0.6390282031562593\n",
"The running loss is:\n",
"10.604379296302795\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 7\n",
"0.589132183127933\n",
"The running loss is:\n",
"12.21282433718443\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 8\n",
"0.6784902409546905\n",
"The running loss is:\n",
"11.869370594620705\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 9\n",
"0.6594094774789281\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 5, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"50 30757 ... 6.104957\n",
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"52 30759 ... 3.290065\n",
"53 30760 ... 3.420416\n",
"54 30761 ... 1.564515\n",
"55 30762 ... -3.665913\n",
"56 30763 ... -0.584266\n",
"\n",
"[15 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: qyjq7c0a \n",
"\n",
"wandb: Agent Starting Run: e7l2v3n1 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 5\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: e7l2v3n1\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/e7l2v3n1
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 5\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 5\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 5\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 1\n",
" number_time_series: 3\n",
" output_seq_len: 1\n",
" seq_len: 5\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 1\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"14.939907671883702\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 0\n",
"0.7863109300991422\n",
"The running loss is:\n",
"27.58423702418804\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 1\n",
"1.451801948641476\n",
"The running loss is:\n",
"21.350735876709223\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 2\n",
"1.1237229408794327\n",
"The running loss is:\n",
"22.028746308758855\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 3\n",
"1.1594077004609924\n",
"The running loss is:\n",
"20.440568597987294\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 4\n",
"1.0758193998940682\n",
"The running loss is:\n",
"18.65727076679468\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 5\n",
"0.9819616193049833\n",
"The running loss is:\n",
"19.96857689321041\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 6\n",
"1.0509777312216007\n",
"The running loss is:\n",
"18.768428467214108\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 7\n",
"0.9878120245902162\n",
"The running loss is:\n",
"18.98760063573718\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 8\n",
"0.9993474018809042\n",
"The running loss is:\n",
"18.08189932629466\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 9\n",
"0.9516789119102453\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 5, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 11.355700\n",
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"49 30756 ... 11.397798\n",
"50 30757 ... 11.411679\n",
"51 30758 ... 11.352333\n",
"52 30759 ... 11.283925\n",
"53 30760 ... 11.236071\n",
"54 30761 ... 11.371363\n",
"55 30762 ... 11.656288\n",
"56 30763 ... 11.443694\n",
"\n",
"[15 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: e7l2v3n1 \n",
"\n",
"wandb: Agent Starting Run: tzqyy8oc with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 5\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: tzqyy8oc\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/tzqyy8oc
\n",
" "
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""
]
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}
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 5\n",
" forecast_length: 2\n",
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" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 5\n",
"forward_params:\n",
" desc: null\n",
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"inference_params:\n",
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" file_path: Colorado_Douglas County.csv\n",
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" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
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" forecast_length: 2\n",
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" output_seq_len: 2\n",
" seq_len: 5\n",
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" desc: null\n",
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"out_seq_length:\n",
" desc: null\n",
" value: 2\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
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" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"16.767386704683304\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 0\n",
"0.882494037088595\n",
"The running loss is:\n",
"23.7237149477005\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 1\n",
"1.2486165761947632\n",
"The running loss is:\n",
"21.810965567827225\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 2\n",
"1.147945556201433\n",
"The running loss is:\n",
"21.628697000443935\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 3\n",
"1.1383524737075756\n",
"The running loss is:\n",
"18.608572021126747\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 4\n",
"0.9793985274277235\n",
"The running loss is:\n",
"17.807227961719036\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 5\n",
"0.937222524301002\n",
"The running loss is:\n",
"16.818491958081722\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 6\n",
"0.885183787267459\n",
"The running loss is:\n",
"17.390442237257957\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 7\n",
"0.9152864335398925\n",
"The running loss is:\n",
"16.504042580723763\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 8\n",
"0.8686338200380928\n",
"The running loss is:\n",
"14.063714668154716\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 9\n",
"0.7401955088502482\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 5, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"42 30749 ... 0.000000\n",
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"49 30756 ... 16.280861\n",
"50 30757 ... 16.302153\n",
"51 30758 ... 18.620329\n",
"52 30759 ... 20.607368\n",
"53 30760 ... 19.939861\n",
"54 30761 ... 21.928680\n",
"55 30762 ... 21.918089\n",
"56 30763 ... 22.155098\n",
"\n",
"[15 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: tzqyy8oc \n",
"\n",
"wandb: Agent Starting Run: y09gepr6 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 5\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: y09gepr6\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/y09gepr6
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 5\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 5\n",
"forward_params:\n",
" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 5\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
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"model_params:\n",
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" seq_len: 5\n",
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" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
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" desc: null\n",
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" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"15.607820570468903\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 0\n",
"0.8671011428038279\n",
"The running loss is:\n",
"21.899810507893562\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 1\n",
"1.2166561393274202\n",
"The running loss is:\n",
"23.761934000998735\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 2\n",
"1.3201074444999297\n",
"The running loss is:\n",
"16.91294802725315\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 3\n",
"0.9396082237362862\n",
"The running loss is:\n",
"18.267082534730434\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 4\n",
"1.0148379185961351\n",
"The running loss is:\n",
"17.08760144561529\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 5\n",
"0.9493111914230717\n",
"The running loss is:\n",
"15.896970629692078\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 6\n",
"0.8831650349828932\n",
"The running loss is:\n",
"17.839499786496162\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 7\n",
"0.9910833214720091\n",
"The running loss is:\n",
"16.226146705448627\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 8\n",
"0.901452594747146\n",
"The running loss is:\n",
"15.652418322861195\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 9\n",
"0.8695787957145108\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 5, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 11.320057\n",
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"49 30756 ... 9.804661\n",
"50 30757 ... 9.939509\n",
"51 30758 ... 10.391244\n",
"52 30759 ... 10.271468\n",
"53 30760 ... 10.242510\n",
"54 30761 ... 9.979496\n",
"55 30762 ... 9.834205\n",
"56 30763 ... 9.926790\n",
"\n",
"[15 rows x 32 columns]\n"
],
"name": "stdout"
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: y09gepr6 \n",
"\n",
"wandb: Agent Starting Run: cbzex9pt with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 5\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: cbzex9pt\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/cbzex9pt
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""
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 5\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 5\n",
"forward_params:\n",
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" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
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" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
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"The number of items in train is: \n",
"19\n",
"The loss for epoch 0\n",
"2.500788221625905\n",
"The running loss is:\n",
"22.905585899949074\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 1\n",
"1.2055571526288986\n",
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"24.01019530929625\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 2\n",
"1.2636944899629605\n",
"The running loss is:\n",
"23.0567737929523\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 3\n",
"1.213514410155384\n",
"The running loss is:\n",
"26.211633875966072\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 4\n",
"1.3795596776824248\n",
"The running loss is:\n",
"20.059789837221615\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 5\n",
"1.0557784124853482\n",
"The running loss is:\n",
"18.259545739740133\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 6\n",
"0.9610287231442175\n",
"The running loss is:\n",
"20.72789303958416\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 7\n",
"1.090941738925482\n",
"The running loss is:\n",
"23.105668414384127\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 8\n",
"1.216087811283375\n",
"The running loss is:\n",
"20.80936250090599\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 9\n",
"1.0952296053108417\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 5, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
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"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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},
{
"output_type": "stream",
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"torch.Size([10])\n",
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"Un-transforming data\n"
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"name": "stdout"
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{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"Current historical dataframe\n",
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"51 30758 ... 11.551901\n",
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"53 30760 ... 11.576552\n",
"54 30761 ... 11.900595\n",
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"56 30763 ... 11.018733\n",
"\n",
"[15 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: cbzex9pt \n",
"\n",
"wandb: Agent Starting Run: y92u1zia with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 5\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: y92u1zia\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/y92u1zia
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
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"_wandb:\n",
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" relevant_cols:\n",
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" scaler: StandardScaler\n",
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" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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" desc: null\n",
" value:\n",
" - MSE\n",
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" optimizer: Adam\n",
"wandb:\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"60.506285328418016\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 0\n",
"3.1845413330746326\n",
"The running loss is:\n",
"22.747136116027832\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 1\n",
"1.1972176903172542\n",
"The running loss is:\n",
"22.141358107328415\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 2\n",
"1.1653346372278113\n",
"The running loss is:\n",
"20.66910433769226\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 3\n",
"1.0878475967206453\n",
"The running loss is:\n",
"21.232126966118813\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 4\n",
"1.1174803666378323\n",
"The running loss is:\n",
"19.210107535123825\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 5\n",
"1.0110582913223065\n",
"The running loss is:\n",
"16.590289562940598\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 6\n",
"0.8731731348916104\n",
"The running loss is:\n",
"15.67080619931221\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 7\n",
"0.8247792736480111\n",
"The running loss is:\n",
"14.635391503572464\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 8\n",
"0.7702837633459192\n",
"The running loss is:\n",
"12.694482833147049\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 9\n",
"0.668130675428792\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 5, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
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"45 30752 ... 0.000000\n",
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"50 30757 ... 11.089784\n",
"51 30758 ... 10.986698\n",
"52 30759 ... 11.406321\n",
"53 30760 ... 12.214860\n",
"54 30761 ... 12.406092\n",
"55 30762 ... 12.407260\n",
"56 30763 ... 12.401293\n",
"\n",
"[15 rows x 32 columns]\n"
],
"name": "stdout"
},
{
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"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: y92u1zia \n",
"\n",
"wandb: Agent Starting Run: 7tyjl8ck with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 5\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: 7tyjl8ck\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/7tyjl8ck
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" "
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""
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{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
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" relevant_cols:\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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" desc: null\n",
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" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"51.1738221719861\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 0\n",
"2.8429901206658945\n",
"The running loss is:\n",
"20.108996018767357\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 1\n",
"1.1171664454870753\n",
"The running loss is:\n",
"20.94754420220852\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 2\n",
"1.163752455678251\n",
"The running loss is:\n",
"19.241921558976173\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 3\n",
"1.068995642165343\n",
"The running loss is:\n",
"19.614308521151543\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 4\n",
"1.0896838067306414\n",
"The running loss is:\n",
"18.551492542028427\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 5\n",
"1.0306384745571349\n",
"The running loss is:\n",
"17.22895458340645\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 6\n",
"0.9571641435225805\n",
"The running loss is:\n",
"16.789826542139053\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 7\n",
"0.9327681412299474\n",
"The running loss is:\n",
"15.875566244125366\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 8\n",
"0.8819759024514092\n",
"The running loss is:\n",
"16.926526993513107\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 9\n",
"0.9403626107507281\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 5, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
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"49 30756 ... 13.271286\n",
"50 30757 ... 13.021132\n",
"51 30758 ... 13.106910\n",
"52 30759 ... 13.234471\n",
"53 30760 ... 13.401170\n",
"54 30761 ... 13.149764\n",
"55 30762 ... 12.935968\n",
"56 30763 ... 13.315945\n",
"\n",
"[15 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
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"text": [
"wandb: Agent Finished Run: 7tyjl8ck \n",
"\n",
"wandb: Agent Starting Run: xtufua36 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 6\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
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],
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
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" python_version: 3.6.9\n",
"batch_size:\n",
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" interpolate: false\n",
" relevant_cols:\n",
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" - month\n",
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" scaler: StandardScaler\n",
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" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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"metrics:\n",
" desc: null\n",
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" - MSE\n",
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"\n",
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"0.9822338282277709\n",
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"The number of items in train is: \n",
"19\n",
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"1.7080874206792367\n",
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"The number of items in train is: \n",
"19\n",
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"0.8835812689932553\n",
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"13.13648857921362\n",
"The number of items in train is: \n",
"19\n",
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"0.6913941357480852\n",
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"11.167816616594791\n",
"The number of items in train is: \n",
"19\n",
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"0.5877798219260416\n",
"The running loss is:\n",
"9.475702971220016\n",
"The number of items in train is: \n",
"19\n",
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"0.4987212090115798\n",
"The running loss is:\n",
"9.611646829172969\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 6\n",
"0.5058761489038405\n",
"The running loss is:\n",
"8.849040357898048\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 7\n",
"0.4657389662051604\n",
"The running loss is:\n",
"10.830722641199827\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 8\n",
"0.5700380337473593\n",
"The running loss is:\n",
"8.893724239896983\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 9\n",
"0.46809074946826223\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 6, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"42 30749 ... 0.000000\n",
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"54 30761 ... 15.520673\n",
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"\n",
"[16 rows x 32 columns]\n"
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"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: xtufua36 \n",
"\n",
"wandb: Agent Starting Run: 6q31wbqt with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 6\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: 6q31wbqt\n"
],
"name": "stdout"
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{
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"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/6q31wbqt
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 6\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 6\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 6\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 2\n",
" number_time_series: 3\n",
" output_seq_len: 2\n",
" seq_len: 6\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 2\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"16.809781923890114\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 0\n",
"0.9338767735494508\n",
"The running loss is:\n",
"31.100095892790705\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 1\n",
"1.7277831051550392\n",
"The running loss is:\n",
"14.82688376866281\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 2\n",
"0.8237157649257116\n",
"The running loss is:\n",
"12.923846289515495\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 3\n",
"0.7179914605286386\n",
"The running loss is:\n",
"10.198259711265564\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 4\n",
"0.566569983959198\n",
"The running loss is:\n",
"9.777777466922998\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 5\n",
"0.5432098592735\n",
"The running loss is:\n",
"8.726226492086425\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 6\n",
"0.4847903606714681\n",
"The running loss is:\n",
"9.029325045645237\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 7\n",
"0.5016291692025132\n",
"The running loss is:\n",
"9.306042216718197\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 8\n",
"0.5170023453732332\n",
"The running loss is:\n",
"9.190385576337576\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 9\n",
"0.5105769764631987\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 6, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"41 30748 ... 0.000000\n",
"42 30749 ... 0.000000\n",
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"48 30755 ... 12.234770\n",
"49 30756 ... 12.906726\n",
"50 30757 ... 9.613279\n",
"51 30758 ... 10.035604\n",
"52 30759 ... 10.181870\n",
"53 30760 ... 11.437014\n",
"54 30761 ... 11.337413\n",
"55 30762 ... 11.397779\n",
"56 30763 ... 11.538319\n",
"\n",
"[16 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 6q31wbqt \n",
"\n",
"wandb: Agent Starting Run: piuk49km with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 6\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: piuk49km\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/piuk49km
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" "
],
"text/plain": [
""
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 6\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 6\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 6\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
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" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 6\n",
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" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
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" desc: null\n",
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"sweep:\n",
" desc: null\n",
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"training_params:\n",
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" batch_size: 2\n",
" criterion: MSE\n",
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" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"19.207939341664314\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 0\n",
"1.067107741203573\n",
"The running loss is:\n",
"26.95139818638563\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 1\n",
"1.4972998992436461\n",
"The running loss is:\n",
"15.8444182574749\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 2\n",
"0.8802454587486055\n",
"The running loss is:\n",
"13.982900321483612\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 3\n",
"0.7768277956379784\n",
"The running loss is:\n",
"12.15248690545559\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 4\n",
"0.6751381614141994\n",
"The running loss is:\n",
"11.28390198200941\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 5\n",
"0.6268834434449673\n",
"The running loss is:\n",
"11.802641343325377\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 6\n",
"0.6557022968514098\n",
"The running loss is:\n",
"10.794923435896635\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 7\n",
"0.5997179686609242\n",
"The running loss is:\n",
"11.76518764346838\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 8\n",
"0.6536215357482433\n",
"The running loss is:\n",
"11.923004761338234\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 9\n",
"0.6623891534076797\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 6, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"41 30748 ... 0.000000\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
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"55 30762 ... -2.441918\n",
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"\n",
"[16 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: piuk49km \n",
"\n",
"wandb: Agent Starting Run: zh6e9hk0 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 6\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: zh6e9hk0\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/zh6e9hk0
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" "
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""
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 6\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 6\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 6\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
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" forecast_length: 1\n",
" number_time_series: 3\n",
" output_seq_len: 1\n",
" seq_len: 6\n",
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" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 1\n",
"sweep:\n",
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"training_params:\n",
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" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"14.526742728427052\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 0\n",
"0.7645654067593185\n",
"The running loss is:\n",
"30.84717154005193\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 1\n",
"1.6235353442132596\n",
"The running loss is:\n",
"26.77706977725029\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 2\n",
"1.4093194619605416\n",
"The running loss is:\n",
"15.642113384790719\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 3\n",
"0.823269125515301\n",
"The running loss is:\n",
"11.526011761277914\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 4\n",
"0.6066321979619955\n",
"The running loss is:\n",
"10.011572066694498\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 5\n",
"0.5269248456154999\n",
"The running loss is:\n",
"10.000060603022575\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 6\n",
"0.5263189791064513\n",
"The running loss is:\n",
"8.50434441305697\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 7\n",
"0.44759707437141943\n",
"The running loss is:\n",
"9.07707198522985\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 8\n",
"0.47774063080157103\n",
"The running loss is:\n",
"7.321829241234809\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 9\n",
"0.3853594337492005\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 6, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"41 30748 ... 0.000000\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 5.666120\n",
"48 30755 ... 9.921270\n",
"49 30756 ... 16.465700\n",
"50 30757 ... 12.533557\n",
"51 30758 ... 12.186483\n",
"52 30759 ... 11.201939\n",
"53 30760 ... 10.682373\n",
"54 30761 ... 9.363009\n",
"55 30762 ... 11.541510\n",
"56 30763 ... 17.120123\n",
"\n",
"[16 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: zh6e9hk0 \n",
"\n",
"wandb: Agent Starting Run: 2p9wj7al with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 6\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: 2p9wj7al\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/2p9wj7al
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
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}
},
{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 6\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 6\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 6\n",
" forecast_length: 2\n",
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" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
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" seq_len: 6\n",
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" desc: null\n",
" value: PyTorch\n",
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" desc: null\n",
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"sweep:\n",
" desc: null\n",
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"training_params:\n",
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" batch_size: 2\n",
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" epochs: 10\n",
" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"12.093412643298507\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 0\n",
"0.6718562579610281\n",
"The running loss is:\n",
"31.850913926959038\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 1\n",
"1.769495218164391\n",
"The running loss is:\n",
"24.548495411872864\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 2\n",
"1.3638053006596036\n",
"The running loss is:\n",
"14.259857133030891\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 3\n",
"0.7922142851683829\n",
"The running loss is:\n",
"11.60143318399787\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 4\n",
"0.6445240657776594\n",
"The running loss is:\n",
"10.158630147576332\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 5\n",
"0.5643683415320184\n",
"The running loss is:\n",
"10.024041716009378\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 6\n",
"0.5568912064449655\n",
"The running loss is:\n",
"10.450636763125658\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 7\n",
"0.5805909312847588\n",
"The running loss is:\n",
"12.88908988237381\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 8\n",
"0.7160605490207672\n",
"The running loss is:\n",
"9.649638891220093\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 9\n",
"0.5360910495122274\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 6, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
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"51 30758 ... 5.484777\n",
"52 30759 ... 4.383102\n",
"53 30760 ... 4.634890\n",
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"\n",
"[16 rows x 32 columns]\n"
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"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 2p9wj7al \n",
"\n",
"wandb: Agent Starting Run: miih8z8l with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 6\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: miih8z8l\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/miih8z8l
\n",
" "
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""
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 6\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 6\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 6\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 6\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"13.902076788246632\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 0\n",
"0.772337599347035\n",
"The running loss is:\n",
"30.734783306717873\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 1\n",
"1.7074879614843264\n",
"The running loss is:\n",
"24.098938152194023\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 2\n",
"1.3388298973441124\n",
"The running loss is:\n",
"16.15599799156189\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 3\n",
"0.8975554439756606\n",
"The running loss is:\n",
"14.88480393588543\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 4\n",
"0.8269335519936349\n",
"The running loss is:\n",
"13.353974744677544\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 5\n",
"0.7418874858154191\n",
"The running loss is:\n",
"13.012045174837112\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 6\n",
"0.7228913986020618\n",
"The running loss is:\n",
"11.28533148765564\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 7\n",
"0.6269628604253134\n",
"The running loss is:\n",
"11.091172754764557\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 8\n",
"0.6161762641535865\n",
"The running loss is:\n",
"14.631795093417168\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 9\n",
"0.8128775051898427\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 6, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"41 30748 ... 0.000000\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
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"48 30755 ... 9.647461\n",
"49 30756 ... 11.834938\n",
"50 30757 ... 8.905302\n",
"51 30758 ... 8.214365\n",
"52 30759 ... 8.132830\n",
"53 30760 ... 8.303577\n",
"54 30761 ... 7.712473\n",
"55 30762 ... 8.126958\n",
"56 30763 ... 9.033283\n",
"\n",
"[16 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: miih8z8l \n",
"\n",
"wandb: Agent Starting Run: 3x0ouo97 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 6\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: 3x0ouo97\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/3x0ouo97
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
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}
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{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 6\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 6\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
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" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
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" seq_len: 6\n",
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" desc: null\n",
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"sweep:\n",
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" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"20.53110232204199\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 0\n",
"1.080584332739052\n",
"The running loss is:\n",
"22.649866599589586\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 1\n",
"1.1920982420836623\n",
"The running loss is:\n",
"20.07614903151989\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 2\n",
"1.0566394227115732\n",
"The running loss is:\n",
"21.142045558430254\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 3\n",
"1.1127392399173819\n",
"The running loss is:\n",
"14.569156531244516\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 4\n",
"0.766797712170764\n",
"The running loss is:\n",
"13.339449528604746\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 5\n",
"0.7020762909791971\n",
"The running loss is:\n",
"11.777572210878134\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 6\n",
"0.619872221625165\n",
"The running loss is:\n",
"16.930491030216217\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 7\n",
"0.8910784752745378\n",
"The running loss is:\n",
"13.112162977457047\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 8\n",
"0.6901138409187919\n",
"The running loss is:\n",
"11.765430979430676\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 9\n",
"0.6192332094437197\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 6, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"Current historical dataframe\n",
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"50 30757 ... 11.087149\n",
"51 30758 ... 10.845184\n",
"52 30759 ... 10.669495\n",
"53 30760 ... 11.297999\n",
"54 30761 ... 10.704900\n",
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"56 30763 ... 6.396082\n",
"\n",
"[16 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 3x0ouo97 \n",
"\n",
"wandb: Agent Starting Run: 8zvt4j88 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 6\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: 8zvt4j88\n"
],
"name": "stdout"
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{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/8zvt4j88
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 6\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 6\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 6\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 2\n",
" number_time_series: 3\n",
" output_seq_len: 2\n",
" seq_len: 6\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 2\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"16.847276613116264\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 0\n",
"0.9359598118397925\n",
"The running loss is:\n",
"22.086317025125027\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 1\n",
"1.2270176125069459\n",
"The running loss is:\n",
"21.75656918808818\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 2\n",
"1.208698288227121\n",
"The running loss is:\n",
"20.252290658652782\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 3\n",
"1.1251272588140435\n",
"The running loss is:\n",
"17.040222689509392\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 4\n",
"0.9466790383060774\n",
"The running loss is:\n",
"16.73467853665352\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 5\n",
"0.9297043631474177\n",
"The running loss is:\n",
"15.817666858434677\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 6\n",
"0.8787592699130377\n",
"The running loss is:\n",
"17.491646096110344\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 7\n",
"0.9717581164505746\n",
"The running loss is:\n",
"14.300822883844376\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 8\n",
"0.7944901602135764\n",
"The running loss is:\n",
"14.148024834692478\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 9\n",
"0.7860013797051377\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 6, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"41 30748 ... 0.000000\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 8.154796\n",
"48 30755 ... 9.414880\n",
"49 30756 ... 9.848639\n",
"50 30757 ... 7.001806\n",
"51 30758 ... 7.194446\n",
"52 30759 ... 6.755281\n",
"53 30760 ... 7.121027\n",
"54 30761 ... 6.964331\n",
"55 30762 ... 6.581292\n",
"56 30763 ... 5.964928\n",
"\n",
"[16 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 8zvt4j88 \n",
"\n",
"wandb: Agent Starting Run: codhaw7z with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 6\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: codhaw7z\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/codhaw7z
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
"tags": []
}
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{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 6\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 6\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 6\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 6\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"16.63626703619957\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 0\n",
"0.9242370575666428\n",
"The running loss is:\n",
"21.218304097652435\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 1\n",
"1.1787946720918019\n",
"The running loss is:\n",
"20.293749123811722\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 2\n",
"1.127430506878429\n",
"The running loss is:\n",
"19.309033408761024\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 3\n",
"1.0727240782645013\n",
"The running loss is:\n",
"17.63574704527855\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 4\n",
"0.9797637247376971\n",
"The running loss is:\n",
"16.501740634441376\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 5\n",
"0.9167633685800765\n",
"The running loss is:\n",
"16.07330948114395\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 6\n",
"0.8929616378413306\n",
"The running loss is:\n",
"14.988985002040863\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 7\n",
"0.8327213890022702\n",
"The running loss is:\n",
"15.27691513299942\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 8\n",
"0.8487175073888567\n",
"The running loss is:\n",
"15.855083525180817\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 9\n",
"0.8808379736211565\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 6, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
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{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"41 30748 ... 0.000000\n",
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"49 30756 ... 11.519807\n",
"50 30757 ... 11.319865\n",
"51 30758 ... 11.301481\n",
"52 30759 ... 11.427913\n",
"53 30760 ... 11.322249\n",
"54 30761 ... 11.377673\n",
"55 30762 ... 11.367601\n",
"56 30763 ... 11.353683\n",
"\n",
"[16 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: codhaw7z \n",
"\n",
"wandb: Agent Starting Run: 3tphqgn9 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 6\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: 3tphqgn9\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/3tphqgn9
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 6\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 6\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 6\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 1\n",
" number_time_series: 3\n",
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" seq_len: 6\n",
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" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
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" desc: null\n",
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"training_params:\n",
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" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"89.16724638454616\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 0\n",
"4.693012967607693\n",
"The running loss is:\n",
"26.253339409828186\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 1\n",
"1.381754705780431\n",
"The running loss is:\n",
"22.28419649042189\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 2\n",
"1.17285244686431\n",
"The running loss is:\n",
"20.892348155379295\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 3\n",
"1.0995972713357525\n",
"The running loss is:\n",
"16.460732923820615\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 4\n",
"0.8663543644116113\n",
"The running loss is:\n",
"18.3472553268075\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 5\n",
"0.9656450172003946\n",
"The running loss is:\n",
"15.07598640746437\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 6\n",
"0.7934729688139143\n",
"The running loss is:\n",
"17.23325503244996\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 7\n",
"0.9070134227605242\n",
"The running loss is:\n",
"16.722626268863678\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 8\n",
"0.8801382246770357\n",
"The running loss is:\n",
"13.728390574455261\n",
"The number of items in train is: \n",
"19\n",
"The loss for epoch 9\n",
"0.7225468723397506\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 6, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"41 30748 ... 0.000000\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 11.590704\n",
"48 30755 ... 13.399076\n",
"49 30756 ... 13.402116\n",
"50 30757 ... 12.507936\n",
"51 30758 ... 12.685381\n",
"52 30759 ... 12.882812\n",
"53 30760 ... 12.423203\n",
"54 30761 ... 12.690681\n",
"55 30762 ... 12.690515\n",
"56 30763 ... 12.690374\n",
"\n",
"[16 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 3tphqgn9 \n",
"\n",
"wandb: Agent Starting Run: xuut9khr with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 6\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: xuut9khr\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/xuut9khr
\n",
" "
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""
]
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 6\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 6\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 6\n",
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" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
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" value: MultiAttnHeadSimple\n",
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" seq_len: 6\n",
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" value: PyTorch\n",
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" desc: null\n",
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"sweep:\n",
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" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"68.00627230107784\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 0\n",
"3.778126238948769\n",
"The running loss is:\n",
"19.79006164520979\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 1\n",
"1.0994478691783216\n",
"The running loss is:\n",
"17.850837409496307\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 2\n",
"0.9917131894164615\n",
"The running loss is:\n",
"24.54628086835146\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 3\n",
"1.36368227046397\n",
"The running loss is:\n",
"21.807621747255325\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 4\n",
"1.2115345415141847\n",
"The running loss is:\n",
"16.156769186258316\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 5\n",
"0.897598288125462\n",
"The running loss is:\n",
"15.531101047992706\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 6\n",
"0.8628389471107059\n",
"The running loss is:\n",
"15.293164731934667\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 7\n",
"0.8496202628852593\n",
"The running loss is:\n",
"14.162357330322266\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 8\n",
"0.7867976294623481\n",
"The running loss is:\n",
"13.308439128100872\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 9\n",
"0.7393577293389373\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 6, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"41 30748 ... 0.000000\n",
"42 30749 ... 0.000000\n",
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"48 30755 ... 11.351794\n",
"49 30756 ... 11.415997\n",
"50 30757 ... 10.585990\n",
"51 30758 ... 10.834534\n",
"52 30759 ... 10.455210\n",
"53 30760 ... 10.706393\n",
"54 30761 ... 10.487299\n",
"55 30762 ... 10.475573\n",
"56 30763 ... 10.091512\n",
"\n",
"[16 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: xuut9khr \n",
"\n",
"wandb: Agent Starting Run: opcbv3h4 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 6\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: opcbv3h4\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/opcbv3h4
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 6\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 6\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 6\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 6\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"55.38436781615019\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 0\n",
"3.076909323119455\n",
"The running loss is:\n",
"20.806777961552143\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 1\n",
"1.155932108975119\n",
"The running loss is:\n",
"18.307716690003872\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 2\n",
"1.0170953716668818\n",
"The running loss is:\n",
"18.69004149734974\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 3\n",
"1.0383356387416522\n",
"The running loss is:\n",
"19.871280409395695\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 4\n",
"1.1039600227442052\n",
"The running loss is:\n",
"17.01835998892784\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 5\n",
"0.9454644438293245\n",
"The running loss is:\n",
"16.486702501773834\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 6\n",
"0.915927916765213\n",
"The running loss is:\n",
"16.326455369591713\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 7\n",
"0.9070252983106507\n",
"The running loss is:\n",
"16.18179951608181\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 8\n",
"0.898988862004545\n",
"The running loss is:\n",
"15.756254091858864\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 9\n",
"0.8753474495477147\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 6, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"41 30748 ... 0.000000\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
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"47 30754 ... 11.574912\n",
"48 30755 ... 11.343673\n",
"49 30756 ... 10.713832\n",
"50 30757 ... 9.781120\n",
"51 30758 ... 9.948353\n",
"52 30759 ... 10.150012\n",
"53 30760 ... 9.753569\n",
"54 30761 ... 9.639825\n",
"55 30762 ... 9.856399\n",
"56 30763 ... 9.539119\n",
"\n",
"[16 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: opcbv3h4 \n",
"\n",
"wandb: Agent Starting Run: payrwmn7 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 7\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: payrwmn7\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/payrwmn7
\n",
" "
],
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""
]
},
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{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 7\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 7\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 7\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 1\n",
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" output_seq_len: 1\n",
" seq_len: 7\n",
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" value: PyTorch\n",
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" desc: null\n",
" value: Adam\n",
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" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"12.764818392693996\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 0\n",
"0.7091565773718886\n",
"The running loss is:\n",
"41.29002905637026\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 1\n",
"2.293890503131681\n",
"The running loss is:\n",
"17.83612199127674\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 2\n",
"0.9908956661820412\n",
"The running loss is:\n",
"16.420202357694507\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 3\n",
"0.9122334643163614\n",
"The running loss is:\n",
"12.88229051977396\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 4\n",
"0.7156828066541089\n",
"The running loss is:\n",
"11.19569367915392\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 5\n",
"0.6219829821752177\n",
"The running loss is:\n",
"10.120619802735746\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 6\n",
"0.5622566557075415\n",
"The running loss is:\n",
"9.58696399955079\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 7\n",
"0.5326091110861549\n",
"The running loss is:\n",
"8.832727583125234\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 8\n",
"0.4907070879514019\n",
"The running loss is:\n",
"8.69556760089472\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 9\n",
"0.48308708893859553\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 7, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"Current historical dataframe\n",
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"51 30758 ... 8.127285\n",
"52 30759 ... 8.260897\n",
"53 30760 ... 8.410134\n",
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"55 30762 ... 8.788653\n",
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"[17 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: payrwmn7 \n",
"\n",
"wandb: Agent Starting Run: yzkklixg with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 7\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: yzkklixg\n"
],
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{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/yzkklixg
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
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" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
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" value:\n",
" batch_size: 2\n",
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" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
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" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
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" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"14.693578988313675\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 0\n",
"0.8163099437952042\n",
"The running loss is:\n",
"35.63161541521549\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 1\n",
"1.979534189734194\n",
"The running loss is:\n",
"16.785623099654913\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 2\n",
"0.9325346166474952\n",
"The running loss is:\n",
"15.402808114886284\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 3\n",
"0.8557115619381269\n",
"The running loss is:\n",
"12.666369892656803\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 4\n",
"0.7036872162587113\n",
"The running loss is:\n",
"11.15108098834753\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 5\n",
"0.6195044993526406\n",
"The running loss is:\n",
"10.014611192047596\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 6\n",
"0.5563672884470887\n",
"The running loss is:\n",
"9.563246592879295\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 7\n",
"0.5312914773821831\n",
"The running loss is:\n",
"9.08486569300294\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 8\n",
"0.5047147607223855\n",
"The running loss is:\n",
"9.686499211937189\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 9\n",
"0.5381388451076217\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 7, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"40 30747 ... 0.000000\n",
"41 30748 ... 0.000000\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
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"53 30760 ... -1.188965\n",
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"\n",
"[17 rows x 32 columns]\n"
],
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{
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"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: yzkklixg \n",
"\n",
"wandb: Agent Starting Run: qgblb6h1 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 7\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: qgblb6h1\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/qgblb6h1
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" "
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""
]
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"metadata": {
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{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 7\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
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" relevant_cols:\n",
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" decoder_params:\n",
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" test_csv_path: Colorado_Douglas County.csv\n",
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" desc: null\n",
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" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
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"The number of items in train is: \n",
"17\n",
"The loss for epoch 0\n",
"0.9966213913524852\n",
"The running loss is:\n",
"25.57343617081642\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 1\n",
"1.5043197747539072\n",
"The running loss is:\n",
"13.54184927791357\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 2\n",
"0.7965793692890335\n",
"The running loss is:\n",
"12.523482795804739\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 3\n",
"0.7366754585767493\n",
"The running loss is:\n",
"10.940785882994533\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 4\n",
"0.643575640176149\n",
"The running loss is:\n",
"10.1965466234833\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 5\n",
"0.5997968602049\n",
"The running loss is:\n",
"9.783029923215508\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 6\n",
"0.5754723484244417\n",
"The running loss is:\n",
"9.331181142479181\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 7\n",
"0.5488930083811283\n",
"The running loss is:\n",
"8.621533285826445\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 8\n",
"0.5071490168133203\n",
"The running loss is:\n",
"9.149149924516678\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 9\n",
"0.5381852896774516\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 7, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
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"\n",
"[17 rows x 32 columns]\n"
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"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: qgblb6h1 \n",
"\n",
"wandb: Agent Starting Run: f9x7y7pi with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 7\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: f9x7y7pi\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/f9x7y7pi
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""
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
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" cli_version: 0.8.35\n",
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" python_version: 3.6.9\n",
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" class: default\n",
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" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
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" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
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" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"13.917671071365476\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 0\n",
"0.773203948409193\n",
"The running loss is:\n",
"32.96171744167805\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 1\n",
"1.8312065245376692\n",
"The running loss is:\n",
"28.98233161121607\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 2\n",
"1.6101295339564483\n",
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"15.695902362465858\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 3\n",
"0.8719945756925477\n",
"The running loss is:\n",
"13.521882995963097\n",
"The number of items in train is: \n",
"18\n",
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"0.7512157219979498\n",
"The running loss is:\n",
"10.357533072587103\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 5\n",
"0.5754185040326169\n",
"The running loss is:\n",
"10.813971852883697\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 6\n",
"0.6007762140490942\n",
"The running loss is:\n",
"9.83951736614108\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 7\n",
"0.5466398536745045\n",
"The running loss is:\n",
"7.9957271702587605\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 8\n",
"0.44420706501437557\n",
"The running loss is:\n",
"9.712909625843167\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 9\n",
"0.5396060903246204\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 7, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"40 30747 ... 0.000000\n",
"41 30748 ... 0.000000\n",
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"\n",
"[17 rows x 32 columns]\n"
],
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: f9x7y7pi \n",
"\n",
"wandb: Agent Starting Run: 582syw3h with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 7\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: 582syw3h\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/582syw3h
\n",
" "
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"text/plain": [
""
]
},
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 7\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 7\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 7\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 2\n",
" number_time_series: 3\n",
" output_seq_len: 2\n",
" seq_len: 7\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 2\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"12.806585595011711\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 0\n",
"0.7114769775006506\n",
"The running loss is:\n",
"30.424656696617603\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 1\n",
"1.6902587053676446\n",
"The running loss is:\n",
"26.228094905614853\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 2\n",
"1.4571163836452696\n",
"The running loss is:\n",
"15.915115505456924\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 3\n",
"0.8841730836364958\n",
"The running loss is:\n",
"13.321218777447939\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 4\n",
"0.7400677098582188\n",
"The running loss is:\n",
"12.429280959069729\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 5\n",
"0.6905156088372072\n",
"The running loss is:\n",
"10.585802391171455\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 6\n",
"0.5881001328428587\n",
"The running loss is:\n",
"10.051417954266071\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 7\n",
"0.5584121085703373\n",
"The running loss is:\n",
"10.791548609733582\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 8\n",
"0.5995304783185323\n",
"The running loss is:\n",
"10.503232896327972\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 9\n",
"0.5835129386848874\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 7, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"40 30747 ... 0.000000\n",
"41 30748 ... 0.000000\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
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"46 30753 ... 0.000000\n",
"47 30754 ... 7.806384\n",
"48 30755 ... 9.270082\n",
"49 30756 ... 9.476368\n",
"50 30757 ... 11.667879\n",
"51 30758 ... 7.077388\n",
"52 30759 ... 7.040015\n",
"53 30760 ... 6.562690\n",
"54 30761 ... 6.141752\n",
"55 30762 ... 7.215327\n",
"56 30763 ... 6.751134\n",
"\n",
"[17 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 582syw3h \n",
"\n",
"wandb: Agent Starting Run: rb2iuxuw with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 7\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: rb2iuxuw\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/rb2iuxuw
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 7\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 7\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 7\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 7\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
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"out_seq_length:\n",
" desc: null\n",
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"sweep:\n",
" desc: null\n",
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"training_params:\n",
" desc: null\n",
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" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"12.165790781378746\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 0\n",
"0.7156347518458086\n",
"The running loss is:\n",
"27.170376665890217\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 1\n",
"1.5982574509347187\n",
"The running loss is:\n",
"21.744665786623955\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 2\n",
"1.279097987448468\n",
"The running loss is:\n",
"13.72632198035717\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 3\n",
"0.8074307047268924\n",
"The running loss is:\n",
"12.807656642049551\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 4\n",
"0.7533915671793854\n",
"The running loss is:\n",
"11.399554572999477\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 5\n",
"0.6705620337058517\n",
"The running loss is:\n",
"10.820783462375402\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 6\n",
"0.6365166742573766\n",
"The running loss is:\n",
"10.212848238646984\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 7\n",
"0.6007557787439403\n",
"The running loss is:\n",
"9.258121870458126\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 8\n",
"0.5445954041445956\n",
"The running loss is:\n",
"10.42987996339798\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 9\n",
"0.6135223507881165\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 7, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"40 30747 ... 0.000000\n",
"41 30748 ... 0.000000\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
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"50 30757 ... 6.468437\n",
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"53 30760 ... 2.644137\n",
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"55 30762 ... 1.020092\n",
"56 30763 ... 0.611532\n",
"\n",
"[17 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: rb2iuxuw \n",
"\n",
"wandb: Agent Starting Run: q8pk37k7 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 7\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: q8pk37k7\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/q8pk37k7
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 7\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 7\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 7\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 1\n",
" number_time_series: 3\n",
" output_seq_len: 1\n",
" seq_len: 7\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
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" desc: null\n",
" value: 1\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"25.0777577906847\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 0\n",
"1.39320876614915\n",
"The running loss is:\n",
"29.13719865679741\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 1\n",
"1.618733258710967\n",
"The running loss is:\n",
"27.344745717942715\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 2\n",
"1.5191525398857064\n",
"The running loss is:\n",
"28.274847473949194\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 3\n",
"1.570824859663844\n",
"The running loss is:\n",
"13.97701994329691\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 4\n",
"0.7765011079609394\n",
"The running loss is:\n",
"12.554442692548037\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 5\n",
"0.697469038474891\n",
"The running loss is:\n",
"13.142991535365582\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 6\n",
"0.730166196409199\n",
"The running loss is:\n",
"14.788394697010517\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 7\n",
"0.821577483167251\n",
"The running loss is:\n",
"14.111675955122337\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 8\n",
"0.7839819975067965\n",
"The running loss is:\n",
"12.757243922678754\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 9\n",
"0.708735773482153\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 7, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"40 30747 ... 0.000000\n",
"41 30748 ... 0.000000\n",
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"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
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"47 30754 ... 8.673750\n",
"48 30755 ... 8.759176\n",
"49 30756 ... 11.605460\n",
"50 30757 ... 12.306805\n",
"51 30758 ... 9.116247\n",
"52 30759 ... 8.930177\n",
"53 30760 ... 8.762095\n",
"54 30761 ... 8.338878\n",
"55 30762 ... 8.324352\n",
"56 30763 ... 8.409344\n",
"\n",
"[17 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: q8pk37k7 \n",
"\n",
"wandb: Agent Starting Run: yuaoe3t1 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 7\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: yuaoe3t1\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/yuaoe3t1
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 7\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 7\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 7\n",
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" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
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" forecast_length: 2\n",
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" output_seq_len: 2\n",
" seq_len: 7\n",
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" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
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"sweep:\n",
" desc: null\n",
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"training_params:\n",
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" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"19.664488945156336\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 0\n",
"1.092471608064241\n",
"The running loss is:\n",
"24.840459644794464\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 1\n",
"1.3800255358219147\n",
"The running loss is:\n",
"24.18926414847374\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 2\n",
"1.3438480082485411\n",
"The running loss is:\n",
"22.759043589234352\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 3\n",
"1.2643913105130196\n",
"The running loss is:\n",
"18.388007149100304\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 4\n",
"1.0215559527277946\n",
"The running loss is:\n",
"17.054414674639702\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 5\n",
"0.9474674819244279\n",
"The running loss is:\n",
"16.19636530429125\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 6\n",
"0.8997980724606249\n",
"The running loss is:\n",
"16.092383541166782\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 7\n",
"0.894021307842599\n",
"The running loss is:\n",
"16.495493300259113\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 8\n",
"0.9164162944588397\n",
"The running loss is:\n",
"14.59353306889534\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 9\n",
"0.8107518371608522\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 7, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"40 30747 ... 0.000000\n",
"41 30748 ... 0.000000\n",
"42 30749 ... 0.000000\n",
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"\n",
"[17 rows x 32 columns]\n"
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{
"output_type": "stream",
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"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: yuaoe3t1 \n",
"\n",
"wandb: Agent Starting Run: msnqy4jq with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 7\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: msnqy4jq\n"
],
"name": "stdout"
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{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/msnqy4jq
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 7\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 7\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 7\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 7\n",
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" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"15.602887228131294\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 0\n",
"0.9178168957724291\n",
"The running loss is:\n",
"20.492954045534134\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 1\n",
"1.2054678850314196\n",
"The running loss is:\n",
"18.17607271671295\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 2\n",
"1.0691807480419384\n",
"The running loss is:\n",
"17.942578546702862\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 3\n",
"1.0554457968648743\n",
"The running loss is:\n",
"15.375115282833576\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 4\n",
"0.9044185460490339\n",
"The running loss is:\n",
"14.95146494358778\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 5\n",
"0.8794979378581047\n",
"The running loss is:\n",
"14.935466520488262\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 6\n",
"0.8785568541463684\n",
"The running loss is:\n",
"13.655654460191727\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 7\n",
"0.8032737917759839\n",
"The running loss is:\n",
"13.988929450511932\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 8\n",
"0.8228782029712901\n",
"The running loss is:\n",
"12.398067966103554\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 9\n",
"0.7292981156531502\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 7, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
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},
{
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"text": [
"Current historical dataframe\n",
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"52 30759 ... 5.976255\n",
"53 30760 ... 5.439822\n",
"54 30761 ... 4.073036\n",
"55 30762 ... 4.531176\n",
"56 30763 ... 2.037996\n",
"\n",
"[17 rows x 32 columns]\n"
],
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: msnqy4jq \n",
"\n",
"wandb: Agent Starting Run: 28zecqnv with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 7\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: 28zecqnv\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/28zecqnv
\n",
" "
],
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""
]
},
"metadata": {
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}
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 7\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 7\n",
"forward_params:\n",
" desc: null\n",
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" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
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"sweep:\n",
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"training_params:\n",
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" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"132.11954160500318\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 0\n",
"7.339974533611287\n",
"The running loss is:\n",
"33.18467270210385\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 1\n",
"1.8435929278946586\n",
"The running loss is:\n",
"15.044109242036939\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 2\n",
"0.83578384677983\n",
"The running loss is:\n",
"32.12868493422866\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 3\n",
"1.784926940790481\n",
"The running loss is:\n",
"16.458579962607473\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 4\n",
"0.9143655534781929\n",
"The running loss is:\n",
"16.18535217642784\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 5\n",
"0.8991862320237689\n",
"The running loss is:\n",
"13.845332082360983\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 6\n",
"0.7691851156867213\n",
"The running loss is:\n",
"18.111790597438812\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 7\n",
"1.0062105887466006\n",
"The running loss is:\n",
"15.37386241927743\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 8\n",
"0.854103467737635\n",
"The running loss is:\n",
"14.108973555266857\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 9\n",
"0.7838318641814921\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 7, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
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"torch.Size([10])\n",
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"Un-transforming data\n"
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},
{
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"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
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"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
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"\n",
"[17 rows x 32 columns]\n"
],
"name": "stdout"
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{
"output_type": "stream",
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"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
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{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 28zecqnv \n",
"\n",
"wandb: Agent Starting Run: wyy0ykxe with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 7\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
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"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/wyy0ykxe
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"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
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" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
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" desc: null\n",
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" class: default\n",
" forecast_history: 7\n",
" forecast_length: 2\n",
" interpolate: false\n",
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" - month\n",
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" scaler: StandardScaler\n",
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" test_path: Colorado_Douglas County.csv\n",
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" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
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" - MSE\n",
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" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"92.95915368199348\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 0\n",
"5.164397426777416\n",
"The running loss is:\n",
"22.1982841193676\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 1\n",
"1.2332380066315334\n",
"The running loss is:\n",
"14.565131276845932\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 2\n",
"0.809173959824774\n",
"The running loss is:\n",
"27.13835011422634\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 3\n",
"1.5076861174570189\n",
"The running loss is:\n",
"19.970424134284258\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 4\n",
"1.1094680074602365\n",
"The running loss is:\n",
"16.359486132860184\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 5\n",
"0.9088603407144547\n",
"The running loss is:\n",
"15.630101136863232\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 6\n",
"0.8683389520479573\n",
"The running loss is:\n",
"14.64559318125248\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 7\n",
"0.8136440656251378\n",
"The running loss is:\n",
"16.040196174755692\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 8\n",
"0.8911220097086496\n",
"The running loss is:\n",
"15.461667504161596\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 9\n",
"0.8589815280089775\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 7, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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{
"output_type": "stream",
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
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{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
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{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"40 30747 ... 0.000000\n",
"41 30748 ... 0.000000\n",
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"43 30750 ... 0.000000\n",
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"52 30759 ... 10.608530\n",
"53 30760 ... 11.141614\n",
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"\n",
"[17 rows x 32 columns]\n"
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"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: wyy0ykxe \n",
"\n",
"wandb: Agent Starting Run: 00dey2s4 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 7\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: 00dey2s4\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/00dey2s4
\n",
" "
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""
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
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" python_version: 3.6.9\n",
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" relevant_cols:\n",
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" scaler: StandardScaler\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 7\n",
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" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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" desc: null\n",
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" optimizer: Adam\n",
"wandb:\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"61.90179131925106\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 0\n",
"3.641281842308886\n",
"The running loss is:\n",
"19.271656930446625\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 1\n",
"1.1336268782615662\n",
"The running loss is:\n",
"19.321099177002907\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 2\n",
"1.1365352457060534\n",
"The running loss is:\n",
"15.400234825909138\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 3\n",
"0.9058961662299493\n",
"The running loss is:\n",
"14.907342068850994\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 4\n",
"0.8769024746382937\n",
"The running loss is:\n",
"14.489337973296642\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 5\n",
"0.8523139984292143\n",
"The running loss is:\n",
"14.622908413410187\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 6\n",
"0.8601710831417757\n",
"The running loss is:\n",
"13.41513104736805\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 7\n",
"0.7891253557275323\n",
"The running loss is:\n",
"13.095239669084549\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 8\n",
"0.7703082158285028\n",
"The running loss is:\n",
"12.160573348402977\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 9\n",
"0.7153278440237045\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 7, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"51 30758 ... 8.547292\n",
"52 30759 ... 8.556589\n",
"53 30760 ... 8.530978\n",
"54 30761 ... 6.731397\n",
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"\n",
"[17 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 00dey2s4 \n",
"\n",
"wandb: Agent Starting Run: l00hyprr with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 8\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: l00hyprr\n"
],
"name": "stdout"
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{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/l00hyprr
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 8\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 8\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
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" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 8\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 1\n",
" number_time_series: 3\n",
" output_seq_len: 1\n",
" seq_len: 8\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 1\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"20.450659646186978\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 0\n",
"1.1361477581214987\n",
"The running loss is:\n",
"25.368839150760323\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 1\n",
"1.409379952820018\n",
"The running loss is:\n",
"13.926943810191005\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 2\n",
"0.773719100566167\n",
"The running loss is:\n",
"12.035636499524117\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 3\n",
"0.6686464721957842\n",
"The running loss is:\n",
"9.788120612502098\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 4\n",
"0.5437844784723388\n",
"The running loss is:\n",
"10.819668479263783\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 5\n",
"0.6010926932924323\n",
"The running loss is:\n",
"9.73928571306169\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 6\n",
"0.5410714285034273\n",
"The running loss is:\n",
"9.011047106876504\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 7\n",
"0.5006137281598058\n",
"The running loss is:\n",
"8.731201235204935\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 8\n",
"0.48506673528916305\n",
"The running loss is:\n",
"7.952998843044043\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 9\n",
"0.44183326905800235\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 8, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"39 30746 ... 0.000000\n",
"40 30747 ... 0.000000\n",
"41 30748 ... 0.000000\n",
"42 30749 ... 0.000000\n",
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"48 30755 ... 11.868648\n",
"49 30756 ... 17.565083\n",
"50 30757 ... 15.627804\n",
"51 30758 ... 9.883644\n",
"52 30759 ... 10.390420\n",
"53 30760 ... 11.200606\n",
"54 30761 ... 10.064157\n",
"55 30762 ... 11.100951\n",
"56 30763 ... 13.825031\n",
"\n",
"[18 rows x 32 columns]\n"
],
"name": "stdout"
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: l00hyprr \n",
"\n",
"wandb: Agent Starting Run: 40olhm4s with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 8\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: 40olhm4s\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/40olhm4s
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 8\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 8\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 8\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 2\n",
" number_time_series: 3\n",
" output_seq_len: 2\n",
" seq_len: 8\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 2\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"19.027740366756916\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 0\n",
"1.119278845103348\n",
"The running loss is:\n",
"26.84563284367323\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 1\n",
"1.5791548731572487\n",
"The running loss is:\n",
"14.248602889478207\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 2\n",
"0.8381531111457768\n",
"The running loss is:\n",
"12.727784872055054\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 3\n",
"0.7486932277679443\n",
"The running loss is:\n",
"12.753539435565472\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 4\n",
"0.7502082020920866\n",
"The running loss is:\n",
"11.517959401011467\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 5\n",
"0.6775270235889098\n",
"The running loss is:\n",
"11.238709852099419\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 6\n",
"0.6611005795352599\n",
"The running loss is:\n",
"10.820317476987839\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 7\n",
"0.6364892633522258\n",
"The running loss is:\n",
"10.896733909845352\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 8\n",
"0.6409843476379619\n",
"The running loss is:\n",
"9.990343987941742\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 9\n",
"0.5876672934083378\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 8, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"Current historical dataframe\n",
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"51 30758 ... 11.942869\n",
"52 30759 ... 10.421821\n",
"53 30760 ... 11.093673\n",
"54 30761 ... 11.154191\n",
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"\n",
"[18 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 40olhm4s \n",
"\n",
"wandb: Agent Starting Run: qa1p7boy with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 8\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: qa1p7boy\n"
],
"name": "stdout"
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{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/qa1p7boy
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 8\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 8\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 8\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 8\n",
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" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
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" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
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" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"17.990485712885857\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 0\n",
"1.0582638654638739\n",
"The running loss is:\n",
"27.865905489772558\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 1\n",
"1.6391709111630917\n",
"The running loss is:\n",
"13.985774576663971\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 2\n",
"0.8226926221567041\n",
"The running loss is:\n",
"12.147280521690845\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 3\n",
"0.714545913040638\n",
"The running loss is:\n",
"10.898061953485012\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 4\n",
"0.6410624678520596\n",
"The running loss is:\n",
"10.279500223696232\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 5\n",
"0.6046764837468371\n",
"The running loss is:\n",
"10.136913530528545\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 6\n",
"0.5962890312075615\n",
"The running loss is:\n",
"9.784845240414143\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 7\n",
"0.5755791317890672\n",
"The running loss is:\n",
"9.845538966357708\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 8\n",
"0.5791493509622181\n",
"The running loss is:\n",
"9.486583903431892\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 9\n",
"0.5580343472606996\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 8, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"39 30746 ... 0.000000\n",
"40 30747 ... 0.000000\n",
"41 30748 ... 0.000000\n",
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"52 30759 ... 6.710083\n",
"53 30760 ... 6.572598\n",
"54 30761 ... 6.372887\n",
"55 30762 ... 5.868860\n",
"56 30763 ... 6.114229\n",
"\n",
"[18 rows x 32 columns]\n"
],
"name": "stdout"
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: qa1p7boy \n",
"\n",
"wandb: Agent Starting Run: z60hhdo0 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 8\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: z60hhdo0\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/z60hhdo0
\n",
" "
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""
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
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" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
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" desc: null\n",
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" class: default\n",
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" forecast_length: 1\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
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" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
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" seq_len: 8\n",
"model_type:\n",
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" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"14.5401990711689\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 0\n",
"0.8077888372871611\n",
"The running loss is:\n",
"27.375006180256605\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 1\n",
"1.5208336766809225\n",
"The running loss is:\n",
"19.92556830495596\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 2\n",
"1.1069760169419978\n",
"The running loss is:\n",
"12.793712127953768\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 3\n",
"0.7107617848863205\n",
"The running loss is:\n",
"10.154001401970163\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 4\n",
"0.5641111889983423\n",
"The running loss is:\n",
"11.277737976284698\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 5\n",
"0.6265409986824833\n",
"The running loss is:\n",
"10.516089941374958\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 6\n",
"0.5842272189652754\n",
"The running loss is:\n",
"10.196689029689878\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 7\n",
"0.5664827238716599\n",
"The running loss is:\n",
"9.814422994852066\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 8\n",
"0.5452457219362259\n",
"The running loss is:\n",
"9.361941157840192\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 9\n",
"0.5201078421022329\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 8, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"Current historical dataframe\n",
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"[18 rows x 32 columns]\n"
],
"name": "stdout"
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: z60hhdo0 \n",
"\n",
"wandb: Agent Starting Run: r13hrd64 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 8\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
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],
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{
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"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
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"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
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"batch_size:\n",
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" relevant_cols:\n",
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" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
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" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
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" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"13.9246169552207\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 0\n",
"0.8190951150129823\n",
"The running loss is:\n",
"27.833781890571117\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 1\n",
"1.637281287680654\n",
"The running loss is:\n",
"20.855405513197184\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 2\n",
"1.2267885595998342\n",
"The running loss is:\n",
"13.618450827896595\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 3\n",
"0.8010853428174468\n",
"The running loss is:\n",
"13.988207560032606\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 4\n",
"0.8228357388254475\n",
"The running loss is:\n",
"12.185236137360334\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 5\n",
"0.7167785963153138\n",
"The running loss is:\n",
"12.937843896448612\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 6\n",
"0.7610496409675654\n",
"The running loss is:\n",
"12.002348616719246\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 7\n",
"0.706020506865838\n",
"The running loss is:\n",
"11.300229970365763\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 8\n",
"0.6647194100215155\n",
"The running loss is:\n",
"10.760703813284636\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 9\n",
"0.6329825772520374\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 8, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"39 30746 ... 0.000000\n",
"40 30747 ... 0.000000\n",
"41 30748 ... 0.000000\n",
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"\n",
"[18 rows x 32 columns]\n"
],
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{
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"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: r13hrd64 \n",
"\n",
"wandb: Agent Starting Run: ylv24ywo with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 8\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: ylv24ywo\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/ylv24ywo
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
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" python_version: 3.6.9\n",
"batch_size:\n",
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" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 8\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
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" training_path: Colorado_Douglas County.csv\n",
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" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
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" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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" desc: null\n",
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" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"12.265747778117657\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 0\n",
"0.7215145751833916\n",
"The running loss is:\n",
"25.639500468969345\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 1\n",
"1.5082059099393732\n",
"The running loss is:\n",
"21.685997530817986\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 2\n",
"1.2756469135775286\n",
"The running loss is:\n",
"13.566235706210136\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 3\n",
"0.7980138650711845\n",
"The running loss is:\n",
"12.054102204740047\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 4\n",
"0.709064835572944\n",
"The running loss is:\n",
"11.060121264308691\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 5\n",
"0.6505953684887466\n",
"The running loss is:\n",
"11.129384398460388\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 6\n",
"0.6546696704976699\n",
"The running loss is:\n",
"10.726066958159208\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 7\n",
"0.6309451151858357\n",
"The running loss is:\n",
"10.483027771115303\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 8\n",
"0.6166486924185473\n",
"The running loss is:\n",
"9.922650948166847\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 9\n",
"0.5836853498921675\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 8, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
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"56 30763 ... 9.212432\n",
"\n",
"[18 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: ylv24ywo \n",
"\n",
"wandb: Agent Starting Run: 202c29sd with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 8\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: 202c29sd\n"
],
"name": "stdout"
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{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/202c29sd
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
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" framework: torch\n",
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" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
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" class: default\n",
" forecast_history: 8\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 8\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
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" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"17.38165923114866\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 0\n",
"0.9656477350638144\n",
"The running loss is:\n",
"22.52288119122386\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 1\n",
"1.2512711772902145\n",
"The running loss is:\n",
"20.58570908382535\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 2\n",
"1.1436505046569638\n",
"The running loss is:\n",
"17.03510294482112\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 3\n",
"0.9463946080456177\n",
"The running loss is:\n",
"16.227192664518952\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 4\n",
"0.9015107035843862\n",
"The running loss is:\n",
"15.710538178682327\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 5\n",
"0.8728076765934626\n",
"The running loss is:\n",
"16.636069810017943\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 6\n",
"0.9242261005565524\n",
"The running loss is:\n",
"16.63070970028639\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 7\n",
"0.9239283166825771\n",
"The running loss is:\n",
"14.5533220928628\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 8\n",
"0.8085178940479333\n",
"The running loss is:\n",
"12.518009976483881\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 9\n",
"0.6954449986935489\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 8, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"39 30746 ... 0.000000\n",
"40 30747 ... 0.000000\n",
"41 30748 ... 0.000000\n",
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"56 30763 ... 13.025203\n",
"\n",
"[18 rows x 32 columns]\n"
],
"name": "stdout"
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{
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"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 202c29sd \n",
"\n",
"wandb: Agent Starting Run: u9eo4dfi with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 8\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: u9eo4dfi\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/u9eo4dfi
\n",
" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 8\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 8\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 8\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 2\n",
" number_time_series: 3\n",
" output_seq_len: 2\n",
" seq_len: 8\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 2\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"16.665514931082726\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 0\n",
"0.9803244077107486\n",
"The running loss is:\n",
"21.98633325099945\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 1\n",
"1.2933137206470264\n",
"The running loss is:\n",
"20.401913326233625\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 2\n",
"1.200112548601978\n",
"The running loss is:\n",
"17.110268775373697\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 3\n",
"1.0064863985513939\n",
"The running loss is:\n",
"15.317520216107368\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 4\n",
"0.9010306009474922\n",
"The running loss is:\n",
"14.436367448419333\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 5\n",
"0.8491980852011372\n",
"The running loss is:\n",
"11.61998137831688\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 6\n",
"0.6835283163715812\n",
"The running loss is:\n",
"14.995876673609018\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 7\n",
"0.8821103925652364\n",
"The running loss is:\n",
"12.463443532586098\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 8\n",
"0.7331437372109469\n",
"The running loss is:\n",
"12.348684921860695\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 9\n",
"0.7263932306976879\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 8, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"39 30746 ... 0.000000\n",
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"46 30753 ... 0.000000\n",
"47 30754 ... 11.883090\n",
"48 30755 ... 11.924982\n",
"49 30756 ... 11.952619\n",
"50 30757 ... 11.935939\n",
"51 30758 ... 11.950844\n",
"52 30759 ... 7.756837\n",
"53 30760 ... 7.546932\n",
"54 30761 ... 7.714972\n",
"55 30762 ... 7.608711\n",
"56 30763 ... 7.573092\n",
"\n",
"[18 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: u9eo4dfi \n",
"\n",
"wandb: Agent Starting Run: gfy2ld4o with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 8\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: gfy2ld4o\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/gfy2ld4o
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
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}
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{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 8\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 8\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 8\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 8\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
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" value: Adam\n",
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" desc: null\n",
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"sweep:\n",
" desc: null\n",
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"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"17.57657253742218\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 0\n",
"1.0339160316130693\n",
"The running loss is:\n",
"21.085083961486816\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 1\n",
"1.240299056558048\n",
"The running loss is:\n",
"20.510505497455597\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 2\n",
"1.206500323379741\n",
"The running loss is:\n",
"18.18516470491886\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 3\n",
"1.06971557087758\n",
"The running loss is:\n",
"15.011801198124886\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 4\n",
"0.8830471293014639\n",
"The running loss is:\n",
"15.11803139001131\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 5\n",
"0.8892959641183124\n",
"The running loss is:\n",
"14.489876501262188\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 6\n",
"0.8523456765448346\n",
"The running loss is:\n",
"14.646412342786789\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 7\n",
"0.8615536672227523\n",
"The running loss is:\n",
"14.810041315853596\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 8\n",
"0.8711789009325644\n",
"The running loss is:\n",
"13.977952808141708\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 9\n",
"0.8222325181259829\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 8, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"39 30746 ... 0.000000\n",
"40 30747 ... 0.000000\n",
"41 30748 ... 0.000000\n",
"42 30749 ... 0.000000\n",
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"52 30759 ... 11.597588\n",
"53 30760 ... 11.598228\n",
"54 30761 ... 11.475595\n",
"55 30762 ... 11.413112\n",
"56 30763 ... 11.466397\n",
"\n",
"[18 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: gfy2ld4o \n",
"\n",
"wandb: Agent Starting Run: 6b6shvso with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 8\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: 6b6shvso\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
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"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/6b6shvso
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 8\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 8\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 8\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
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" value:\n",
" forecast_length: 1\n",
" number_time_series: 3\n",
" output_seq_len: 1\n",
" seq_len: 8\n",
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" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
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"sweep:\n",
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" value: true\n",
"training_params:\n",
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" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"78.06080336868763\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 0\n",
"4.336711298260424\n",
"The running loss is:\n",
"23.151071030646563\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 1\n",
"1.2861706128136978\n",
"The running loss is:\n",
"18.575490936636925\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 2\n",
"1.0319717187020514\n",
"The running loss is:\n",
"23.149101957678795\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 3\n",
"1.2860612198710442\n",
"The running loss is:\n",
"17.067200284451246\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 4\n",
"0.9481777935806248\n",
"The running loss is:\n",
"17.59191408008337\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 5\n",
"0.9773285600046316\n",
"The running loss is:\n",
"14.751718316227198\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 6\n",
"0.8195399064570665\n",
"The running loss is:\n",
"17.836396224796772\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 7\n",
"0.9909109013775984\n",
"The running loss is:\n",
"12.664922920055687\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 8\n",
"0.7036068288919827\n",
"The running loss is:\n",
"19.829482200788334\n",
"The number of items in train is: \n",
"18\n",
"The loss for epoch 9\n",
"1.1016379000437964\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 8, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
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},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"39 30746 ... 0.000000\n",
"40 30747 ... 0.000000\n",
"41 30748 ... 0.000000\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 10.880940\n",
"48 30755 ... 10.986598\n",
"49 30756 ... 10.924918\n",
"50 30757 ... 12.085524\n",
"51 30758 ... 11.770830\n",
"52 30759 ... 11.676743\n",
"53 30760 ... 11.817716\n",
"54 30761 ... 11.519333\n",
"55 30762 ... 11.551911\n",
"56 30763 ... 11.689872\n",
"\n",
"[18 rows x 32 columns]\n"
],
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 6b6shvso \n",
"\n",
"wandb: Agent Starting Run: v0ak9wcn with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 8\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: v0ak9wcn\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/v0ak9wcn
\n",
" "
],
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""
]
},
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}
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 8\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 8\n",
"forward_params:\n",
" desc: null\n",
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" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
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" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
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" seq_len: 8\n",
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" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"61.02029025554657\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 0\n",
"3.589428838561563\n",
"The running loss is:\n",
"19.11992210894823\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 1\n",
"1.1247013005263664\n",
"The running loss is:\n",
"20.35962064191699\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 2\n",
"1.1976247436421759\n",
"The running loss is:\n",
"17.901119500398636\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 3\n",
"1.0530070294352138\n",
"The running loss is:\n",
"19.68121352046728\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 4\n",
"1.1577184423804283\n",
"The running loss is:\n",
"15.582372598350048\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 5\n",
"0.9166101528441205\n",
"The running loss is:\n",
"15.728278800845146\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 6\n",
"0.9251928706379497\n",
"The running loss is:\n",
"15.83667142689228\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 7\n",
"0.9315689074642518\n",
"The running loss is:\n",
"15.11179693043232\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 8\n",
"0.8889292312019011\n",
"The running loss is:\n",
"14.601482972502708\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 9\n",
"0.8589107630883946\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 8, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"\n",
"[18 rows x 32 columns]\n"
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"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: v0ak9wcn \n",
"\n",
"wandb: Agent Starting Run: v0kjygd2 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 8\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: v0kjygd2\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/v0kjygd2
\n",
" "
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""
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 8\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 8\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 8\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 8\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"89.38227146863937\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 0\n",
"5.257780674625845\n",
"The running loss is:\n",
"24.08541053533554\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 1\n",
"1.4167888550197376\n",
"The running loss is:\n",
"14.835047475993633\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 2\n",
"0.8726498515290373\n",
"The running loss is:\n",
"17.46521347016096\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 3\n",
"1.0273654982447624\n",
"The running loss is:\n",
"14.109677575528622\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 4\n",
"0.8299810338546249\n",
"The running loss is:\n",
"14.43064521253109\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 5\n",
"0.8488614830900642\n",
"The running loss is:\n",
"13.140712775290012\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 6\n",
"0.7729831044288242\n",
"The running loss is:\n",
"12.153762593865395\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 7\n",
"0.7149272114038467\n",
"The running loss is:\n",
"12.104884780943394\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 8\n",
"0.7120520459378467\n",
"The running loss is:\n",
"11.55245054513216\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 9\n",
"0.6795559144195389\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 8, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"39 30746 ... 0.000000\n",
"40 30747 ... 0.000000\n",
"41 30748 ... 0.000000\n",
"42 30749 ... 0.000000\n",
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"47 30754 ... 8.822438\n",
"48 30755 ... 11.070477\n",
"49 30756 ... 13.553607\n",
"50 30757 ... 11.531958\n",
"51 30758 ... 12.513781\n",
"52 30759 ... 10.915012\n",
"53 30760 ... 11.354100\n",
"54 30761 ... 10.394032\n",
"55 30762 ... 10.346492\n",
"56 30763 ... 10.777813\n",
"\n",
"[18 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: v0kjygd2 \n",
"\n",
"wandb: Agent Starting Run: 47x2i8jx with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 9\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: 47x2i8jx\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/47x2i8jx
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
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}
},
{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 9\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 9\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 9\n",
" forecast_length: 1\n",
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" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
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" seq_len: 9\n",
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" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
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" desc: null\n",
" value: 1\n",
"sweep:\n",
" desc: null\n",
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"training_params:\n",
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" batch_size: 2\n",
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" epochs: 10\n",
" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"16.129226248711348\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 0\n",
"0.9487780146300793\n",
"The running loss is:\n",
"33.76753030810505\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 1\n",
"1.9863253122414737\n",
"The running loss is:\n",
"14.467158187180758\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 2\n",
"0.8510093051282799\n",
"The running loss is:\n",
"12.87113780900836\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 3\n",
"0.75712575347108\n",
"The running loss is:\n",
"9.909067310392857\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 4\n",
"0.5828863123760504\n",
"The running loss is:\n",
"9.568089163396508\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 5\n",
"0.5628287743174416\n",
"The running loss is:\n",
"9.66799031291157\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 6\n",
"0.56870531252421\n",
"The running loss is:\n",
"9.636533673852682\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 7\n",
"0.5668549219913342\n",
"The running loss is:\n",
"8.8233229694888\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 8\n",
"0.5190189982052235\n",
"The running loss is:\n",
"7.847568524535745\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 9\n",
"0.4616216779138674\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 9, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"50 30757 ... 13.019385\n",
"51 30758 ... 12.181848\n",
"52 30759 ... 9.387854\n",
"53 30760 ... 8.466204\n",
"54 30761 ... 8.803273\n",
"55 30762 ... 8.617043\n",
"56 30763 ... 8.495243\n",
"\n",
"[19 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 47x2i8jx \n",
"\n",
"wandb: Agent Starting Run: k64zd0i7 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 9\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: k64zd0i7\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/k64zd0i7
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" "
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""
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 9\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 9\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 9\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 2\n",
" number_time_series: 3\n",
" output_seq_len: 2\n",
" seq_len: 9\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 2\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"18.11563566327095\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 0\n",
"1.0656256272512323\n",
"The running loss is:\n",
"24.05933529138565\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 1\n",
"1.4152550171403324\n",
"The running loss is:\n",
"12.897609576582909\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 2\n",
"0.7586829162695828\n",
"The running loss is:\n",
"11.346729777753353\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 3\n",
"0.6674546928090208\n",
"The running loss is:\n",
"10.032144397497177\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 4\n",
"0.5901261410292458\n",
"The running loss is:\n",
"9.255228951573372\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 5\n",
"0.5444252324454925\n",
"The running loss is:\n",
"8.855674020946026\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 6\n",
"0.5209220012321192\n",
"The running loss is:\n",
"8.337467238307\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 7\n",
"0.4904392493121764\n",
"The running loss is:\n",
"7.936403177678585\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 8\n",
"0.4668472457457991\n",
"The running loss is:\n",
"7.299756273627281\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 9\n",
"0.4293974278604283\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 9, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"38 30745 ... 0.000000\n",
"39 30746 ... 0.000000\n",
"40 30747 ... 0.000000\n",
"41 30748 ... 0.000000\n",
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"46 30753 ... 0.000000\n",
"47 30754 ... 6.314528\n",
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"49 30756 ... 7.303198\n",
"50 30757 ... 10.772114\n",
"51 30758 ... 8.226935\n",
"52 30759 ... 2.058505\n",
"53 30760 ... -0.580315\n",
"54 30761 ... -1.148522\n",
"55 30762 ... -3.539087\n",
"56 30763 ... -3.183217\n",
"\n",
"[19 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: k64zd0i7 \n",
"\n",
"wandb: Agent Starting Run: 90hzhwlz with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 9\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: 90hzhwlz\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/90hzhwlz
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 9\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 9\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 9\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 9\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"12.229821100831032\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 0\n",
"0.7643638188019395\n",
"The running loss is:\n",
"31.796365045011044\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 1\n",
"1.9872728153131902\n",
"The running loss is:\n",
"15.763759694993496\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 2\n",
"0.9852349809370935\n",
"The running loss is:\n",
"13.028775602579117\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 3\n",
"0.8142984751611948\n",
"The running loss is:\n",
"13.04194351285696\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 4\n",
"0.81512146955356\n",
"The running loss is:\n",
"10.17906753718853\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 5\n",
"0.6361917210742831\n",
"The running loss is:\n",
"9.676793612539768\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 6\n",
"0.6047996007837355\n",
"The running loss is:\n",
"9.569400377571583\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 7\n",
"0.5980875235982239\n",
"The running loss is:\n",
"9.05061225220561\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 8\n",
"0.5656632657628506\n",
"The running loss is:\n",
"8.944659441709518\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 9\n",
"0.5590412151068449\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 9, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"38 30745 ... 0.000000\n",
"39 30746 ... 0.000000\n",
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"49 30756 ... 8.965311\n",
"50 30757 ... 9.146642\n",
"51 30758 ... 9.041492\n",
"52 30759 ... 7.654950\n",
"53 30760 ... 5.084298\n",
"54 30761 ... 4.954723\n",
"55 30762 ... 4.857830\n",
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"\n",
"[19 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 90hzhwlz \n",
"\n",
"wandb: Agent Starting Run: v8g59dsp with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 9\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: v8g59dsp\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/v8g59dsp
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" "
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 9\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 9\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 9\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 1\n",
" number_time_series: 3\n",
" output_seq_len: 1\n",
" seq_len: 9\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 1\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"13.235776502639055\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 0\n",
"0.7785750883905327\n",
"The running loss is:\n",
"26.4114770591259\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 1\n",
"1.5536162975956411\n",
"The running loss is:\n",
"19.23542471975088\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 2\n",
"1.1314955717500519\n",
"The running loss is:\n",
"13.774107448756695\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 3\n",
"0.8102416146327468\n",
"The running loss is:\n",
"10.821895120665431\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 4\n",
"0.6365820659214959\n",
"The running loss is:\n",
"10.974949937546626\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 5\n",
"0.6455852904439192\n",
"The running loss is:\n",
"10.996416509151459\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 6\n",
"0.6468480299500858\n",
"The running loss is:\n",
"10.585891755763441\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 7\n",
"0.6226995150449083\n",
"The running loss is:\n",
"10.654300592839718\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 8\n",
"0.6267235642846893\n",
"The running loss is:\n",
"9.282092098146677\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 9\n",
"0.5460054175380398\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 9, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"38 30745 ... 0.000000\n",
"39 30746 ... 0.000000\n",
"40 30747 ... 0.000000\n",
"41 30748 ... 0.000000\n",
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"47 30754 ... 12.044758\n",
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"49 30756 ... 12.449036\n",
"50 30757 ... 13.799903\n",
"51 30758 ... 14.154404\n",
"52 30759 ... 11.899445\n",
"53 30760 ... 11.876869\n",
"54 30761 ... 11.815728\n",
"55 30762 ... 12.099028\n",
"56 30763 ... 12.176918\n",
"\n",
"[19 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: v8g59dsp \n",
"\n",
"wandb: Agent Starting Run: mkxr9eu3 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 9\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: mkxr9eu3\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/mkxr9eu3
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 9\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 9\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 9\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 2\n",
" number_time_series: 3\n",
" output_seq_len: 2\n",
" seq_len: 9\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 2\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"13.2156822681427\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 0\n",
"0.7773930745966294\n",
"The running loss is:\n",
"24.976793557405472\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 1\n",
"1.469223150435616\n",
"The running loss is:\n",
"19.48406381905079\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 2\n",
"1.1461214011206347\n",
"The running loss is:\n",
"12.607521995902061\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 3\n",
"0.7416189409354154\n",
"The running loss is:\n",
"10.452070504426956\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 4\n",
"0.6148276767309975\n",
"The running loss is:\n",
"10.917114395648241\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 5\n",
"0.6421831997440142\n",
"The running loss is:\n",
"8.793405067175627\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 6\n",
"0.5172591215985662\n",
"The running loss is:\n",
"8.538302391767502\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 7\n",
"0.5022530818686766\n",
"The running loss is:\n",
"8.421132470248267\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 8\n",
"0.4953607335440157\n",
"The running loss is:\n",
"9.026005014777184\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 9\n",
"0.5309414714574814\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 9, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"51 30758 ... 9.797338\n",
"52 30759 ... 8.877247\n",
"53 30760 ... 4.768612\n",
"54 30761 ... 4.516591\n",
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"56 30763 ... 2.947486\n",
"\n",
"[19 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: mkxr9eu3 \n",
"\n",
"wandb: Agent Starting Run: 1dip79bl with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 9\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: 1dip79bl\n"
],
"name": "stdout"
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{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/1dip79bl
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 9\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 9\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 9\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 9\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"14.258202567696571\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 0\n",
"0.8911376604810357\n",
"The running loss is:\n",
"24.629937380552292\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 1\n",
"1.5393710862845182\n",
"The running loss is:\n",
"21.176617115736008\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 2\n",
"1.3235385697335005\n",
"The running loss is:\n",
"15.326480709016323\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 3\n",
"0.9579050443135202\n",
"The running loss is:\n",
"12.801851324737072\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 4\n",
"0.800115707796067\n",
"The running loss is:\n",
"10.181393705308437\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 5\n",
"0.6363371065817773\n",
"The running loss is:\n",
"9.973678585141897\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 6\n",
"0.6233549115713686\n",
"The running loss is:\n",
"9.959196142852306\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 7\n",
"0.6224497589282691\n",
"The running loss is:\n",
"9.231910694390535\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 8\n",
"0.5769944183994085\n",
"The running loss is:\n",
"9.512702483683825\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 9\n",
"0.594543905230239\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 9, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"38 30745 ... 0.000000\n",
"39 30746 ... 0.000000\n",
"40 30747 ... 0.000000\n",
"41 30748 ... 0.000000\n",
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"51 30758 ... 7.403520\n",
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"53 30760 ... 2.108467\n",
"54 30761 ... 2.234306\n",
"55 30762 ... 1.988864\n",
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"\n",
"[19 rows x 32 columns]\n"
],
"name": "stdout"
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 1dip79bl \n",
"\n",
"wandb: Agent Starting Run: frrjdi26 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 9\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: frrjdi26\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/frrjdi26
\n",
" "
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""
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 9\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 9\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 9\n",
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" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
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" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"21.684900924563408\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 0\n",
"1.2755824073272592\n",
"The running loss is:\n",
"21.957859233021736\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 1\n",
"1.2916387784130432\n",
"The running loss is:\n",
"18.442369546741247\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 2\n",
"1.0848452674553675\n",
"The running loss is:\n",
"18.312154326587915\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 3\n",
"1.0771855486228186\n",
"The running loss is:\n",
"12.220995549112558\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 4\n",
"0.7188820911242682\n",
"The running loss is:\n",
"12.270410992205143\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 5\n",
"0.7217888818944201\n",
"The running loss is:\n",
"13.395324366167188\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 6\n",
"0.787960256833364\n",
"The running loss is:\n",
"12.515632160007954\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 7\n",
"0.7362136564710561\n",
"The running loss is:\n",
"13.149393206462264\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 8\n",
"0.773493718027192\n",
"The running loss is:\n",
"10.945322513580322\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 9\n",
"0.6438425007988425\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 9, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"53 30760 ... 7.219286\n",
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"\n",
"[19 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: frrjdi26 \n",
"\n",
"wandb: Agent Starting Run: 5e6yghhl with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 9\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: 5e6yghhl\n"
],
"name": "stdout"
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{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/5e6yghhl
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
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"batch_size:\n",
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" interpolate: false\n",
" relevant_cols:\n",
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" - month\n",
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" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
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" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
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" desc: null\n",
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" - MSE\n",
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" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"16.075793281197548\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 0\n",
"0.9456348988939735\n",
"The running loss is:\n",
"21.148211747407913\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 1\n",
"1.2440124557298773\n",
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"18.14787855744362\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 2\n",
"1.0675222680849188\n",
"The running loss is:\n",
"17.102335512638092\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 3\n",
"1.006019736037535\n",
"The running loss is:\n",
"16.263279542326927\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 4\n",
"0.9566635024898192\n",
"The running loss is:\n",
"14.015104442834854\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 5\n",
"0.8244179084020502\n",
"The running loss is:\n",
"14.513734132051468\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 6\n",
"0.8537490665912628\n",
"The running loss is:\n",
"14.677594423294067\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 7\n",
"0.8633879072525922\n",
"The running loss is:\n",
"13.664641842246056\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 8\n",
"0.8038024613085915\n",
"The running loss is:\n",
"12.593484312295914\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 9\n",
"0.7407931948409361\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 9, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"38 30745 ... 0.000000\n",
"39 30746 ... 0.000000\n",
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"41 30748 ... 0.000000\n",
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"51 30758 ... 12.723232\n",
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"53 30760 ... 10.750948\n",
"54 30761 ... 10.552313\n",
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"\n",
"[19 rows x 32 columns]\n"
],
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{
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"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 5e6yghhl \n",
"\n",
"wandb: Agent Starting Run: 49t73wpr with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 9\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: 49t73wpr\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/49t73wpr
\n",
" "
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""
]
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{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
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" framework: torch\n",
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" relevant_cols:\n",
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" decoder_function: simple_decode\n",
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" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
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" desc: null\n",
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" desc: null\n",
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" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"27.19437624514103\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 0\n",
"1.6996485153213143\n",
"The running loss is:\n",
"23.46845108270645\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 1\n",
"1.4667781926691532\n",
"The running loss is:\n",
"23.564942955970764\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 2\n",
"1.4728089347481728\n",
"The running loss is:\n",
"21.112747326493263\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 3\n",
"1.319546707905829\n",
"The running loss is:\n",
"16.332939110696316\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 4\n",
"1.0208086944185197\n",
"The running loss is:\n",
"13.240181624889374\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 5\n",
"0.8275113515555859\n",
"The running loss is:\n",
"10.968062326312065\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 6\n",
"0.6855038953945041\n",
"The running loss is:\n",
"9.933336228132248\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 7\n",
"0.6208335142582655\n",
"The running loss is:\n",
"9.906222566962242\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 8\n",
"0.6191389104351401\n",
"The running loss is:\n",
"9.35060365498066\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 9\n",
"0.5844127284362912\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 9, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"53 30760 ... 4.291282\n",
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"[19 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 49t73wpr \n",
"\n",
"wandb: Agent Starting Run: fg7lzlcs with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 9\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
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],
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},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/fg7lzlcs
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" "
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""
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
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" class: default\n",
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" forecast_length: 1\n",
" interpolate: false\n",
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" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
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"wandb:\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
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"The number of items in train is: \n",
"17\n",
"The loss for epoch 0\n",
"6.22671012613265\n",
"The running loss is:\n",
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"The number of items in train is: \n",
"17\n",
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"1.6665449152317118\n",
"The running loss is:\n",
"22.39996526762843\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 2\n",
"1.317645015742849\n",
"The running loss is:\n",
"24.83209763467312\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 3\n",
"1.460711625569007\n",
"The running loss is:\n",
"18.151431158185005\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 4\n",
"1.067731244599118\n",
"The running loss is:\n",
"15.67039943113923\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 5\n",
"0.9217882018317195\n",
"The running loss is:\n",
"16.54207806289196\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 6\n",
"0.9730634154642329\n",
"The running loss is:\n",
"15.77171096089296\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 7\n",
"0.9277477035819388\n",
"The running loss is:\n",
"13.84425493516028\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 8\n",
"0.8143679373623693\n",
"The running loss is:\n",
"14.698465192690492\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 9\n",
"0.8646155995700289\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 9, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"39 30746 ... 0.000000\n",
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{
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"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: fg7lzlcs \n",
"\n",
"wandb: Agent Starting Run: c0an2nim with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 9\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: c0an2nim\n"
],
"name": "stdout"
},
{
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"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/c0an2nim
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 9\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 9\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 9\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 2\n",
" number_time_series: 3\n",
" output_seq_len: 2\n",
" seq_len: 9\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 2\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"68.1619100868702\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 0\n",
"4.00952412275707\n",
"The running loss is:\n",
"22.371742129325867\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 1\n",
"1.3159848311368156\n",
"The running loss is:\n",
"16.736645698547363\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 2\n",
"0.9845085705027861\n",
"The running loss is:\n",
"15.064269214868546\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 3\n",
"0.8861334832275615\n",
"The running loss is:\n",
"15.606667906045914\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 4\n",
"0.9180392885909361\n",
"The running loss is:\n",
"15.834020808339119\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 5\n",
"0.9314129887258306\n",
"The running loss is:\n",
"14.995947480201721\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 6\n",
"0.8821145576589248\n",
"The running loss is:\n",
"16.214449003338814\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 7\n",
"0.9537911178434596\n",
"The running loss is:\n",
"13.982399955391884\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 8\n",
"0.822494115023052\n",
"The running loss is:\n",
"13.378327805548906\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 9\n",
"0.7869604591499356\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 9, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"38 30745 ... 0.000000\n",
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"49 30756 ... 10.943957\n",
"50 30757 ... 11.364924\n",
"51 30758 ... 12.050787\n",
"52 30759 ... 10.258490\n",
"53 30760 ... 11.160790\n",
"54 30761 ... 10.898850\n",
"55 30762 ... 11.130223\n",
"56 30763 ... 10.652694\n",
"\n",
"[19 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: c0an2nim \n",
"\n",
"wandb: Agent Starting Run: ncqc46kb with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 9\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: ncqc46kb\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/ncqc46kb
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 9\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 9\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 9\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 9\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
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"out_seq_length:\n",
" desc: null\n",
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"sweep:\n",
" desc: null\n",
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"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"134.06062477827072\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 0\n",
"8.37878904864192\n",
"The running loss is:\n",
"42.89721769094467\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 1\n",
"2.681076105684042\n",
"The running loss is:\n",
"42.296622425317764\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 2\n",
"2.6435389015823603\n",
"The running loss is:\n",
"14.58924949169159\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 3\n",
"0.9118280932307243\n",
"The running loss is:\n",
"13.531480722129345\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 4\n",
"0.8457175451330841\n",
"The running loss is:\n",
"11.921478353440762\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 5\n",
"0.7450923970900476\n",
"The running loss is:\n",
"11.945398841053247\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 6\n",
"0.746587427565828\n",
"The running loss is:\n",
"11.684036530554295\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 7\n",
"0.7302522831596434\n",
"The running loss is:\n",
"11.216044843196869\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 8\n",
"0.7010028026998043\n",
"The running loss is:\n",
"10.252280615270138\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 9\n",
"0.6407675384543836\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 9, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"38 30745 ... 0.000000\n",
"39 30746 ... 0.000000\n",
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"50 30757 ... 9.209830\n",
"51 30758 ... 9.307390\n",
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"53 30760 ... 7.193860\n",
"54 30761 ... 7.226322\n",
"55 30762 ... 7.089177\n",
"56 30763 ... 5.841412\n",
"\n",
"[19 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: ncqc46kb \n",
"\n",
"wandb: Agent Starting Run: yh35fkau with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 10\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: yh35fkau\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/yh35fkau
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
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" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 10\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 10\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 10\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
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" value:\n",
" forecast_length: 1\n",
" number_time_series: 3\n",
" output_seq_len: 1\n",
" seq_len: 10\n",
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" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
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" desc: null\n",
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"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
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" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"18.99254409223795\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 0\n",
"1.117208476013997\n",
"The running loss is:\n",
"27.134451758436626\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 1\n",
"1.5961442210845074\n",
"The running loss is:\n",
"14.144931258633733\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 2\n",
"0.8320547799196314\n",
"The running loss is:\n",
"12.379254553001374\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 3\n",
"0.7281914442941985\n",
"The running loss is:\n",
"10.936451382935047\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 4\n",
"0.6433206695844146\n",
"The running loss is:\n",
"10.157983610406518\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 5\n",
"0.5975284476709717\n",
"The running loss is:\n",
"10.516974926926196\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 6\n",
"0.618645583936835\n",
"The running loss is:\n",
"10.19902788894251\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 7\n",
"0.5999428169966182\n",
"The running loss is:\n",
"9.524700343608856\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 8\n",
"0.560276490800521\n",
"The running loss is:\n",
"8.423859127797186\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 9\n",
"0.4955211251645404\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 10, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"37 30744 ... 0.000000\n",
"38 30745 ... 0.000000\n",
"39 30746 ... 0.000000\n",
"40 30747 ... 0.000000\n",
"41 30748 ... 0.000000\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 9.894247\n",
"48 30755 ... 9.785186\n",
"49 30756 ... 12.737395\n",
"50 30757 ... 12.269347\n",
"51 30758 ... 10.923274\n",
"52 30759 ... 11.233722\n",
"53 30760 ... 10.437478\n",
"54 30761 ... 6.463241\n",
"55 30762 ... 6.731721\n",
"56 30763 ... 7.264863\n",
"\n",
"[20 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: yh35fkau \n",
"\n",
"wandb: Agent Starting Run: og55gigm with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 10\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: og55gigm\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/og55gigm
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
"tags": []
}
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{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 10\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 10\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 10\n",
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" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
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" seq_len: 10\n",
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" desc: null\n",
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" desc: null\n",
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"sweep:\n",
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" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"16.133108966052532\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 0\n",
"1.0083193103782833\n",
"The running loss is:\n",
"28.869964830577374\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 1\n",
"1.8043728019110858\n",
"The running loss is:\n",
"12.548532001674175\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 2\n",
"0.784283250104636\n",
"The running loss is:\n",
"11.040770269930363\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 3\n",
"0.6900481418706477\n",
"The running loss is:\n",
"9.910119865089655\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 4\n",
"0.6193824915681034\n",
"The running loss is:\n",
"9.276767298579216\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 5\n",
"0.579797956161201\n",
"The running loss is:\n",
"9.77975993603468\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 6\n",
"0.6112349960021675\n",
"The running loss is:\n",
"8.785409968346357\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 7\n",
"0.5490881230216473\n",
"The running loss is:\n",
"8.258642934262753\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 8\n",
"0.516165183391422\n",
"The running loss is:\n",
"8.085627540946007\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 9\n",
"0.5053517213091254\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 10, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
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"name": "stderr"
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"[20 rows x 32 columns]\n"
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"name": "stdout"
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"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
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"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
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"name": "stderr"
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{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: og55gigm \n",
"\n",
"wandb: Agent Starting Run: lsyxrhtc with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 10\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
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"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/lsyxrhtc
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"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
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"batch_size:\n",
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" batch_size: 2\n",
" class: default\n",
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" interpolate: false\n",
" relevant_cols:\n",
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" training_path: Colorado_Douglas County.csv\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 10\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
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" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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" desc: null\n",
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" - MSE\n",
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" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"16.61077520623803\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 0\n",
"1.038173450389877\n",
"The running loss is:\n",
"25.137400671839714\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 1\n",
"1.5710875419899821\n",
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"12.270547769963741\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 2\n",
"0.7669092356227338\n",
"The running loss is:\n",
"10.999523766338825\n",
"The number of items in train is: \n",
"16\n",
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"0.6874702353961766\n",
"The running loss is:\n",
"9.699016734957695\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 4\n",
"0.6061885459348559\n",
"The running loss is:\n",
"9.058913193643093\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 5\n",
"0.5661820746026933\n",
"The running loss is:\n",
"9.072721466422081\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 6\n",
"0.5670450916513801\n",
"The running loss is:\n",
"9.164514727890491\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 7\n",
"0.5727821704931557\n",
"The running loss is:\n",
"8.674532353878021\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 8\n",
"0.5421582721173763\n",
"The running loss is:\n",
"8.324480183422565\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 9\n",
"0.5202800114639103\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 10, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
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{
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"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
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{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"53 30760 ... 7.678141\n",
"54 30761 ... 2.797157\n",
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"56 30763 ... 2.548421\n",
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"[20 rows x 32 columns]\n"
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"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: lsyxrhtc \n",
"\n",
"wandb: Agent Starting Run: raan5oee with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 10\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: raan5oee\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/raan5oee
\n",
" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
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" python_version: 3.6.9\n",
"batch_size:\n",
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" relevant_cols:\n",
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" - month\n",
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" scaler: StandardScaler\n",
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" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
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" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
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" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
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" desc: null\n",
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" optimizer: Adam\n",
"wandb:\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"14.07104841247201\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 0\n",
"0.8277087301454124\n",
"The running loss is:\n",
"22.927550297230482\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 1\n",
"1.348679429248852\n",
"The running loss is:\n",
"18.472346489550546\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 2\n",
"1.086608617032385\n",
"The running loss is:\n",
"12.637594176456332\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 3\n",
"0.7433878927327254\n",
"The running loss is:\n",
"11.350484196096659\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 4\n",
"0.6676755409468623\n",
"The running loss is:\n",
"9.470307543873787\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 5\n",
"0.5570769143455169\n",
"The running loss is:\n",
"12.329006131738424\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 6\n",
"0.7252356548081426\n",
"The running loss is:\n",
"10.936658833175898\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 7\n",
"0.6433328725397587\n",
"The running loss is:\n",
"10.534783300827257\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 8\n",
"0.6196931353427798\n",
"The running loss is:\n",
"8.076542284339666\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 9\n",
"0.47509072260821567\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 10, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
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{
"output_type": "stream",
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"\n",
"[20 rows x 32 columns]\n"
],
"name": "stdout"
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"output_type": "stream",
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"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
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{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: raan5oee \n",
"\n",
"wandb: Agent Starting Run: 78dfcr0h with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 10\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: 78dfcr0h\n"
],
"name": "stdout"
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{
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"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/78dfcr0h
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 10\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 10\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
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" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 10\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
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" forecast_length: 2\n",
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" seq_len: 10\n",
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" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
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" desc: null\n",
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"training_params:\n",
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" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"12.633374132215977\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 0\n",
"0.7895858832634985\n",
"The running loss is:\n",
"24.585037760436535\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 1\n",
"1.5365648600272834\n",
"The running loss is:\n",
"20.226487666368484\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 2\n",
"1.2641554791480303\n",
"The running loss is:\n",
"10.598256275057793\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 3\n",
"0.662391017191112\n",
"The running loss is:\n",
"10.891551569104195\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 4\n",
"0.6807219730690122\n",
"The running loss is:\n",
"9.729584485292435\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 5\n",
"0.6080990303307772\n",
"The running loss is:\n",
"10.25032301992178\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 6\n",
"0.6406451887451112\n",
"The running loss is:\n",
"12.466548934578896\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 7\n",
"0.779159308411181\n",
"The running loss is:\n",
"9.112505622208118\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 8\n",
"0.5695316013880074\n",
"The running loss is:\n",
"8.59875401854515\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 9\n",
"0.5374221261590719\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 10, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"37 30744 ... 0.000000\n",
"38 30745 ... 0.000000\n",
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"51 30758 ... 4.515433\n",
"52 30759 ... 4.815760\n",
"53 30760 ... 5.747679\n",
"54 30761 ... 2.746140\n",
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"56 30763 ... 1.695187\n",
"\n",
"[20 rows x 32 columns]\n"
],
"name": "stdout"
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 78dfcr0h \n",
"\n",
"wandb: Agent Starting Run: hoczfgq1 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 10\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: hoczfgq1\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/hoczfgq1
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 10\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 10\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 10\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 10\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
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" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"12.084807999432087\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 0\n",
"0.7553004999645054\n",
"The running loss is:\n",
"22.603727489709854\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 1\n",
"1.4127329681068659\n",
"The running loss is:\n",
"18.862066105008125\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 2\n",
"1.1788791315630078\n",
"The running loss is:\n",
"12.395430564880371\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 3\n",
"0.7747144103050232\n",
"The running loss is:\n",
"11.394499212503433\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 4\n",
"0.7121562007814646\n",
"The running loss is:\n",
"10.081028185784817\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 5\n",
"0.630064261611551\n",
"The running loss is:\n",
"9.585860520601273\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 6\n",
"0.5991162825375795\n",
"The running loss is:\n",
"11.116112791001797\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 7\n",
"0.6947570494376123\n",
"The running loss is:\n",
"9.021495692431927\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 8\n",
"0.5638434807769954\n",
"The running loss is:\n",
"8.90778385847807\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 9\n",
"0.5567364911548793\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 10, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"\n",
"[20 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: hoczfgq1 \n",
"\n",
"wandb: Agent Starting Run: c27e7jkt with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 10\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: c27e7jkt\n"
],
"name": "stdout"
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{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/c27e7jkt
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 10\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 10\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 10\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
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" value:\n",
" forecast_length: 1\n",
" number_time_series: 3\n",
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" seq_len: 10\n",
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" value: PyTorch\n",
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" value: true\n",
"training_params:\n",
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" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"19.021860733628273\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 0\n",
"1.118932984331075\n",
"The running loss is:\n",
"19.840141020715237\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 1\n",
"1.167067118865602\n",
"The running loss is:\n",
"19.325562549754977\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 2\n",
"1.1367977970444105\n",
"The running loss is:\n",
"14.916489260271192\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 3\n",
"0.8774405447218347\n",
"The running loss is:\n",
"13.93316643126309\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 4\n",
"0.819598025368417\n",
"The running loss is:\n",
"10.690809190273285\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 5\n",
"0.6288711288396049\n",
"The running loss is:\n",
"13.479163165204227\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 6\n",
"0.7928919508943663\n",
"The running loss is:\n",
"14.082069613039494\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 7\n",
"0.8283570360611466\n",
"The running loss is:\n",
"12.653895137831569\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 8\n",
"0.7443467728136217\n",
"The running loss is:\n",
"10.394164901226759\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 9\n",
"0.6114214647780446\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 10, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"37 30744 ... 0.000000\n",
"38 30745 ... 0.000000\n",
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"52 30759 ... 9.359842\n",
"53 30760 ... 10.251583\n",
"54 30761 ... 9.111098\n",
"55 30762 ... 4.847028\n",
"56 30763 ... 8.793217\n",
"\n",
"[20 rows x 32 columns]\n"
],
"name": "stdout"
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: c27e7jkt \n",
"\n",
"wandb: Agent Starting Run: rc0hdh5k with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 10\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: rc0hdh5k\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/rc0hdh5k
\n",
" "
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""
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
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" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 10\n",
" forecast_length: 2\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
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" training_path: Colorado_Douglas County.csv\n",
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" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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" desc: null\n",
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" - MSE\n",
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"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"19.67585827410221\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 0\n",
"1.2297411421313882\n",
"The running loss is:\n",
"20.92596773058176\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 1\n",
"1.30787298316136\n",
"The running loss is:\n",
"21.21123907715082\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 2\n",
"1.3257024423219264\n",
"The running loss is:\n",
"13.602266885340214\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 3\n",
"0.8501416803337634\n",
"The running loss is:\n",
"12.655046753585339\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 4\n",
"0.7909404220990837\n",
"The running loss is:\n",
"10.041675612330437\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 5\n",
"0.6276047257706523\n",
"The running loss is:\n",
"12.342215452343225\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 6\n",
"0.7713884657714516\n",
"The running loss is:\n",
"14.822323441505432\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 7\n",
"0.9263952150940895\n",
"The running loss is:\n",
"10.33838652074337\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 8\n",
"0.6461491575464606\n",
"The running loss is:\n",
"12.166576441377401\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 9\n",
"0.7604110275860876\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 10, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"37 30744 ... 0.000000\n",
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"52 30759 ... 9.926955\n",
"53 30760 ... 9.483013\n",
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"\n",
"[20 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: rc0hdh5k \n",
"\n",
"wandb: Agent Starting Run: 0dph3cu7 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 10\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: 0dph3cu7\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/0dph3cu7
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 10\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 10\n",
"forward_params:\n",
" desc: null\n",
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"inference_params:\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 10\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
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" value: MultiAttnHeadSimple\n",
"model_params:\n",
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" seq_len: 10\n",
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" desc: null\n",
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"sweep:\n",
" desc: null\n",
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"training_params:\n",
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" criterion: MSE\n",
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" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"16.855378910899162\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 0\n",
"1.0534611819311976\n",
"The running loss is:\n",
"20.029029339551926\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 1\n",
"1.2518143337219954\n",
"The running loss is:\n",
"16.415701150894165\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 2\n",
"1.0259813219308853\n",
"The running loss is:\n",
"15.392409943044186\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 3\n",
"0.9620256214402616\n",
"The running loss is:\n",
"12.786209851503372\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 4\n",
"0.7991381157189608\n",
"The running loss is:\n",
"10.640215292572975\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 5\n",
"0.665013455785811\n",
"The running loss is:\n",
"10.768309026956558\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 6\n",
"0.6730193141847849\n",
"The running loss is:\n",
"12.681664541363716\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 7\n",
"0.7926040338352323\n",
"The running loss is:\n",
"10.68557322025299\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 8\n",
"0.6678483262658119\n",
"The running loss is:\n",
"9.19628544151783\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 9\n",
"0.5747678400948644\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 10, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"37 30744 ... 0.000000\n",
"38 30745 ... 0.000000\n",
"39 30746 ... 0.000000\n",
"40 30747 ... 0.000000\n",
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"51 30758 ... 10.732364\n",
"52 30759 ... 10.814871\n",
"53 30760 ... 12.901135\n",
"54 30761 ... 3.767852\n",
"55 30762 ... 2.326275\n",
"56 30763 ... 3.856884\n",
"\n",
"[20 rows x 32 columns]\n"
],
"name": "stdout"
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 0dph3cu7 \n",
"\n",
"wandb: Agent Starting Run: scb18cx2 with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 10\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: scb18cx2\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/scb18cx2
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
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}
},
{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 10\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
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" decoder_params:\n",
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" test_csv_path: Colorado_Douglas County.csv\n",
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" desc: null\n",
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" desc: null\n",
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" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"95.02955102175474\n",
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"17\n",
"The loss for epoch 0\n",
"5.589973589514985\n",
"The running loss is:\n",
"24.03973775357008\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 1\n",
"1.4141022207982399\n",
"The running loss is:\n",
"15.009492529556155\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 2\n",
"0.8829113252680091\n",
"The running loss is:\n",
"15.12568387016654\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 3\n",
"0.8897461100097965\n",
"The running loss is:\n",
"14.419101245701313\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 4\n",
"0.8481824262177243\n",
"The running loss is:\n",
"14.80416202545166\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 5\n",
"0.8708330603206859\n",
"The running loss is:\n",
"14.07496515661478\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 6\n",
"0.827939126859693\n",
"The running loss is:\n",
"16.150368846952915\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 7\n",
"0.9500216968795833\n",
"The running loss is:\n",
"13.275858359294944\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 8\n",
"0.7809328446644085\n",
"The running loss is:\n",
"10.595419317483902\n",
"The number of items in train is: \n",
"17\n",
"The loss for epoch 9\n",
"0.6232599598519942\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 10, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"[20 rows x 32 columns]\n"
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{
"output_type": "stream",
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"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: scb18cx2 \n",
"\n",
"wandb: Agent Starting Run: wzhv9dbd with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 10\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
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],
"name": "stdout"
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{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/wzhv9dbd
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
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" desc: null\n",
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" value:\n",
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" class: default\n",
" forecast_history: 10\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
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" - month\n",
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" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
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" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
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" unsqueeze_dim: 1\n",
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" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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" desc: null\n",
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" optimizer: Adam\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
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"The number of items in train is: \n",
"16\n",
"The loss for epoch 0\n",
"5.966427356004715\n",
"The running loss is:\n",
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"The number of items in train is: \n",
"16\n",
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"1.7413400639779866\n",
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"The number of items in train is: \n",
"16\n",
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"0.8615592457354069\n",
"The running loss is:\n",
"21.267036229372025\n",
"The number of items in train is: \n",
"16\n",
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"1.3291897643357515\n",
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"19.88978810235858\n",
"The number of items in train is: \n",
"16\n",
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"1.2431117563974112\n",
"The running loss is:\n",
"15.775068141520023\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 5\n",
"0.9859417588450015\n",
"The running loss is:\n",
"14.655570544302464\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 6\n",
"0.915973159018904\n",
"The running loss is:\n",
"14.580344870686531\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 7\n",
"0.9112715544179082\n",
"The running loss is:\n",
"12.412341699004173\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 8\n",
"0.7757713561877608\n",
"The running loss is:\n",
"12.429722763597965\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 9\n",
"0.7768576727248728\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 10, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
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"[20 rows x 32 columns]\n"
],
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{
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"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: wzhv9dbd \n",
"\n",
"wandb: Agent Starting Run: g6lldpjl with config:\n",
"\tbatch_size: 2\n",
"\tforecast_history: 10\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: g6lldpjl\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/g6lldpjl
\n",
" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
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" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 2\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 2\n",
" class: default\n",
" forecast_history: 10\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
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"forward_params:\n",
" desc: null\n",
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" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 10\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
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" value:\n",
" forecast_length: 3\n",
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" seq_len: 10\n",
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" desc: null\n",
" value: PyTorch\n",
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" desc: null\n",
" value: Adam\n",
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" desc: null\n",
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"sweep:\n",
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" value: true\n",
"training_params:\n",
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" value:\n",
" batch_size: 2\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"74.41158412396908\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 0\n",
"4.650724007748067\n",
"The running loss is:\n",
"21.020324990153313\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 1\n",
"1.313770311884582\n",
"The running loss is:\n",
"16.04583202302456\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 2\n",
"1.002864501439035\n",
"The running loss is:\n",
"17.90377826243639\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 3\n",
"1.1189861414022744\n",
"The running loss is:\n",
"14.566076338291168\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 4\n",
"0.910379771143198\n",
"The running loss is:\n",
"14.132137462496758\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 5\n",
"0.8832585914060473\n",
"The running loss is:\n",
"13.948560565710068\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 6\n",
"0.8717850353568792\n",
"The running loss is:\n",
"13.438048601150513\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 7\n",
"0.839878037571907\n",
"The running loss is:\n",
"13.514577560126781\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 8\n",
"0.8446610975079238\n",
"The running loss is:\n",
"12.867796912789345\n",
"The number of items in train is: \n",
"16\n",
"The loss for epoch 9\n",
"0.804237307049334\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 10, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"37 30744 ... 0.000000\n",
"38 30745 ... 0.000000\n",
"39 30746 ... 0.000000\n",
"40 30747 ... 0.000000\n",
"41 30748 ... 0.000000\n",
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"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 10.610271\n",
"48 30755 ... 10.570126\n",
"49 30756 ... 10.616474\n",
"50 30757 ... 10.498391\n",
"51 30758 ... 11.009744\n",
"52 30759 ... 10.557771\n",
"53 30760 ... 10.617533\n",
"54 30761 ... 10.595282\n",
"55 30762 ... 10.595298\n",
"56 30763 ... 10.593192\n",
"\n",
"[20 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: g6lldpjl \n",
"\n",
"wandb: Agent Starting Run: 5kgpjqql with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 1\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: 5kgpjqql\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/5kgpjqql
\n",
" "
],
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""
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},
"metadata": {
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}
},
{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 1\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 1\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 1\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
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" forecast_length: 1\n",
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" seq_len: 1\n",
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" value: PyTorch\n",
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"sweep:\n",
" desc: null\n",
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"training_params:\n",
" desc: null\n",
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" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"17.670363292098045\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 0\n",
"1.2621688065784318\n",
"The running loss is:\n",
"10.943816676735878\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 1\n",
"0.7817011911954198\n",
"The running loss is:\n",
"10.41209028288722\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 2\n",
"0.7437207344919443\n",
"The running loss is:\n",
"9.48156014829874\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 3\n",
"0.6772542963070529\n",
"The running loss is:\n",
"9.911844491958618\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 4\n",
"0.7079888922827584\n",
"The running loss is:\n",
"9.89071624726057\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 5\n",
"0.7064797319471836\n",
"The running loss is:\n",
"9.785955913364887\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 6\n",
"0.6989968509546348\n",
"The running loss is:\n",
"9.477959398645908\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 7\n",
"0.6769970999032792\n",
"The running loss is:\n",
"10.341568265110254\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 8\n",
"0.7386834475078753\n",
"The running loss is:\n",
"10.629889108240604\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 9\n",
"0.7592777934457574\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 12.328932\n",
"48 30755 ... 11.992808\n",
"49 30756 ... 11.800481\n",
"50 30757 ... 11.669888\n",
"51 30758 ... 11.565799\n",
"52 30759 ... 11.473088\n",
"53 30760 ... 11.385262\n",
"54 30761 ... 11.635700\n",
"55 30762 ... 11.695193\n",
"56 30763 ... 11.672710\n",
"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
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"name": "stderr"
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{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 5kgpjqql \n",
"\n",
"wandb: Agent Starting Run: 7qvksyb1 with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 1\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: 7qvksyb1\n"
],
"name": "stdout"
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{
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"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/7qvksyb1
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
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" framework: torch\n",
" is_jupyter_run: true\n",
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" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
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" interpolate: false\n",
" relevant_cols:\n",
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" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
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" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 1\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
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" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
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" seq_len: 1\n",
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" value: PyTorch\n",
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" batch_size: 3\n",
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" epochs: 10\n",
" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"22.802268385887146\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 0\n",
"1.6287334561347961\n",
"The running loss is:\n",
"17.569238662719727\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 1\n",
"1.2549456187656947\n",
"The running loss is:\n",
"16.22460624575615\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 2\n",
"1.1589004461254393\n",
"The running loss is:\n",
"14.956971347332\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 3\n",
"1.068355096238\n",
"The running loss is:\n",
"15.105294823646545\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 4\n",
"1.0789496302604675\n",
"The running loss is:\n",
"15.303263306617737\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 5\n",
"1.0930902361869812\n",
"The running loss is:\n",
"15.001798063516617\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 6\n",
"1.0715570045369012\n",
"The running loss is:\n",
"14.771975100040436\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 7\n",
"1.055141078574317\n",
"The running loss is:\n",
"14.277655333280563\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 8\n",
"1.0198325238057546\n",
"The running loss is:\n",
"14.258073136210442\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 9\n",
"1.018433795443603\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
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{
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
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{
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"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"47 30754 ... 17.221895\n",
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"49 30756 ... 20.901167\n",
"50 30757 ... 21.527845\n",
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"52 30759 ... 21.745245\n",
"53 30760 ... 21.590210\n",
"54 30761 ... 22.387379\n",
"55 30762 ... 22.718334\n",
"56 30763 ... 22.768944\n",
"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 7qvksyb1 \n",
"\n",
"wandb: Agent Starting Run: py7m8aa2 with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 1\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: py7m8aa2\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/py7m8aa2
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" "
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""
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
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"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 1\n",
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" relevant_cols:\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
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" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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" desc: null\n",
" value:\n",
" - MSE\n",
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" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"22.336795777082443\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 0\n",
"1.5954854126487459\n",
"The running loss is:\n",
"16.64599171280861\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 1\n",
"1.1889994080577577\n",
"The running loss is:\n",
"14.604424864053726\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 2\n",
"1.0431732045752662\n",
"The running loss is:\n",
"14.123595744371414\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 3\n",
"1.008828267455101\n",
"The running loss is:\n",
"14.480102002620697\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 4\n",
"1.0342930001871926\n",
"The running loss is:\n",
"13.984807938337326\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 5\n",
"0.9989148527383804\n",
"The running loss is:\n",
"14.12735378742218\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 6\n",
"1.0090966991015844\n",
"The running loss is:\n",
"14.249413669109344\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 7\n",
"1.017815262079239\n",
"The running loss is:\n",
"13.871794015169144\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 8\n",
"0.9908424296549388\n",
"The running loss is:\n",
"13.480072140693665\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 9\n",
"0.9628622957638332\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 7.018013\n",
"48 30755 ... 3.923897\n",
"49 30756 ... 2.033710\n",
"50 30757 ... 0.645433\n",
"51 30758 ... -0.533605\n",
"52 30759 ... -1.625411\n",
"53 30760 ... -2.680852\n",
"54 30761 ... 0.480797\n",
"55 30762 ... 1.198586\n",
"56 30763 ... 0.897552\n",
"\n",
"[11 rows x 32 columns]\n"
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"name": "stdout"
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{
"output_type": "stream",
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"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: py7m8aa2 \n",
"\n",
"wandb: Agent Starting Run: fhkws31a with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 1\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: fhkws31a\n"
],
"name": "stdout"
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{
"output_type": "display_data",
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"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/fhkws31a
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 1\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 1\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 1\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 1\n",
" number_time_series: 3\n",
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" seq_len: 1\n",
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" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
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"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"13.473997741937637\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 0\n",
"0.9624284101384026\n",
"The running loss is:\n",
"27.837897576391697\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 1\n",
"1.9884212554565497\n",
"The running loss is:\n",
"11.861431896686554\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 2\n",
"0.847245135477611\n",
"The running loss is:\n",
"10.067777810618281\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 3\n",
"0.7191269864727344\n",
"The running loss is:\n",
"9.917817741632462\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 4\n",
"0.7084155529737473\n",
"The running loss is:\n",
"9.74946603924036\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 5\n",
"0.6963904313743114\n",
"The running loss is:\n",
"9.383864752948284\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 6\n",
"0.6702760537820203\n",
"The running loss is:\n",
"9.33708634832874\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 7\n",
"0.6669347391663385\n",
"The running loss is:\n",
"10.058764830231667\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 8\n",
"0.7184832021594048\n",
"The running loss is:\n",
"10.721103806048632\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 9\n",
"0.7657931290034737\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
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{
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"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 12.203970\n",
"48 30755 ... 11.892198\n",
"49 30756 ... 11.772248\n",
"50 30757 ... 11.728283\n",
"51 30758 ... 11.714417\n",
"52 30759 ... 11.712473\n",
"53 30760 ... 11.715252\n",
"54 30761 ... 11.695059\n",
"55 30762 ... 11.690609\n",
"56 30763 ... 11.692395\n",
"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: fhkws31a \n",
"\n",
"wandb: Agent Starting Run: o8fp0wdh with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 1\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: o8fp0wdh\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/o8fp0wdh
\n",
" "
],
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""
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 1\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
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"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 1\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
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" value: MultiAttnHeadSimple\n",
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"sweep:\n",
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" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"18.880937218666077\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 0\n",
"1.3486383727618627\n",
"The running loss is:\n",
"30.557601034641266\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 1\n",
"2.1826857881886617\n",
"The running loss is:\n",
"16.620768785476685\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 2\n",
"1.1871977703911918\n",
"The running loss is:\n",
"15.550219416618347\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 3\n",
"1.110729958329882\n",
"The running loss is:\n",
"14.529386848211288\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 4\n",
"1.0378133463008063\n",
"The running loss is:\n",
"14.709754675626755\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 5\n",
"1.0506967625447683\n",
"The running loss is:\n",
"14.263691067695618\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 6\n",
"1.0188350762639726\n",
"The running loss is:\n",
"13.642646819353104\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 7\n",
"0.974474772810936\n",
"The running loss is:\n",
"13.388307765126228\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 8\n",
"0.9563076975090163\n",
"The running loss is:\n",
"13.098741456866264\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 9\n",
"0.9356243897761617\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
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"49 30756 ... 19.515354\n",
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"56 30763 ... 21.025421\n",
"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
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"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
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"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
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"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
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"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
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{
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"wandb: Agent Finished Run: o8fp0wdh \n",
"\n",
"wandb: Agent Starting Run: npyvux13 with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 1\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
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"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
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"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
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" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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" desc: null\n",
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" seq_len: 1\n",
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" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"17.19215828180313\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 0\n",
"1.2280113058430808\n",
"The running loss is:\n",
"35.54996246099472\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 1\n",
"2.539283032928194\n",
"The running loss is:\n",
"16.276898205280304\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 2\n",
"1.1626355860914503\n",
"The running loss is:\n",
"15.494183450937271\n",
"The number of items in train is: \n",
"14\n",
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"1.1067273893526621\n",
"The running loss is:\n",
"13.394286423921585\n",
"The number of items in train is: \n",
"14\n",
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"0.9567347445658275\n",
"The running loss is:\n",
"13.729548782110214\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 5\n",
"0.9806820558650153\n",
"The running loss is:\n",
"13.483346164226532\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 6\n",
"0.9630961545876094\n",
"The running loss is:\n",
"13.767163097858429\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 7\n",
"0.9833687927041735\n",
"The running loss is:\n",
"13.156352579593658\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 8\n",
"0.9397394699709756\n",
"The running loss is:\n",
"12.842736065387726\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 9\n",
"0.9173382903848376\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
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{
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"torch.Size([10])\n",
"test_data scale\n",
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{
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"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
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{
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"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 7.175701\n",
"48 30755 ... 4.349280\n",
"49 30756 ... 2.709584\n",
"50 30757 ... 1.539658\n",
"51 30758 ... 0.555692\n",
"52 30759 ... -0.354660\n",
"53 30760 ... -1.235872\n",
"54 30761 ... 1.540366\n",
"55 30762 ... 2.118507\n",
"56 30763 ... 1.826522\n",
"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
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{
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"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
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{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: npyvux13 \n",
"\n",
"wandb: Agent Starting Run: v4j861hu with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 1\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: v4j861hu\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/v4j861hu
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"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
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" framework: torch\n",
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"batch_size:\n",
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" scaling: StandardScaler\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
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" test_csv_path: Colorado_Douglas County.csv\n",
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"\n",
"Torch is using cpu\n",
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"The number of items in train is: \n",
"14\n",
"The loss for epoch 0\n",
"1.272445575999362\n",
"The running loss is:\n",
"27.287052668631077\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 1\n",
"1.9490751906165056\n",
"The running loss is:\n",
"23.304617062211037\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 2\n",
"1.6646155044436455\n",
"The running loss is:\n",
"13.46847514808178\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 3\n",
"0.9620339391486985\n",
"The running loss is:\n",
"10.77438042499125\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 4\n",
"0.7695986017850893\n",
"The running loss is:\n",
"10.228682920336723\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 5\n",
"0.7306202085954803\n",
"The running loss is:\n",
"9.9163583740592\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 6\n",
"0.7083113124328\n",
"The running loss is:\n",
"9.541842748411\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 7\n",
"0.6815601963150714\n",
"The running loss is:\n",
"10.52641460672021\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 8\n",
"0.751886757622872\n",
"The running loss is:\n",
"10.936396487057209\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 9\n",
"0.7811711776469435\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
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"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 11.996588\n",
"48 30755 ... 11.617249\n",
"49 30756 ... 11.487004\n",
"50 30757 ... 11.456182\n",
"51 30758 ... 11.465044\n",
"52 30759 ... 11.489745\n",
"53 30760 ... 11.520768\n",
"54 30761 ... 11.406167\n",
"55 30762 ... 11.381589\n",
"56 30763 ... 11.392943\n",
"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: v4j861hu \n",
"\n",
"wandb: Agent Starting Run: pb2xg24u with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 1\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: pb2xg24u\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/pb2xg24u
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
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" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
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" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 1\n",
"forward_params:\n",
" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 1\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 2\n",
" number_time_series: 3\n",
" output_seq_len: 2\n",
" seq_len: 1\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 2\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"18.450218737125397\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 0\n",
"1.3178727669375283\n",
"The running loss is:\n",
"33.69246228039265\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 1\n",
"2.4066044485994746\n",
"The running loss is:\n",
"30.424543470144272\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 2\n",
"2.1731816764388765\n",
"The running loss is:\n",
"21.68705663084984\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 3\n",
"1.5490754736321313\n",
"The running loss is:\n",
"15.464419141411781\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 4\n",
"1.1046013672436987\n",
"The running loss is:\n",
"13.43197026848793\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 5\n",
"0.9594264477491379\n",
"The running loss is:\n",
"13.450857311487198\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 6\n",
"0.9607755222490856\n",
"The running loss is:\n",
"12.503621444106102\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 7\n",
"0.8931158174361501\n",
"The running loss is:\n",
"12.548032850027084\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 8\n",
"0.8962880607162204\n",
"The running loss is:\n",
"12.026508867740631\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 9\n",
"0.8590363476957593\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 15.448249\n",
"48 30755 ... 16.847450\n",
"49 30756 ... 17.598450\n",
"50 30757 ... 17.948925\n",
"51 30758 ... 18.051918\n",
"52 30759 ... 18.001993\n",
"53 30760 ... 17.857580\n",
"54 30761 ... 18.449734\n",
"55 30762 ... 18.702061\n",
"56 30763 ... 18.744408\n",
"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: pb2xg24u \n",
"\n",
"wandb: Agent Starting Run: w8s1lsld with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 1\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: w8s1lsld\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/w8s1lsld
\n",
" "
],
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""
]
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 1\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 1\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 1\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 1\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
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" desc: null\n",
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" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
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"training_params:\n",
" desc: null\n",
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" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"16.729584485292435\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 0\n",
"1.194970320378031\n",
"The running loss is:\n",
"31.90469980239868\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 1\n",
"2.278907128742763\n",
"The running loss is:\n",
"26.94806531071663\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 2\n",
"1.9248618079083306\n",
"The running loss is:\n",
"21.172048971056938\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 3\n",
"1.5122892122183527\n",
"The running loss is:\n",
"14.548314154148102\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 4\n",
"1.0391652967248644\n",
"The running loss is:\n",
"14.059065759181976\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 5\n",
"1.0042189827987127\n",
"The running loss is:\n",
"13.152787834405899\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 6\n",
"0.9394848453147071\n",
"The running loss is:\n",
"13.332339078187943\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 7\n",
"0.9523099341562816\n",
"The running loss is:\n",
"12.577288955450058\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 8\n",
"0.898377782532147\n",
"The running loss is:\n",
"12.499642044305801\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 9\n",
"0.8928315745932716\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 8.248249\n",
"48 30755 ... 6.103832\n",
"49 30756 ... 4.877185\n",
"50 30757 ... 3.973589\n",
"51 30758 ... 3.183706\n",
"52 30759 ... 2.433849\n",
"53 30760 ... 1.698083\n",
"54 30761 ... 4.270024\n",
"55 30762 ... 4.703514\n",
"56 30763 ... 4.384280\n",
"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: w8s1lsld \n",
"\n",
"wandb: Agent Starting Run: 5rzp4ajy with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 1\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: 5rzp4ajy\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/5rzp4ajy
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 1\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 1\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 1\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 1\n",
" number_time_series: 3\n",
" output_seq_len: 1\n",
" seq_len: 1\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 1\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"36.93057554960251\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 0\n",
"2.637898253543036\n",
"The running loss is:\n",
"26.37780451774597\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 1\n",
"1.8841288941247123\n",
"The running loss is:\n",
"22.75959214195609\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 2\n",
"1.6256851529968637\n",
"The running loss is:\n",
"30.54565773718059\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 3\n",
"2.1818326955128993\n",
"The running loss is:\n",
"36.84430718794465\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 4\n",
"2.631736227710332\n",
"The running loss is:\n",
"36.018092423677444\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 5\n",
"2.5727208874055316\n",
"The running loss is:\n",
"19.373262114822865\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 6\n",
"1.3838044367730618\n",
"The running loss is:\n",
"11.502933956682682\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 7\n",
"0.8216381397630487\n",
"The running loss is:\n",
"10.898656576871872\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 8\n",
"0.7784754697765622\n",
"The running loss is:\n",
"10.19880486652255\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 9\n",
"0.7284860618944679\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 12.216917\n",
"48 30755 ... 11.971518\n",
"49 30756 ... 11.933516\n",
"50 30757 ... 11.975511\n",
"51 30758 ... 12.048363\n",
"52 30759 ... 12.133118\n",
"53 30760 ... 12.222463\n",
"54 30761 ... 11.917004\n",
"55 30762 ... 11.855834\n",
"56 30763 ... 11.888893\n",
"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 5rzp4ajy \n",
"\n",
"wandb: Agent Starting Run: 3ek9rvyd with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 1\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: 3ek9rvyd\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/3ek9rvyd
\n",
" "
],
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""
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},
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{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 1\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 1\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 1\n",
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" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
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" forecast_length: 2\n",
" number_time_series: 3\n",
" output_seq_len: 2\n",
" seq_len: 1\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
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" desc: null\n",
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" desc: null\n",
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"sweep:\n",
" desc: null\n",
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"training_params:\n",
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" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"41.207330763339996\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 0\n",
"2.9433807688099995\n",
"The running loss is:\n",
"27.082152098417282\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 1\n",
"1.9344394356012344\n",
"The running loss is:\n",
"25.876445710659027\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 2\n",
"1.8483175507613592\n",
"The running loss is:\n",
"33.90110743790865\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 3\n",
"2.421507674136332\n",
"The running loss is:\n",
"44.29538279771805\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 4\n",
"3.1639559141227176\n",
"The running loss is:\n",
"37.04779974371195\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 5\n",
"2.6462714102651392\n",
"The running loss is:\n",
"17.184944421052933\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 6\n",
"1.2274960300752096\n",
"The running loss is:\n",
"13.733961462974548\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 7\n",
"0.9809972473553249\n",
"The running loss is:\n",
"14.716185823082924\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 8\n",
"1.0511561302202088\n",
"The running loss is:\n",
"13.83261838182807\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 9\n",
"0.9880441701305764\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 9.035178\n",
"48 30755 ... 8.766874\n",
"49 30756 ... 8.916343\n",
"50 30757 ... 9.113027\n",
"51 30758 ... 9.315046\n",
"52 30759 ... 9.517670\n",
"53 30760 ... 9.720361\n",
"54 30761 ... 8.664521\n",
"55 30762 ... 8.724984\n",
"56 30763 ... 8.911608\n",
"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 3ek9rvyd \n",
"\n",
"wandb: Agent Starting Run: 874h0d1x with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 1\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: 874h0d1x\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/874h0d1x
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 1\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 1\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 1\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 1\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"44.45691132545471\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 0\n",
"3.175493666103908\n",
"The running loss is:\n",
"29.342597395181656\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 1\n",
"2.095899813941547\n",
"The running loss is:\n",
"31.56341904401779\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 2\n",
"2.2545299317155565\n",
"The running loss is:\n",
"22.378557235002518\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 3\n",
"1.5984683739287513\n",
"The running loss is:\n",
"29.19557212293148\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 4\n",
"2.08539800878082\n",
"The running loss is:\n",
"19.708526015281677\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 5\n",
"1.4077518582344055\n",
"The running loss is:\n",
"16.751707702875137\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 6\n",
"1.196550550205367\n",
"The running loss is:\n",
"17.867665767669678\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 7\n",
"1.276261840547834\n",
"The running loss is:\n",
"17.180501848459244\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 8\n",
"1.2271787034613746\n",
"The running loss is:\n",
"11.488581970334053\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 9\n",
"0.8206129978810038\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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},
{
"output_type": "stream",
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"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 9.363071\n",
"48 30755 ... 8.094663\n",
"49 30756 ... 7.382749\n",
"50 30757 ... 6.801587\n",
"51 30758 ... 6.251144\n",
"52 30759 ... 5.707920\n",
"53 30760 ... 5.166392\n",
"54 30761 ... 7.522529\n",
"55 30762 ... 7.662219\n",
"56 30763 ... 7.281145\n",
"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 874h0d1x \n",
"\n",
"wandb: Agent Starting Run: 59n65cyk with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 2\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: 59n65cyk\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/59n65cyk
\n",
" "
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""
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 2\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 2\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 2\n",
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" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
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" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
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" value:\n",
" forecast_length: 1\n",
" number_time_series: 3\n",
" output_seq_len: 1\n",
" seq_len: 2\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
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" desc: null\n",
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"sweep:\n",
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" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"18.64117774181068\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 0\n",
"1.3315126958436199\n",
"The running loss is:\n",
"13.435925766825676\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 1\n",
"0.9597089833446911\n",
"The running loss is:\n",
"9.767426192760468\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 2\n",
"0.6976732994828906\n",
"The running loss is:\n",
"8.82443618774414\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 3\n",
"0.6303168705531529\n",
"The running loss is:\n",
"8.694632604718208\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 4\n",
"0.6210451860513005\n",
"The running loss is:\n",
"9.05456755310297\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 5\n",
"0.6467548252216407\n",
"The running loss is:\n",
"8.356636479496956\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 6\n",
"0.596902605678354\n",
"The running loss is:\n",
"9.370028473436832\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 7\n",
"0.6692877481026309\n",
"The running loss is:\n",
"9.064932033419609\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 8\n",
"0.6474951452442578\n",
"The running loss is:\n",
"7.789532475173473\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 9\n",
"0.5563951767981052\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 2, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 12.928371\n",
"48 30755 ... 15.471230\n",
"49 30756 ... 15.420227\n",
"50 30757 ... 15.615501\n",
"51 30758 ... 14.940125\n",
"52 30759 ... 14.135720\n",
"53 30760 ... 12.981010\n",
"54 30761 ... 14.701076\n",
"55 30762 ... 15.958694\n",
"56 30763 ... 16.192640\n",
"\n",
"[12 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 59n65cyk \n",
"\n",
"wandb: Agent Starting Run: mwiqfbe8 with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 2\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: mwiqfbe8\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/mwiqfbe8
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 2\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 2\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 2\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 2\n",
" number_time_series: 3\n",
" output_seq_len: 2\n",
" seq_len: 2\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 2\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"18.326901137828827\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 0\n",
"1.3090643669877733\n",
"The running loss is:\n",
"15.11211396753788\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 1\n",
"1.0794367119669914\n",
"The running loss is:\n",
"12.211668342351913\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 2\n",
"0.8722620244537082\n",
"The running loss is:\n",
"11.787426233291626\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 3\n",
"0.8419590166636876\n",
"The running loss is:\n",
"11.032762914896011\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 4\n",
"0.7880544939211437\n",
"The running loss is:\n",
"10.791624754667282\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 5\n",
"0.7708303396190915\n",
"The running loss is:\n",
"10.629769459366798\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 6\n",
"0.7592692470976284\n",
"The running loss is:\n",
"10.726359777152538\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 7\n",
"0.7661685555108956\n",
"The running loss is:\n",
"10.42826895415783\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 8\n",
"0.7448763538684163\n",
"The running loss is:\n",
"10.19526007771492\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 9\n",
"0.7282328626939228\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 2, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 8.490717\n",
"48 30755 ... 11.641187\n",
"49 30756 ... 9.905563\n",
"50 30757 ... 9.972510\n",
"51 30758 ... 8.155688\n",
"52 30759 ... 6.332791\n",
"53 30760 ... 3.572726\n",
"54 30761 ... 2.926773\n",
"55 30762 ... 4.603442\n",
"56 30763 ... 4.082183\n",
"\n",
"[12 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: mwiqfbe8 \n",
"\n",
"wandb: Agent Starting Run: odk5x886 with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 2\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: odk5x886\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/odk5x886
\n",
" "
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""
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 2\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
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" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 2\n",
"forward_params:\n",
" desc: null\n",
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" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 2\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
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" seq_len: 2\n",
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" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"17.417068786919117\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"1.3397745220707014\n",
"The running loss is:\n",
"12.89317137002945\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"0.9917824130791885\n",
"The running loss is:\n",
"10.928997546434402\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"0.8406921189564925\n",
"The running loss is:\n",
"9.924030363559723\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"0.7633869510430557\n",
"The running loss is:\n",
"9.564537711441517\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 4\n",
"0.7357336701108859\n",
"The running loss is:\n",
"9.373335793614388\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.7210258302780298\n",
"The running loss is:\n",
"9.464933928102255\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"0.7280718406232504\n",
"The running loss is:\n",
"8.969834722578526\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.6899872863521943\n",
"The running loss is:\n",
"9.041607558727264\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.6955082737482511\n",
"The running loss is:\n",
"8.688183203339577\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.6683217848722751\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 2, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
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"48 30755 ... 12.863463\n",
"49 30756 ... 13.743500\n",
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"51 30758 ... 15.064708\n",
"52 30759 ... 14.955314\n",
"53 30760 ... 14.306695\n",
"54 30761 ... 16.493378\n",
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"56 30763 ... 19.960632\n",
"\n",
"[12 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: odk5x886 \n",
"\n",
"wandb: Agent Starting Run: t7774fje with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 2\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: t7774fje\n"
],
"name": "stdout"
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{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/t7774fje
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
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" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
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" class: default\n",
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" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
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" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
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"forward_params:\n",
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" file_path: Colorado_Douglas County.csv\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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"metrics:\n",
" desc: null\n",
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" - MSE\n",
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" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"14.82401143014431\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 0\n",
"1.058857959296022\n",
"The running loss is:\n",
"32.10828600823879\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 1\n",
"2.293449000588485\n",
"The running loss is:\n",
"16.21480782330036\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 2\n",
"1.1582005588071687\n",
"The running loss is:\n",
"10.950186144560575\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 3\n",
"0.7821561531828982\n",
"The running loss is:\n",
"9.553723186254501\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 4\n",
"0.6824087990181786\n",
"The running loss is:\n",
"9.226969838142395\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 5\n",
"0.6590692741530282\n",
"The running loss is:\n",
"8.455528162419796\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 6\n",
"0.6039662973156997\n",
"The running loss is:\n",
"8.660504542291164\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 7\n",
"0.6186074673065117\n",
"The running loss is:\n",
"9.142078697681427\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 8\n",
"0.653005621262959\n",
"The running loss is:\n",
"7.957540884613991\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 9\n",
"0.5683957774724279\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 2, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 13.434075\n",
"48 30755 ... 15.096694\n",
"49 30756 ... 14.959582\n",
"50 30757 ... 14.883185\n",
"51 30758 ... 14.149712\n",
"52 30759 ... 13.306772\n",
"53 30760 ... 12.192998\n",
"54 30761 ... 13.766081\n",
"55 30762 ... 14.880667\n",
"56 30763 ... 15.032399\n",
"\n",
"[12 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: t7774fje \n",
"\n",
"wandb: Agent Starting Run: hebxlk2l with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 2\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: hebxlk2l\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/hebxlk2l
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
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"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 2\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
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" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
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" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"15.723597005009651\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 0\n",
"1.1231140717864037\n",
"The running loss is:\n",
"28.490644335746765\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 1\n",
"2.035046023981912\n",
"The running loss is:\n",
"13.955412358045578\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 2\n",
"0.996815168431827\n",
"The running loss is:\n",
"13.241860419511795\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 3\n",
"0.945847172822271\n",
"The running loss is:\n",
"11.466906487941742\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 4\n",
"0.8190647491386959\n",
"The running loss is:\n",
"10.924891918897629\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 5\n",
"0.780349422778402\n",
"The running loss is:\n",
"10.513674184679985\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 6\n",
"0.7509767274771418\n",
"The running loss is:\n",
"9.895356297492981\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 7\n",
"0.7068111641066415\n",
"The running loss is:\n",
"9.991915211081505\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 8\n",
"0.7137082293629646\n",
"The running loss is:\n",
"9.326003551483154\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 9\n",
"0.6661431108202253\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 2, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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{
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
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"48 30755 ... 13.185613\n",
"49 30756 ... 11.520662\n",
"50 30757 ... 11.929882\n",
"51 30758 ... 10.195442\n",
"52 30759 ... 8.390749\n",
"53 30760 ... 5.661302\n",
"54 30761 ... 5.480610\n",
"55 30762 ... 7.734272\n",
"56 30763 ... 7.415340\n",
"\n",
"[12 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: hebxlk2l \n",
"\n",
"wandb: Agent Starting Run: f9q3bn5p with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 2\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: f9q3bn5p\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/f9q3bn5p
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
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" python_version: 3.6.9\n",
"batch_size:\n",
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" class: default\n",
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" scaler: StandardScaler\n",
" target_col:\n",
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" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
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" - MSE\n",
"model_name:\n",
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" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"13.760922595858574\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"1.0585325073737364\n",
"The running loss is:\n",
"28.3547403216362\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"2.1811338708950925\n",
"The running loss is:\n",
"12.500449031591415\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"0.9615730024301089\n",
"The running loss is:\n",
"11.595830231904984\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"0.8919869409157679\n",
"The running loss is:\n",
"9.472603611648083\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 4\n",
"0.7286618162806218\n",
"The running loss is:\n",
"9.583042055368423\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.7371570811821864\n",
"The running loss is:\n",
"9.448577012866735\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"0.7268136163743643\n",
"The running loss is:\n",
"8.934248983860016\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.6872499218353858\n",
"The running loss is:\n",
"8.718861654400826\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.6706816657231405\n",
"The running loss is:\n",
"8.367036566138268\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.6436181973952514\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 2, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 9.351791\n",
"48 30755 ... 13.041138\n",
"49 30756 ... 14.050688\n",
"50 30757 ... 14.945793\n",
"51 30758 ... 15.019467\n",
"52 30759 ... 14.608635\n",
"53 30760 ... 13.617412\n",
"54 30761 ... 15.745596\n",
"55 30762 ... 18.032488\n",
"56 30763 ... 19.294676\n",
"\n",
"[12 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: f9q3bn5p \n",
"\n",
"wandb: Agent Starting Run: mx7h8bz8 with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 2\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: mx7h8bz8\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/mx7h8bz8
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" "
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""
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
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"wandb:\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
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"The number of items in train is: \n",
"14\n",
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"1.1983242226498467\n",
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"26.58887927979231\n",
"The number of items in train is: \n",
"14\n",
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"1.8992056628423077\n",
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"24.896283831447363\n",
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"14\n",
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"1.7783059879605259\n",
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"17.928823247551918\n",
"The number of items in train is: \n",
"14\n",
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"1.280630231967994\n",
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"12.109752431511879\n",
"The number of items in train is: \n",
"14\n",
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"8.675509860739112\n",
"The number of items in train is: \n",
"14\n",
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"0.6196792757670794\n",
"The running loss is:\n",
"10.843803316354752\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 6\n",
"0.7745573797396251\n",
"The running loss is:\n",
"9.790428780019283\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 7\n",
"0.6993163414299488\n",
"The running loss is:\n",
"8.949594028294086\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 8\n",
"0.6392567163067204\n",
"The running loss is:\n",
"8.564673632383347\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 9\n",
"0.6117624023130962\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 2, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
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"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
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{
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"test_data scale\n",
"Un-transforming data\n"
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},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
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{
"output_type": "stream",
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"54 30761 ... 11.024097\n",
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"[12 rows x 32 columns]\n"
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
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{
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"wandb: Agent Finished Run: mx7h8bz8 \n",
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"\tforecast_history: 2\n",
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"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
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" target_col:\n",
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" decoder_params:\n",
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"lr:\n",
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"14\n",
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"The number of items in train is: \n",
"14\n",
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"0.8376404494047165\n",
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"10.596563547849655\n",
"The number of items in train is: \n",
"14\n",
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"0.7568973962749753\n",
"The running loss is:\n",
"10.482213720679283\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 7\n",
"0.7487295514770916\n",
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"10.999816179275513\n",
"The number of items in train is: \n",
"14\n",
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"0.7857011556625366\n",
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"8.992802858352661\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 9\n",
"0.6423430613109044\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 2, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
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"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
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"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
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{
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{
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"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
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"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
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"50 30757 ... 9.121360\n",
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"52 30759 ... 5.924037\n",
"53 30760 ... 3.844475\n",
"54 30761 ... 3.221498\n",
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"\n",
"[12 rows x 32 columns]\n"
],
"name": "stdout"
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
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"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
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{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: lm9loxi1 \n",
"\n",
"wandb: Agent Starting Run: 3mgs8xbf with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 2\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
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{
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" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/3mgs8xbf
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"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 2\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 2\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 2\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 2\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
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" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"13.498512089252472\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"1.0383470837886517\n",
"The running loss is:\n",
"25.564792200922966\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"1.9665224769940743\n",
"The running loss is:\n",
"22.65778923034668\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"1.7429068638728216\n",
"The running loss is:\n",
"14.94919142127037\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"1.1499378016361823\n",
"The running loss is:\n",
"13.298549711704254\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 4\n",
"1.0229653624387889\n",
"The running loss is:\n",
"10.945579677820206\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.8419676675246313\n",
"The running loss is:\n",
"10.539850123226643\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"0.8107577017866648\n",
"The running loss is:\n",
"10.23940223455429\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.7876463257349454\n",
"The running loss is:\n",
"9.733535498380661\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.7487334998754355\n",
"The running loss is:\n",
"8.944746106863022\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.6880573928356171\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 2, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 10.021401\n",
"48 30755 ... 11.561892\n",
"49 30756 ... 12.308455\n",
"50 30757 ... 12.756186\n",
"51 30758 ... 12.854743\n",
"52 30759 ... 12.682150\n",
"53 30760 ... 12.287163\n",
"54 30761 ... 13.468019\n",
"55 30762 ... 14.454829\n",
"56 30763 ... 15.026141\n",
"\n",
"[12 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 3mgs8xbf \n",
"\n",
"wandb: Agent Starting Run: nihnfer9 with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 2\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: nihnfer9\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/nihnfer9
\n",
" "
],
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""
]
},
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 2\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 2\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 2\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
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" seq_len: 2\n",
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" desc: null\n",
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"training_params:\n",
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" batch_size: 3\n",
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" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"51.30401501059532\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 0\n",
"3.6645725007568086\n",
"The running loss is:\n",
"28.13227316737175\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 1\n",
"2.0094480833836963\n",
"The running loss is:\n",
"30.677978098392487\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 2\n",
"2.1912841498851776\n",
"The running loss is:\n",
"25.798474550247192\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 3\n",
"1.8427481821605138\n",
"The running loss is:\n",
"23.53739532828331\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 4\n",
"1.6812425234488078\n",
"The running loss is:\n",
"12.46931640803814\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 5\n",
"0.89066545771701\n",
"The running loss is:\n",
"14.836411327123642\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 6\n",
"1.0597436662231172\n",
"The running loss is:\n",
"11.940000280737877\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 7\n",
"0.8528571629098484\n",
"The running loss is:\n",
"9.431063748896122\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 8\n",
"0.6736474106354373\n",
"The running loss is:\n",
"9.614306479692459\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 9\n",
"0.68673617712089\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 2, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 11.500200\n",
"48 30755 ... 13.090182\n",
"49 30756 ... 12.382077\n",
"50 30757 ... 12.541276\n",
"51 30758 ... 11.883831\n",
"52 30759 ... 11.478168\n",
"53 30760 ... 10.748770\n",
"54 30761 ... 11.050783\n",
"55 30762 ... 12.022332\n",
"56 30763 ... 11.973404\n",
"\n",
"[12 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: nihnfer9 \n",
"\n",
"wandb: Agent Starting Run: ionv873k with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 2\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: ionv873k\n"
],
"name": "stdout"
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{
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"data": {
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"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/ionv873k
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
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" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
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"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
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" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 2\n",
"forward_params:\n",
" desc: null\n",
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" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 2\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 2\n",
" number_time_series: 3\n",
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" seq_len: 2\n",
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" desc: null\n",
" value: PyTorch\n",
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" value: Adam\n",
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" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"33.80015930533409\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 0\n",
"2.4142970932381496\n",
"The running loss is:\n",
"21.325599938631058\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 1\n",
"1.523257138473647\n",
"The running loss is:\n",
"18.091121673583984\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 2\n",
"1.2922229766845703\n",
"The running loss is:\n",
"27.904833287000656\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 3\n",
"1.993202377642904\n",
"The running loss is:\n",
"19.25467175245285\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 4\n",
"1.375333696603775\n",
"The running loss is:\n",
"17.12490466237068\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 5\n",
"1.2232074758836202\n",
"The running loss is:\n",
"13.32920789718628\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 6\n",
"0.9520862783704486\n",
"The running loss is:\n",
"13.500364929437637\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 7\n",
"0.9643117806741169\n",
"The running loss is:\n",
"13.285066820681095\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 8\n",
"0.9489333443343639\n",
"The running loss is:\n",
"12.104208245873451\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 9\n",
"0.8645863032766751\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 2, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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{
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
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{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
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{
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"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"45 30752 ... 0.000000\n",
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"51 30758 ... 8.870846\n",
"52 30759 ... 8.580363\n",
"53 30760 ... 8.285401\n",
"54 30761 ... 7.854644\n",
"55 30762 ... 9.419525\n",
"56 30763 ... 9.371837\n",
"\n",
"[12 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: ionv873k \n",
"\n",
"wandb: Agent Starting Run: oe5h8j48 with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 2\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: oe5h8j48\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/oe5h8j48
\n",
" "
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""
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 2\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
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" - month\n",
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" scaler: StandardScaler\n",
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" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 2\n",
"forward_params:\n",
" desc: null\n",
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" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 2\n",
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" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
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"sweep:\n",
" desc: null\n",
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" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"36.88397306203842\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"2.837228697079879\n",
"The running loss is:\n",
"23.387097895145416\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"1.7990075303958013\n",
"The running loss is:\n",
"20.17457577586174\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"1.551890444297057\n",
"The running loss is:\n",
"20.294566094875336\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"1.5611204688365643\n",
"The running loss is:\n",
"18.586155623197556\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 4\n",
"1.4297042787075043\n",
"The running loss is:\n",
"13.293670758605003\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"1.0225900583542311\n",
"The running loss is:\n",
"13.621711760759354\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"1.0478239815968733\n",
"The running loss is:\n",
"10.410593956708908\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.800814919746839\n",
"The running loss is:\n",
"10.608880147337914\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.8160677036413779\n",
"The running loss is:\n",
"9.719066202640533\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.7476204771261948\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 2, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 10.146037\n",
"48 30755 ... 13.109223\n",
"49 30756 ... 13.432909\n",
"50 30757 ... 13.972692\n",
"51 30758 ... 13.988523\n",
"52 30759 ... 13.896473\n",
"53 30760 ... 13.568353\n",
"54 30761 ... 12.816897\n",
"55 30762 ... 14.419169\n",
"56 30763 ... 14.700335\n",
"\n",
"[12 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: oe5h8j48 \n",
"\n",
"wandb: Agent Starting Run: uz0dql7o with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 3\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: uz0dql7o\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/uz0dql7o
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 3\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 3\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 3\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
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" value:\n",
" forecast_length: 1\n",
" number_time_series: 3\n",
" output_seq_len: 1\n",
" seq_len: 3\n",
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" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
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" desc: null\n",
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"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"10.755451019853354\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 0\n",
"0.7682465014180967\n",
"The running loss is:\n",
"38.836746633052826\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 1\n",
"2.7740533309323445\n",
"The running loss is:\n",
"11.501722127199173\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 2\n",
"0.8215515805142266\n",
"The running loss is:\n",
"10.499587520956993\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 3\n",
"0.7499705372112138\n",
"The running loss is:\n",
"8.515039145946503\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 4\n",
"0.6082170818533216\n",
"The running loss is:\n",
"8.96797063946724\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 5\n",
"0.6405693313905171\n",
"The running loss is:\n",
"7.806724339723587\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 6\n",
"0.5576231671231133\n",
"The running loss is:\n",
"7.387755490839481\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 7\n",
"0.5276968207742486\n",
"The running loss is:\n",
"7.427955038845539\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 8\n",
"0.5305682170603957\n",
"The running loss is:\n",
"7.187168009579182\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 9\n",
"0.5133691435413701\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 3, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
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},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 8.769258\n",
"48 30755 ... 10.274848\n",
"49 30756 ... 17.754297\n",
"50 30757 ... 16.682022\n",
"51 30758 ... 15.986617\n",
"52 30759 ... 15.547783\n",
"53 30760 ... 12.919273\n",
"54 30761 ... 15.504961\n",
"55 30762 ... 17.572283\n",
"56 30763 ... 21.066988\n",
"\n",
"[13 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: uz0dql7o \n",
"\n",
"wandb: Agent Starting Run: imlwhsva with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 3\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: imlwhsva\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/imlwhsva
\n",
" "
],
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""
]
},
"metadata": {
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}
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{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 3\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 3\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
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" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 3\n",
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" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
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"sweep:\n",
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" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"16.53025685250759\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"1.2715582194236608\n",
"The running loss is:\n",
"16.255148097872734\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"1.2503960075286717\n",
"The running loss is:\n",
"10.766040947288275\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"0.8281569959452519\n",
"The running loss is:\n",
"9.744163434952497\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"0.7495510334578844\n",
"The running loss is:\n",
"9.72730216011405\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 4\n",
"0.7482540123164654\n",
"The running loss is:\n",
"9.620016269385815\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.7400012514912165\n",
"The running loss is:\n",
"9.431224629282951\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"0.72547881763715\n",
"The running loss is:\n",
"9.202248107641935\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.7078652390493796\n",
"The running loss is:\n",
"9.111172825098038\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.7008594480844644\n",
"The running loss is:\n",
"7.962752666324377\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.6125194358711059\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 3, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
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"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
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"47 30754 ... 9.158216\n",
"48 30755 ... 10.707749\n",
"49 30756 ... 15.812157\n",
"50 30757 ... 15.918945\n",
"51 30758 ... 16.698002\n",
"52 30759 ... 17.599003\n",
"53 30760 ... 16.707861\n",
"54 30761 ... 19.135910\n",
"55 30762 ... 21.531374\n",
"56 30763 ... 25.614202\n",
"\n",
"[13 rows x 32 columns]\n"
],
"name": "stdout"
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: imlwhsva \n",
"\n",
"wandb: Agent Starting Run: 6s6mkjgq with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 3\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: 6s6mkjgq\n"
],
"name": "stdout"
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{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/6s6mkjgq
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
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" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
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" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 3\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 3\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 3\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
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" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
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" value: MultiAttnHeadSimple\n",
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" forecast_length: 3\n",
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" output_seq_len: 3\n",
" seq_len: 3\n",
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" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
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" desc: null\n",
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"sweep:\n",
" desc: null\n",
" value: true\n",
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" criterion: MSE\n",
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" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"14.457125097513199\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"1.1120865459625537\n",
"The running loss is:\n",
"16.085287496447563\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"1.2373298074190433\n",
"The running loss is:\n",
"10.15951931476593\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"0.7815014857512254\n",
"The running loss is:\n",
"9.465455561876297\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"0.7281119662981766\n",
"The running loss is:\n",
"9.188641458749771\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 4\n",
"0.7068185737499824\n",
"The running loss is:\n",
"8.755524381995201\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.6735018755380924\n",
"The running loss is:\n",
"8.427750319242477\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"0.6482884860955752\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"\u001b[34m\u001b[1mwandb\u001b[0m: Network error resolved after 0:00:11.182615, resuming normal operation.\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"The running loss is:\n",
"7.923837661743164\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.6095259739802434\n",
"The running loss is:\n",
"8.0590850263834\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.6199296174141077\n",
"The running loss is:\n",
"8.314335748553276\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.639564288350252\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 3, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 7.424254\n",
"48 30755 ... 7.630701\n",
"49 30756 ... 9.997432\n",
"50 30757 ... 9.401261\n",
"51 30758 ... 8.641278\n",
"52 30759 ... 7.329124\n",
"53 30760 ... 4.651038\n",
"54 30761 ... 5.290149\n",
"55 30762 ... 4.552412\n",
"56 30763 ... 5.032251\n",
"\n",
"[13 rows x 32 columns]\n"
],
"name": "stdout"
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{
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"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 6s6mkjgq \n",
"\n",
"wandb: Agent Starting Run: l03hgmub with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 3\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: l03hgmub\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/l03hgmub
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
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" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 3\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 3\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
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" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
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" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
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" forecast_length: 1\n",
" number_time_series: 3\n",
" output_seq_len: 1\n",
" seq_len: 3\n",
"model_type:\n",
" desc: null\n",
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"optimizer:\n",
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" desc: null\n",
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"sweep:\n",
" desc: null\n",
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" criterion: MSE\n",
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" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"10.75971208512783\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 0\n",
"0.7685508632234165\n",
"The running loss is:\n",
"36.87247994542122\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 1\n",
"2.633748567530087\n",
"The running loss is:\n",
"17.486398860812187\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 2\n",
"1.2490284900580133\n",
"The running loss is:\n",
"15.61052069067955\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 3\n",
"1.1150371921913964\n",
"The running loss is:\n",
"11.076192826032639\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 4\n",
"0.7911566304309028\n",
"The running loss is:\n",
"8.441155915148556\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 5\n",
"0.6029397082248968\n",
"The running loss is:\n",
"7.802495114505291\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 6\n",
"0.5573210796075208\n",
"The running loss is:\n",
"7.1354983150959015\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 7\n",
"0.5096784510782787\n",
"The running loss is:\n",
"7.774059057235718\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 8\n",
"0.5552899326596942\n",
"The running loss is:\n",
"6.861661870032549\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 9\n",
"0.4901187050023249\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 3, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 9.290727\n",
"48 30755 ... 10.207885\n",
"49 30756 ... 18.020309\n",
"50 30757 ... 17.071165\n",
"51 30758 ... 16.314606\n",
"52 30759 ... 16.627880\n",
"53 30760 ... 14.441933\n",
"54 30761 ... 18.675493\n",
"55 30762 ... 21.162457\n",
"56 30763 ... 22.604240\n",
"\n",
"[13 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: l03hgmub \n",
"\n",
"wandb: Agent Starting Run: c9c5e13j with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 3\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: c9c5e13j\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/c9c5e13j
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 3\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 3\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 3\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 2\n",
" number_time_series: 3\n",
" output_seq_len: 2\n",
" seq_len: 3\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 2\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"12.687808863818645\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"0.9759852972168189\n",
"The running loss is:\n",
"30.817717105150223\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"2.370593623473094\n",
"The running loss is:\n",
"15.852080255746841\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"1.219390788903603\n",
"The running loss is:\n",
"13.337770016863942\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"1.025982308989534\n",
"The running loss is:\n",
"11.452782481908798\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 4\n",
"0.8809832678391383\n",
"The running loss is:\n",
"10.242657408118248\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.7878967237014037\n",
"The running loss is:\n",
"9.236272256821394\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"0.7104824812939534\n",
"The running loss is:\n",
"9.14104574918747\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.703157365322113\n",
"The running loss is:\n",
"8.3548953384161\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.6426842568012384\n",
"The running loss is:\n",
"8.045029904693365\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.6188484542071819\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 3, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 8.374634\n",
"48 30755 ... 8.578894\n",
"49 30756 ... 12.920104\n",
"50 30757 ... 13.142343\n",
"51 30758 ... 13.096810\n",
"52 30759 ... 13.633474\n",
"53 30760 ... 12.822398\n",
"54 30761 ... 13.097551\n",
"55 30762 ... 13.966360\n",
"56 30763 ... 17.648935\n",
"\n",
"[13 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: c9c5e13j \n",
"\n",
"wandb: Agent Starting Run: axwlbwqd with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 3\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: axwlbwqd\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/axwlbwqd
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 3\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 3\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 3\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 3\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"11.29591067135334\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"0.8689162054887185\n",
"The running loss is:\n",
"31.16746847331524\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"2.397497574870403\n",
"The running loss is:\n",
"13.213620707392693\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"1.0164323621071303\n",
"The running loss is:\n",
"12.236616969108582\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"0.9412782283929678\n",
"The running loss is:\n",
"10.079297959804535\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 4\n",
"0.7753306122926565\n",
"The running loss is:\n",
"9.156161159276962\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.704320089175151\n",
"The running loss is:\n",
"8.367442056536674\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"0.6436493889643595\n",
"The running loss is:\n",
"7.782520815730095\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.5986554473638535\n",
"The running loss is:\n",
"7.92472417652607\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.6095941674250823\n",
"The running loss is:\n",
"7.543179780244827\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.5802445984803714\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 3, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
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{
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
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{
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"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
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"51 30758 ... 5.768365\n",
"52 30759 ... 3.849137\n",
"53 30760 ... 0.948829\n",
"54 30761 ... 1.004140\n",
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"56 30763 ... -0.856214\n",
"\n",
"[13 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: axwlbwqd \n",
"\n",
"wandb: Agent Starting Run: bngef59s with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 3\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: bngef59s\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/bngef59s
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
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" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
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" class: default\n",
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" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
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" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 3\n",
"forward_params:\n",
" desc: null\n",
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" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 3\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 1\n",
" number_time_series: 3\n",
" output_seq_len: 1\n",
" seq_len: 3\n",
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" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
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" criterion: MSE\n",
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" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"22.474827259778976\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 0\n",
"1.605344804269927\n",
"The running loss is:\n",
"25.603744968771935\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 1\n",
"1.8288389263408524\n",
"The running loss is:\n",
"23.369097493588924\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 2\n",
"1.669221249542066\n",
"The running loss is:\n",
"17.44265967607498\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 3\n",
"1.2459042625767844\n",
"The running loss is:\n",
"12.164395917207003\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 4\n",
"0.868885422657643\n",
"The running loss is:\n",
"12.119173973798752\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 5\n",
"0.865655283842768\n",
"The running loss is:\n",
"9.556369185447693\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 6\n",
"0.6825977989605495\n",
"The running loss is:\n",
"9.649928107857704\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 7\n",
"0.6892805791326931\n",
"The running loss is:\n",
"11.666721649467945\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 8\n",
"0.8333372606762818\n",
"The running loss is:\n",
"8.00122594833374\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 9\n",
"0.5715161391666957\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 3, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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{
"output_type": "stream",
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 13.312113\n",
"48 30755 ... 15.524620\n",
"49 30756 ... 21.541870\n",
"50 30757 ... 20.370146\n",
"51 30758 ... 19.467724\n",
"52 30759 ... 19.207888\n",
"53 30760 ... 16.430124\n",
"54 30761 ... 22.729057\n",
"55 30762 ... 23.434126\n",
"56 30763 ... 24.633392\n",
"\n",
"[13 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: bngef59s \n",
"\n",
"wandb: Agent Starting Run: nsmc9ilv with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 3\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: nsmc9ilv\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/nsmc9ilv
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" "
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""
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 3\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
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" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 3\n",
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" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
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" relevant_cols:\n",
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" - month\n",
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" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
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" - MSE\n",
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" value: MultiAttnHeadSimple\n",
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" seq_len: 3\n",
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" desc: null\n",
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" desc: null\n",
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"sweep:\n",
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" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"15.707977592945099\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"1.2083059686880846\n",
"The running loss is:\n",
"19.711661607492715\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"1.5162816621148243\n",
"The running loss is:\n",
"20.035046309232712\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"1.5411574084025164\n",
"The running loss is:\n",
"15.251697435975075\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"1.1732074950750058\n",
"The running loss is:\n",
"11.459911532700062\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 4\n",
"0.8815316563615432\n",
"The running loss is:\n",
"9.84505944699049\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.7573122651531146\n",
"The running loss is:\n",
"9.718630462884903\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"0.747586958683454\n",
"The running loss is:\n",
"8.777115888893604\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.6751627606841234\n",
"The running loss is:\n",
"9.399527624249458\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.7230405864807276\n",
"The running loss is:\n",
"9.292045809328556\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.7147727545637351\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 3, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 9.226769\n",
"48 30755 ... 9.470608\n",
"49 30756 ... 9.915501\n",
"50 30757 ... 9.908090\n",
"51 30758 ... 9.937128\n",
"52 30759 ... 10.003601\n",
"53 30760 ... 10.060073\n",
"54 30761 ... 9.755686\n",
"55 30762 ... 9.939466\n",
"56 30763 ... 10.018828\n",
"\n",
"[13 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: nsmc9ilv \n",
"\n",
"wandb: Agent Starting Run: ifw0p83l with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 3\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: ifw0p83l\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/ifw0p83l
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 3\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 3\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 3\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 3\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"12.531682252883911\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"0.963975557914147\n",
"The running loss is:\n",
"20.678108781576157\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"1.590623752428935\n",
"The running loss is:\n",
"20.66189543902874\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"1.58937657223298\n",
"The running loss is:\n",
"15.72855657339096\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"1.2098889671839201\n",
"The running loss is:\n",
"11.498915523290634\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 4\n",
"0.8845319633300488\n",
"The running loss is:\n",
"10.46013493835926\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.8046257644891739\n",
"The running loss is:\n",
"9.681835949420929\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"0.7447566114939176\n",
"The running loss is:\n",
"8.949368417263031\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.6884129551740793\n",
"The running loss is:\n",
"8.690906845033169\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.6685312957717822\n",
"The running loss is:\n",
"9.19144169986248\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.7070339769124985\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 3, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 9.390057\n",
"48 30755 ... 9.157915\n",
"49 30756 ... 11.250272\n",
"50 30757 ... 11.213902\n",
"51 30758 ... 10.737865\n",
"52 30759 ... 10.233933\n",
"53 30760 ... 9.121439\n",
"54 30761 ... 10.235040\n",
"55 30762 ... 9.953352\n",
"56 30763 ... 10.905466\n",
"\n",
"[13 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: ifw0p83l \n",
"\n",
"wandb: Agent Starting Run: ipvidfam with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 3\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: ipvidfam\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/ipvidfam
\n",
" "
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""
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 3\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 3\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 3\n",
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" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
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" value:\n",
" forecast_length: 1\n",
" number_time_series: 3\n",
" output_seq_len: 1\n",
" seq_len: 3\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 1\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
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" desc: null\n",
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" batch_size: 3\n",
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" epochs: 10\n",
" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"119.7130461782217\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 0\n",
"8.55093186987298\n",
"The running loss is:\n",
"55.55126856267452\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 1\n",
"3.9679477544767514\n",
"The running loss is:\n",
"24.79954195022583\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 2\n",
"1.7713958535875594\n",
"The running loss is:\n",
"29.550060272216797\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 3\n",
"2.1107185908726285\n",
"The running loss is:\n",
"34.141096126288176\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 4\n",
"2.4386497233062983\n",
"The running loss is:\n",
"19.86576085537672\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 5\n",
"1.4189829182411944\n",
"The running loss is:\n",
"12.140714094042778\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 6\n",
"0.8671938638601985\n",
"The running loss is:\n",
"10.807734534144402\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 7\n",
"0.7719810381531715\n",
"The running loss is:\n",
"8.74726428091526\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 8\n",
"0.6248045914939472\n",
"The running loss is:\n",
"8.744693741202354\n",
"The number of items in train is: \n",
"14\n",
"The loss for epoch 9\n",
"0.6246209815144539\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 3, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
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"47 30754 ... 11.098480\n",
"48 30755 ... 11.234056\n",
"49 30756 ... 16.740345\n",
"50 30757 ... 15.662832\n",
"51 30758 ... 13.948870\n",
"52 30759 ... 13.708152\n",
"53 30760 ... 11.351399\n",
"54 30761 ... 11.689322\n",
"55 30762 ... 11.627025\n",
"56 30763 ... 16.219433\n",
"\n",
"[13 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: ipvidfam \n",
"\n",
"wandb: Agent Starting Run: vol92wf7 with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 3\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: vol92wf7\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/vol92wf7
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
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" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 3\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 3\n",
"forward_params:\n",
" desc: null\n",
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" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 3\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
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" value: MultiAttnHeadSimple\n",
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" seq_len: 3\n",
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" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"60.953131318092346\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"4.688702409084026\n",
"The running loss is:\n",
"35.30423188209534\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"2.7157101447765646\n",
"The running loss is:\n",
"17.126852050423622\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"1.317450157724894\n",
"The running loss is:\n",
"29.961639672517776\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"2.3047415132705984\n",
"The running loss is:\n",
"28.83660078048706\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 4\n",
"2.218200060037466\n",
"The running loss is:\n",
"13.997964818030596\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"1.076766524463892\n",
"The running loss is:\n",
"13.703625090420246\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"1.0541250069554036\n",
"The running loss is:\n",
"14.603826694190502\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"1.1233712841685002\n",
"The running loss is:\n",
"12.683620244264603\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.9756630957126617\n",
"The running loss is:\n",
"11.017892237752676\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.8475301721348212\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 3, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 8.601355\n",
"48 30755 ... 8.784111\n",
"49 30756 ... 14.580492\n",
"50 30757 ... 13.166733\n",
"51 30758 ... 11.297988\n",
"52 30759 ... 10.419773\n",
"53 30760 ... 8.309337\n",
"54 30761 ... 8.855109\n",
"55 30762 ... 9.287474\n",
"56 30763 ... 13.585121\n",
"\n",
"[13 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: vol92wf7 \n",
"\n",
"wandb: Agent Starting Run: ui1q5amn with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 3\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: ui1q5amn\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/ui1q5amn
\n",
" "
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""
]
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{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 3\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 3\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
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" decoder_params:\n",
" decoder_function: simple_decode\n",
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"Torch is using cpu\n",
"The running loss is:\n",
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"13\n",
"The loss for epoch 0\n",
"3.3131132813600392\n",
"The running loss is:\n",
"24.968651235103607\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"1.9206654796233544\n",
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"19.673025608062744\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"1.5133096621586726\n",
"The running loss is:\n",
"15.400908634066582\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"1.1846852795435832\n",
"The running loss is:\n",
"13.345179736614227\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 4\n",
"1.0265522874318636\n",
"The running loss is:\n",
"12.23420536518097\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.9410927203985361\n",
"The running loss is:\n",
"12.980785593390465\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"0.9985219687223434\n",
"The running loss is:\n",
"11.168275743722916\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.859098134132532\n",
"The running loss is:\n",
"10.740023881196976\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.8261556831689981\n",
"The running loss is:\n",
"10.570404797792435\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.8131080613686488\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 3, 3])\n",
"Add debugging crap below\n"
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"name": "stdout"
},
{
"output_type": "stream",
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"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
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"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
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{
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"torch.Size([10])\n",
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"Un-transforming data\n"
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{
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"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
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{
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"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"52 30759 ... 13.362471\n",
"53 30760 ... 11.854248\n",
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"55 30762 ... 13.206392\n",
"56 30763 ... 15.721452\n",
"\n",
"[13 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
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{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: ui1q5amn \n",
"\n",
"wandb: Agent Starting Run: 1godljqj with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 4\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
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],
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{
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"data": {
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"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
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"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
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"batch_size:\n",
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" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
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" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
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" desc: null\n",
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" optimizer: Adam\n",
"wandb:\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
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"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"1.1683034564440067\n",
"The running loss is:\n",
"12.53387589007616\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"0.9641442992366277\n",
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"8.774933334439993\n",
"The number of items in train is: \n",
"13\n",
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"0.6749948718799994\n",
"The running loss is:\n",
"7.201144218444824\n",
"The number of items in train is: \n",
"13\n",
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"0.5539341706496018\n",
"The running loss is:\n",
"7.156394409015775\n",
"The number of items in train is: \n",
"13\n",
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"0.550491877616598\n",
"The running loss is:\n",
"6.275515090674162\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.4827319300518586\n",
"The running loss is:\n",
"6.67833286896348\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"0.5137179129971907\n",
"The running loss is:\n",
"5.711407098919153\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.4393390076091656\n",
"The running loss is:\n",
"5.9839532896876335\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.46030409920674104\n",
"The running loss is:\n",
"6.153777305036783\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.4733674850028295\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 4, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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{
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"test_data scale\n",
"Un-transforming data\n"
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{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
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{
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"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
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"47 30754 ... 7.458205\n",
"48 30755 ... 7.137259\n",
"49 30756 ... 8.528614\n",
"50 30757 ... 8.608210\n",
"51 30758 ... 8.303369\n",
"52 30759 ... 7.806078\n",
"53 30760 ... 7.328808\n",
"54 30761 ... 5.026564\n",
"55 30762 ... 6.488012\n",
"56 30763 ... 8.036192\n",
"\n",
"[14 rows x 32 columns]\n"
],
"name": "stdout"
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{
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"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
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"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
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{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 1godljqj \n",
"\n",
"wandb: Agent Starting Run: ptu5e09p with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 4\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: ptu5e09p\n"
],
"name": "stdout"
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{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/ptu5e09p
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
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" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"17.338553577661514\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"1.3337348905893474\n",
"The running loss is:\n",
"12.01589360833168\n",
"The number of items in train is: \n",
"13\n",
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"0.9242995083332062\n",
"The running loss is:\n",
"9.383199691772461\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"0.7217845916748047\n",
"The running loss is:\n",
"7.883500777184963\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"0.6064231367065356\n",
"The running loss is:\n",
"7.181640453636646\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 4\n",
"0.5524338810489728\n",
"The running loss is:\n",
"7.315292157232761\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.562714781325597\n",
"The running loss is:\n",
"6.892123244702816\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"0.5301633265156013\n",
"The running loss is:\n",
"6.666610881686211\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.5128162216681701\n",
"The running loss is:\n",
"6.246898893266916\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.4805306840974551\n",
"The running loss is:\n",
"6.445175599306822\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.49578273840821707\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 4, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"51 30758 ... 10.124650\n",
"52 30759 ... 10.684422\n",
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"54 30761 ... 12.109084\n",
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"\n",
"[14 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: ptu5e09p \n",
"\n",
"wandb: Agent Starting Run: 1bn7u6ek with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 4\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
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],
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{
"output_type": "display_data",
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" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
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"_wandb:\n",
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" batch_size: 3\n",
" class: default\n",
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" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
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" scaler: StandardScaler\n",
" target_col:\n",
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" training_path: Colorado_Douglas County.csv\n",
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" file_path: Colorado_Douglas County.csv\n",
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" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
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"\n",
"Torch is using cpu\n",
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"The number of items in train is: \n",
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"The loss for epoch 0\n",
"1.2689327047421382\n",
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"The number of items in train is: \n",
"13\n",
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"1.0934484417621906\n",
"The running loss is:\n",
"10.41348597407341\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"0.8010373826210315\n",
"The running loss is:\n",
"9.035328388214111\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"0.6950252606318548\n",
"The running loss is:\n",
"8.10020449757576\n",
"The number of items in train is: \n",
"13\n",
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"0.6230926536596738\n",
"The running loss is:\n",
"8.421209901571274\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.6477853770439441\n",
"The running loss is:\n",
"7.663483992218971\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"0.5894987686322286\n",
"The running loss is:\n",
"8.22572796791792\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.6327483052244554\n",
"The running loss is:\n",
"7.9032817631959915\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.6079447510150763\n",
"The running loss is:\n",
"7.974031358957291\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.6133870276120993\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 4, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 11.992487\n",
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"50 30757 ... 13.786767\n",
"51 30758 ... 14.966878\n",
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"54 30761 ... 18.917545\n",
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"56 30763 ... 19.971638\n",
"\n",
"[14 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 1bn7u6ek \n",
"\n",
"wandb: Agent Starting Run: utturoc5 with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 4\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
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" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
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"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
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" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 4\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 4\n",
"forward_params:\n",
" desc: null\n",
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" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 4\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
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" seq_len: 4\n",
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" desc: null\n",
" value: PyTorch\n",
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" desc: null\n",
" value: Adam\n",
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" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"11.249525194987655\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"0.8653480919221272\n",
"The running loss is:\n",
"30.46081379801035\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"2.343139522923873\n",
"The running loss is:\n",
"9.777215026319027\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"0.7520934635630021\n",
"The running loss is:\n",
"10.099652647972107\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"0.7768963575363159\n",
"The running loss is:\n",
"7.714620653539896\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 4\n",
"0.5934323579646074\n",
"The running loss is:\n",
"6.230708753690124\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.4792852887453941\n",
"The running loss is:\n",
"6.548743784427643\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"0.5037495218790494\n",
"The running loss is:\n",
"5.332755489274859\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.41021196071345073\n",
"The running loss is:\n",
"5.4890450509265065\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.42223423468665433\n",
"The running loss is:\n",
"6.13737740367651\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.4721059541289623\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 4, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
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"46 30753 ... 0.000000\n",
"47 30754 ... 9.758069\n",
"48 30755 ... 10.323517\n",
"49 30756 ... 11.307789\n",
"50 30757 ... 10.594126\n",
"51 30758 ... 10.666987\n",
"52 30759 ... 11.087155\n",
"53 30760 ... 11.666491\n",
"54 30761 ... 10.458287\n",
"55 30762 ... 12.071755\n",
"56 30763 ... 13.168046\n",
"\n",
"[14 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: utturoc5 \n",
"\n",
"wandb: Agent Starting Run: nvxoca53 with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 4\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: nvxoca53\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/nvxoca53
\n",
" "
],
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""
]
},
"metadata": {
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}
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 4\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 4\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 4\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
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" seq_len: 4\n",
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" desc: null\n",
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"sweep:\n",
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" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"14.307263173162937\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"1.1005587056279182\n",
"The running loss is:\n",
"26.481370121240616\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"2.0370284708646627\n",
"The running loss is:\n",
"10.21297961473465\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"0.78561381651805\n",
"The running loss is:\n",
"9.383397921919823\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"0.7217998401476786\n",
"The running loss is:\n",
"7.646930389106274\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 4\n",
"0.5882254145466365\n",
"The running loss is:\n",
"7.441839635372162\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.5724492027209356\n",
"The running loss is:\n",
"7.128525517880917\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"0.5483481167600706\n",
"The running loss is:\n",
"6.7704630345106125\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.5208048488085086\n",
"The running loss is:\n",
"6.290463771671057\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.4838818285900813\n",
"The running loss is:\n",
"6.040915712714195\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.4646858240549381\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 4, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 11.632046\n",
"48 30755 ... 10.507959\n",
"49 30756 ... 9.999850\n",
"50 30757 ... 11.279503\n",
"51 30758 ... 11.918778\n",
"52 30759 ... 12.729056\n",
"53 30760 ... 13.610320\n",
"54 30761 ... 15.292119\n",
"55 30762 ... 14.556417\n",
"56 30763 ... 14.570903\n",
"\n",
"[14 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: nvxoca53 \n",
"\n",
"wandb: Agent Starting Run: bqts5xmo with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 4\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: bqts5xmo\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/bqts5xmo
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 4\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 4\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 4\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 4\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
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" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"12.725847855210304\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"0.9789113734777157\n",
"The running loss is:\n",
"30.892170883715153\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"2.376320837208858\n",
"The running loss is:\n",
"13.146855235099792\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"1.0112965565461378\n",
"The running loss is:\n",
"12.148904085159302\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"0.9345310834737924\n",
"The running loss is:\n",
"9.722107946872711\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 4\n",
"0.7478544574517471\n",
"The running loss is:\n",
"9.249086931347847\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.7114682254882959\n",
"The running loss is:\n",
"8.29569448530674\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"0.6381303450235953\n",
"The running loss is:\n",
"8.795628726482391\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.6765868251140301\n",
"The running loss is:\n",
"8.55500802397728\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.6580775403059446\n",
"The running loss is:\n",
"8.533968634903431\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.6564591257618024\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 4, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
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{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
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"47 30754 ... 11.248339\n",
"48 30755 ... 11.703672\n",
"49 30756 ... 12.366732\n",
"50 30757 ... 12.580591\n",
"51 30758 ... 13.153063\n",
"52 30759 ... 13.921073\n",
"53 30760 ... 14.727524\n",
"54 30761 ... 14.668133\n",
"55 30762 ... 15.302679\n",
"56 30763 ... 15.801561\n",
"\n",
"[14 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: bqts5xmo \n",
"\n",
"wandb: Agent Starting Run: 97en7jps with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 4\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: 97en7jps\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/97en7jps
\n",
" "
],
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""
]
},
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 4\n",
" forecast_length: 1\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
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" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 4\n",
"forward_params:\n",
" desc: null\n",
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"inference_params:\n",
" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 4\n",
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" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
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"sweep:\n",
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" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"11.382418245077133\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"0.8755706342367026\n",
"The running loss is:\n",
"23.412592843174934\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"1.8009686802442257\n",
"The running loss is:\n",
"17.038911778479815\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"1.3106855214215243\n",
"The running loss is:\n",
"10.114607397466898\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"0.7780467228820691\n",
"The running loss is:\n",
"9.873054258525372\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 4\n",
"0.7594657121942594\n",
"The running loss is:\n",
"6.991059593856335\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.5377738149120257\n",
"The running loss is:\n",
"7.195119507610798\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"0.5534707313546767\n",
"The running loss is:\n",
"8.087266314774752\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.622097408828827\n",
"The running loss is:\n",
"6.980310961604118\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.5369469970464706\n",
"The running loss is:\n",
"8.746676992624998\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.6728213071249999\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 4, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
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"\n",
"[14 rows x 32 columns]\n"
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"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
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{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 97en7jps \n",
"\n",
"wandb: Agent Starting Run: mqseoc3o with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 4\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: mqseoc3o\n"
],
"name": "stdout"
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{
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"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/mqseoc3o
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"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
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" framework: torch\n",
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" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
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" desc: null\n",
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" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 4\n",
"forward_params:\n",
" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 4\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
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" desc: null\n",
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" - MSE\n",
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" desc: null\n",
" value: MultiAttnHeadSimple\n",
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" seq_len: 4\n",
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" value: PyTorch\n",
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" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"11.85589762032032\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"0.9119921246400247\n",
"The running loss is:\n",
"23.438958287239075\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"1.8029967913260827\n",
"The running loss is:\n",
"16.074821338057518\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"1.2365247183121169\n",
"The running loss is:\n",
"10.657343104481697\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"0.819795623421669\n",
"The running loss is:\n",
"11.378557436168194\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 4\n",
"0.8752736489360149\n",
"The running loss is:\n",
"10.08240570127964\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.7755696693292031\n",
"The running loss is:\n",
"9.281341701745987\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"0.7139493616727682\n",
"The running loss is:\n",
"9.217081643640995\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.7090062802800765\n",
"The running loss is:\n",
"8.837434470653534\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.6798026515887334\n",
"The running loss is:\n",
"8.208003804087639\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.6313849080067414\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 4, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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{
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
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"Current historical dataframe\n",
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"52 30759 ... 13.034577\n",
"53 30760 ... 13.474689\n",
"54 30761 ... 14.320210\n",
"55 30762 ... 14.396397\n",
"56 30763 ... 14.574674\n",
"\n",
"[14 rows x 32 columns]\n"
],
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"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
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{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: mqseoc3o \n",
"\n",
"wandb: Agent Starting Run: pfd9jj82 with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 4\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: pfd9jj82\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/pfd9jj82
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
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"dataset_params:\n",
" desc: null\n",
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" batch_size: 3\n",
" class: default\n",
" forecast_history: 4\n",
" forecast_length: 3\n",
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" relevant_cols:\n",
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" - month\n",
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" scaler: StandardScaler\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
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" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
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"forward_params:\n",
" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 4\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
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" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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" desc: null\n",
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" - MSE\n",
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"sweep:\n",
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" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"10.825587838888168\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"0.8327375260683206\n",
"The running loss is:\n",
"28.150420397520065\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"2.1654169536553898\n",
"The running loss is:\n",
"20.6149685382843\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"1.585766810637254\n",
"The running loss is:\n",
"11.813875526189804\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"0.9087596558607541\n",
"The running loss is:\n",
"12.213937133550644\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 4\n",
"0.9395336256577418\n",
"The running loss is:\n",
"11.47781416773796\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.8829087821336893\n",
"The running loss is:\n",
"10.867890685796738\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"0.8359915912151337\n",
"The running loss is:\n",
"10.418911457061768\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.8014547274662898\n",
"The running loss is:\n",
"9.896387428045273\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.7612605713880979\n",
"The running loss is:\n",
"9.135141223669052\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.7027031710514655\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 4, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
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"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
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"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
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"name": "stderr"
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"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"52 30759 ... 9.942549\n",
"53 30760 ... 10.416265\n",
"54 30761 ... 6.991664\n",
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"56 30763 ... 9.746800\n",
"\n",
"[14 rows x 32 columns]\n"
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"name": "stdout"
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"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
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"name": "stderr"
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{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: pfd9jj82 \n",
"\n",
"wandb: Agent Starting Run: vz7xqs63 with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 4\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
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"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/vz7xqs63
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"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
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" framework: torch\n",
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" python_version: 3.6.9\n",
"batch_size:\n",
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" training_path: Colorado_Douglas County.csv\n",
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" file_path: Colorado_Douglas County.csv\n",
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" relevant_cols:\n",
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" - month\n",
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" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
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" desc: null\n",
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" seq_len: 4\n",
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" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"46.30128153041005\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"3.561637040800773\n",
"The running loss is:\n",
"24.802572248037905\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"1.9078901729259927\n",
"The running loss is:\n",
"13.231589883565903\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"1.0178146064281464\n",
"The running loss is:\n",
"7.9983332976698875\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"0.6152564075130683\n",
"The running loss is:\n",
"10.238236993551254\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 4\n",
"0.7875566918116349\n",
"The running loss is:\n",
"9.1368916220963\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.7028378170843308\n",
"The running loss is:\n",
"8.546009212732315\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"0.6573853240563319\n",
"The running loss is:\n",
"8.557626497000456\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.6582789613077273\n",
"The running loss is:\n",
"8.405014142394066\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.6465395494149282\n",
"The running loss is:\n",
"8.690803073346615\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.668523313334355\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 4, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
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{
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"test_data scale\n",
"Un-transforming data\n"
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{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
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{
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"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 12.108495\n",
"48 30755 ... 10.607700\n",
"49 30756 ... 10.552139\n",
"50 30757 ... 11.810363\n",
"51 30758 ... 11.965808\n",
"52 30759 ... 11.572226\n",
"53 30760 ... 11.432143\n",
"54 30761 ... 11.407201\n",
"55 30762 ... 11.625036\n",
"56 30763 ... 11.583269\n",
"\n",
"[14 rows x 32 columns]\n"
],
"name": "stdout"
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
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{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: vz7xqs63 \n",
"\n",
"wandb: Agent Starting Run: vat0wthg with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 4\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: vat0wthg\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/vat0wthg
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
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" class: default\n",
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" relevant_cols:\n",
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" scaler: StandardScaler\n",
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" test_path: Colorado_Douglas County.csv\n",
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" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
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" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
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" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
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" optimizer: Adam\n",
"wandb:\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"38.69787164032459\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"2.9767593569480457\n",
"The running loss is:\n",
"20.345289036631584\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"1.565022233587045\n",
"The running loss is:\n",
"14.763616390526295\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"1.1356627992712534\n",
"The running loss is:\n",
"10.519289702177048\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"0.8091761309366959\n",
"The running loss is:\n",
"12.006632789969444\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 4\n",
"0.9235871376899573\n",
"The running loss is:\n",
"10.068530097603798\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.7745023152002921\n",
"The running loss is:\n",
"10.892198204994202\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"0.8378614003841693\n",
"The running loss is:\n",
"9.449286311864853\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.726868177835758\n",
"The running loss is:\n",
"8.240423366427422\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.6338787204944171\n",
"The running loss is:\n",
"8.944622784852982\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.6880479065271524\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 4, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
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{
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"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
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"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"52 30759 ... 14.516523\n",
"53 30760 ... 15.342272\n",
"54 30761 ... 15.626085\n",
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"56 30763 ... 15.897081\n",
"\n",
"[14 rows x 32 columns]\n"
],
"name": "stdout"
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
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{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: vat0wthg \n",
"\n",
"wandb: Agent Starting Run: 7ympyi75 with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 4\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
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],
"name": "stdout"
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{
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"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/7ympyi75
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
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" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 4\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 4\n",
"forward_params:\n",
" desc: null\n",
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" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 4\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
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" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 4\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
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" value:\n",
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" criterion: MSE\n",
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" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"42.751119792461395\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"3.2885476763431845\n",
"The running loss is:\n",
"22.814359664916992\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"1.7549507434551532\n",
"The running loss is:\n",
"17.861228555440903\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"1.3739406581108387\n",
"The running loss is:\n",
"13.160692304372787\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"1.0123609464902144\n",
"The running loss is:\n",
"12.061859995126724\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 4\n",
"0.9278353842405173\n",
"The running loss is:\n",
"11.913350507616997\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.9164115775089997\n",
"The running loss is:\n",
"10.849895969033241\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"0.8346073822333262\n",
"The running loss is:\n",
"11.268224865198135\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.8667865280921643\n",
"The running loss is:\n",
"10.611917436122894\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.8163013412402227\n",
"The running loss is:\n",
"9.465873330831528\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.7281441023716559\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 4, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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{
"output_type": "stream",
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
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{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 10.687474\n",
"48 30755 ... 8.196827\n",
"49 30756 ... 8.605579\n",
"50 30757 ... 8.132575\n",
"51 30758 ... 7.834826\n",
"52 30759 ... 7.821600\n",
"53 30760 ... 8.354590\n",
"54 30761 ... 8.151829\n",
"55 30762 ... 8.153378\n",
"56 30763 ... 8.345223\n",
"\n",
"[14 rows x 32 columns]\n"
],
"name": "stdout"
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
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{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 7ympyi75 \n",
"\n",
"wandb: Agent Starting Run: wlmcvsr7 with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 5\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: wlmcvsr7\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/wlmcvsr7
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" "
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""
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 5\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 5\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 5\n",
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" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
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" seq_len: 5\n",
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" desc: null\n",
" value: PyTorch\n",
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" desc: null\n",
" value: 1\n",
"sweep:\n",
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" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"16.07284878194332\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"1.2363729832264094\n",
"The running loss is:\n",
"11.393546909093857\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"0.8764266853149121\n",
"The running loss is:\n",
"9.211045920848846\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"0.7085419939114497\n",
"The running loss is:\n",
"8.046417102217674\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"0.6189551617090518\n",
"The running loss is:\n",
"8.130555003881454\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 4\n",
"0.6254273079908811\n",
"The running loss is:\n",
"7.790109492838383\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.5992391917567986\n",
"The running loss is:\n",
"7.453979782760143\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"0.5733830602123187\n",
"The running loss is:\n",
"7.104567661881447\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.5465052047601113\n",
"The running loss is:\n",
"6.915351435542107\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.5319501104263159\n",
"The running loss is:\n",
"7.459764987230301\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.5738280759407923\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 5, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"42 30749 ... 0.000000\n",
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"48 30755 ... 8.039572\n",
"49 30756 ... 8.126947\n",
"50 30757 ... 8.647640\n",
"51 30758 ... 8.920097\n",
"52 30759 ... 8.672168\n",
"53 30760 ... 8.654925\n",
"54 30761 ... 8.377190\n",
"55 30762 ... 7.938785\n",
"56 30763 ... 8.490222\n",
"\n",
"[15 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: wlmcvsr7 \n",
"\n",
"wandb: Agent Starting Run: 4usoutte with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 5\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: 4usoutte\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/4usoutte
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 5\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 5\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 5\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 2\n",
" number_time_series: 3\n",
" output_seq_len: 2\n",
" seq_len: 5\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
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" desc: null\n",
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"sweep:\n",
" desc: null\n",
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" desc: null\n",
" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"17.015090629458427\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"1.308853125342956\n",
"The running loss is:\n",
"14.904403626918793\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"1.146492586686061\n",
"The running loss is:\n",
"9.877731040120125\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"0.759825464624625\n",
"The running loss is:\n",
"8.914640828967094\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"0.685741602228238\n",
"The running loss is:\n",
"8.24161709845066\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 4\n",
"0.6339705460346662\n",
"The running loss is:\n",
"7.48406345397234\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.5756971887671031\n",
"The running loss is:\n",
"7.502739422023296\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"0.5771338016940997\n",
"The running loss is:\n",
"7.524602979421616\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.5788156138016627\n",
"The running loss is:\n",
"7.4196352288126945\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.5707411714471303\n",
"The running loss is:\n",
"8.976969480514526\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.6905361138857328\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 5, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 8.343148\n",
"48 30755 ... 7.248403\n",
"49 30756 ... 6.399437\n",
"50 30757 ... 6.592106\n",
"51 30758 ... 4.307819\n",
"52 30759 ... 3.254845\n",
"53 30760 ... 2.614995\n",
"54 30761 ... 2.333879\n",
"55 30762 ... 1.141000\n",
"56 30763 ... 0.928883\n",
"\n",
"[15 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 4usoutte \n",
"\n",
"wandb: Agent Starting Run: qnbzxb65 with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 5\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: qnbzxb65\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/qnbzxb65
\n",
" "
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""
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 5\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 5\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 5\n",
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" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
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" value:\n",
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" output_seq_len: 3\n",
" seq_len: 5\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
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" desc: null\n",
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"sweep:\n",
" desc: null\n",
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"training_params:\n",
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" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"16.061375049874187\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 0\n",
"1.3384479208228488\n",
"The running loss is:\n",
"11.802918165922165\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 1\n",
"0.9835765138268471\n",
"The running loss is:\n",
"9.635548263788223\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 2\n",
"0.8029623553156853\n",
"The running loss is:\n",
"7.900071606040001\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 3\n",
"0.6583393005033334\n",
"The running loss is:\n",
"7.308927018195391\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 4\n",
"0.6090772515162826\n",
"The running loss is:\n",
"7.408294729888439\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"0.61735789415737\n",
"The running loss is:\n",
"7.30912384018302\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.609093653348585\n",
"The running loss is:\n",
"8.098075211048126\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.6748396009206772\n",
"The running loss is:\n",
"8.676205836236477\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.7230171530197064\n",
"The running loss is:\n",
"8.98013935610652\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.7483449463422099\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 5, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
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"45 30752 ... 0.000000\n",
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"49 30756 ... 7.261724\n",
"50 30757 ... 7.391668\n",
"51 30758 ... 6.424718\n",
"52 30759 ... 6.508060\n",
"53 30760 ... 6.848399\n",
"54 30761 ... 6.814502\n",
"55 30762 ... 6.458637\n",
"56 30763 ... 6.546707\n",
"\n",
"[15 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: qnbzxb65 \n",
"\n",
"wandb: Agent Starting Run: 6u98nj7v with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 5\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: 6u98nj7v\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/6u98nj7v
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 5\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 5\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 5\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 1\n",
" number_time_series: 3\n",
" output_seq_len: 1\n",
" seq_len: 5\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 1\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"13.765893511474133\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"1.0589148854980102\n",
"The running loss is:\n",
"23.43887052498758\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"1.8029900403836598\n",
"The running loss is:\n",
"10.36953791975975\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"0.7976567630584424\n",
"The running loss is:\n",
"8.904323771595955\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"0.6849479824304581\n",
"The running loss is:\n",
"7.417386781424284\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 4\n",
"0.5705682139557141\n",
"The running loss is:\n",
"7.913604368921369\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.6087387976093361\n",
"The running loss is:\n",
"6.859258336946368\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"0.5276352566881821\n",
"The running loss is:\n",
"6.282172272214666\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.4832440209395897\n",
"The running loss is:\n",
"6.116885121911764\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.4705296247624434\n",
"The running loss is:\n",
"7.14730378985405\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.5497925992195423\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 5, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 9.736671\n",
"48 30755 ... 11.564378\n",
"49 30756 ... 9.607123\n",
"50 30757 ... 10.786201\n",
"51 30758 ... 10.428370\n",
"52 30759 ... 11.004709\n",
"53 30760 ... 11.867481\n",
"54 30761 ... 11.287722\n",
"55 30762 ... 10.306524\n",
"56 30763 ... 11.843080\n",
"\n",
"[15 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 6u98nj7v \n",
"\n",
"wandb: Agent Starting Run: x8y2ap84 with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 5\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: x8y2ap84\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/x8y2ap84
\n",
" "
],
"text/plain": [
""
]
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"metadata": {
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}
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{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 5\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 5\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 5\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
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"model_params:\n",
" desc: null\n",
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" seq_len: 5\n",
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" desc: null\n",
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" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"12.553385689854622\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"0.9656450530657401\n",
"The running loss is:\n",
"32.152095057070255\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"2.4732380813130965\n",
"The running loss is:\n",
"13.22272926568985\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"1.0171330204376807\n",
"The running loss is:\n",
"12.398492097854614\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"0.9537301613734319\n",
"The running loss is:\n",
"9.956698954105377\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 4\n",
"0.7658999195465674\n",
"The running loss is:\n",
"8.292960315942764\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.6379200243032895\n",
"The running loss is:\n",
"7.7905485183000565\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"0.5992729629461582\n",
"The running loss is:\n",
"7.017962105572224\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.539843238890171\n",
"The running loss is:\n",
"7.154788330197334\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.5503683330921026\n",
"The running loss is:\n",
"6.995831839740276\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.5381409107492521\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 5, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"Current historical dataframe\n",
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"53 30760 ... 0.202644\n",
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"\n",
"[15 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: x8y2ap84 \n",
"\n",
"wandb: Agent Starting Run: f4nlybf9 with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 5\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: f4nlybf9\n"
],
"name": "stdout"
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{
"output_type": "display_data",
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"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/f4nlybf9
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
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" framework: torch\n",
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" python_version: 3.6.9\n",
"batch_size:\n",
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" relevant_cols:\n",
" - new_cases\n",
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" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
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" relevant_cols:\n",
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" - month\n",
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" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
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" desc: null\n",
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" - MSE\n",
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" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"12.682664819061756\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 0\n",
"1.056888734921813\n",
"The running loss is:\n",
"26.245943874120712\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 1\n",
"2.1871619895100594\n",
"The running loss is:\n",
"10.745129108428955\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 2\n",
"0.895427425702413\n",
"The running loss is:\n",
"10.478202775120735\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 3\n",
"0.8731835645933946\n",
"The running loss is:\n",
"8.926227048039436\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 4\n",
"0.7438522540032864\n",
"The running loss is:\n",
"7.637079827487469\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"0.6364233189572891\n",
"The running loss is:\n",
"7.005005210638046\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.5837504342198372\n",
"The running loss is:\n",
"6.797870747745037\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.5664892289787531\n",
"The running loss is:\n",
"7.502613537013531\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.6252177947511276\n",
"The running loss is:\n",
"7.621904402971268\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.6351587002476057\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 5, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
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"49 30756 ... 5.860340\n",
"50 30757 ... 6.031592\n",
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"53 30760 ... -0.055734\n",
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"\n",
"[15 rows x 32 columns]\n"
],
"name": "stdout"
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: f4nlybf9 \n",
"\n",
"wandb: Agent Starting Run: bxrcu8tu with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 5\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: bxrcu8tu\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/bxrcu8tu
\n",
" "
],
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""
]
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{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 5\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
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" training_path: Colorado_Douglas County.csv\n",
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" relevant_cols:\n",
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" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
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" desc: null\n",
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" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"12.525801971554756\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"0.963523228581135\n",
"The running loss is:\n",
"23.895836547017097\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"1.838141272847469\n",
"The running loss is:\n",
"14.084609515964985\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"1.0834315012280757\n",
"The running loss is:\n",
"10.381171528249979\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"0.7985516560192292\n",
"The running loss is:\n",
"10.052995964884758\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 4\n",
"0.7733073819142121\n",
"The running loss is:\n",
"10.303962796926498\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.7926125228404999\n",
"The running loss is:\n",
"8.726175464689732\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"0.6712442665145948\n",
"The running loss is:\n",
"9.212526094168425\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.7086558533975711\n",
"The running loss is:\n",
"10.139194697141647\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.7799380536262805\n",
"The running loss is:\n",
"10.184998378157616\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.783461413704432\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 5, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"Current historical dataframe\n",
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"49 30756 ... 10.369150\n",
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"51 30758 ... 10.079480\n",
"52 30759 ... 10.377722\n",
"53 30760 ... 11.070954\n",
"54 30761 ... 9.903352\n",
"55 30762 ... 9.985621\n",
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"\n",
"[15 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: bxrcu8tu \n",
"\n",
"wandb: Agent Starting Run: je2yahnk with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 5\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: je2yahnk\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/je2yahnk
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
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" framework: torch\n",
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" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
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" batch_size: 3\n",
" class: default\n",
" forecast_history: 5\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
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" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
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" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"10.798818975687027\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"0.8306783827451559\n",
"The running loss is:\n",
"28.490219056606293\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"2.191555312046638\n",
"The running loss is:\n",
"19.000672325491905\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"1.4615901788839927\n",
"The running loss is:\n",
"12.530485570430756\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"0.9638835054177505\n",
"The running loss is:\n",
"11.969089105725288\n",
"The number of items in train is: \n",
"13\n",
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"0.9206991619788684\n",
"The running loss is:\n",
"10.927263751626015\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.8405587501250781\n",
"The running loss is:\n",
"10.749707907438278\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"0.826900608264483\n",
"The running loss is:\n",
"8.986315917223692\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.6912550705556686\n",
"The running loss is:\n",
"7.793350949883461\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.59948853460642\n",
"The running loss is:\n",
"7.86865272372961\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.6052809787484316\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 5, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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},
{
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"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
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{
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"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"43 30750 ... 0.000000\n",
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"45 30752 ... 0.000000\n",
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"53 30760 ... 15.278111\n",
"54 30761 ... 12.534163\n",
"55 30762 ... 9.271551\n",
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"\n",
"[15 rows x 32 columns]\n"
],
"name": "stdout"
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"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: je2yahnk \n",
"\n",
"wandb: Agent Starting Run: pv154y7u with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 5\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: pv154y7u\n"
],
"name": "stdout"
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{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/pv154y7u
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" "
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"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
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"batch_size:\n",
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" relevant_cols:\n",
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" scaler: StandardScaler\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 5\n",
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" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
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" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"9.802732415497303\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 0\n",
"0.8168943679581085\n",
"The running loss is:\n",
"26.21215522289276\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 1\n",
"2.1843462685743966\n",
"The running loss is:\n",
"17.116993874311447\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 2\n",
"1.4264161561926205\n",
"The running loss is:\n",
"10.959399312734604\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 3\n",
"0.913283276061217\n",
"The running loss is:\n",
"10.964498907327652\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 4\n",
"0.9137082422773043\n",
"The running loss is:\n",
"9.913394719362259\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"0.8261162266135216\n",
"The running loss is:\n",
"8.57229234278202\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.714357695231835\n",
"The running loss is:\n",
"7.871752962470055\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.6559794135391712\n",
"The running loss is:\n",
"7.458349071443081\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.6215290892869234\n",
"The running loss is:\n",
"8.988392800092697\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.7490327333410581\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 5, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 9.390130\n",
"48 30755 ... 11.972624\n",
"49 30756 ... 8.251997\n",
"50 30757 ... 8.524872\n",
"51 30758 ... 7.873636\n",
"52 30759 ... 6.769165\n",
"53 30760 ... 5.787257\n",
"54 30761 ... 4.192029\n",
"55 30762 ... 2.647506\n",
"56 30763 ... 3.688875\n",
"\n",
"[15 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: pv154y7u \n",
"\n",
"wandb: Agent Starting Run: tfairxgi with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 5\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: tfairxgi\n"
],
"name": "stdout"
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{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/tfairxgi
\n",
" "
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""
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
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"dataset_params:\n",
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" batch_size: 3\n",
" class: default\n",
" forecast_history: 5\n",
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" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 5\n",
"forward_params:\n",
" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 5\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
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" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"37.44812400639057\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"2.8806249235685053\n",
"The running loss is:\n",
"22.365391314029694\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"1.7204147164638226\n",
"The running loss is:\n",
"14.247072592377663\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"1.095928660952128\n",
"The running loss is:\n",
"12.75909799337387\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"0.9814690764133747\n",
"The running loss is:\n",
"17.026127204298973\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 4\n",
"1.3097020926383824\n",
"The running loss is:\n",
"12.31944526731968\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.9476496359476676\n",
"The running loss is:\n",
"13.54552149027586\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"1.0419631915596814\n",
"The running loss is:\n",
"12.44608373939991\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.9573910568769162\n",
"The running loss is:\n",
"10.811461791396141\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.8316509070304724\n",
"The running loss is:\n",
"13.428137093782425\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"1.032933622598648\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 5, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
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"49 30756 ... 12.174776\n",
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"51 30758 ... 11.824924\n",
"52 30759 ... 12.332734\n",
"53 30760 ... 12.714437\n",
"54 30761 ... 13.116733\n",
"55 30762 ... 13.821445\n",
"56 30763 ... 13.117739\n",
"\n",
"[15 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: tfairxgi \n",
"\n",
"wandb: Agent Starting Run: qaitrbya with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 5\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: qaitrbya\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/qaitrbya
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 5\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 5\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 5\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 2\n",
" number_time_series: 3\n",
" output_seq_len: 2\n",
" seq_len: 5\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
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" desc: null\n",
" value: 2\n",
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" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"49.11082097887993\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"3.7777554599138408\n",
"The running loss is:\n",
"25.69899582862854\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"1.9768458329714262\n",
"The running loss is:\n",
"17.135295033454895\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"1.3180996179580688\n",
"The running loss is:\n",
"11.379485577344894\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"0.8753450444111457\n",
"The running loss is:\n",
"11.188541859388351\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 4\n",
"0.8606570661067963\n",
"The running loss is:\n",
"11.069215461611748\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.8514781124316729\n",
"The running loss is:\n",
"10.00205671787262\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"0.7693889782978938\n",
"The running loss is:\n",
"10.64719857275486\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.819015274827297\n",
"The running loss is:\n",
"10.02389670908451\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.7710689776218854\n",
"The running loss is:\n",
"9.106609582901001\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.7005084294539231\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 5, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
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"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
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"48 30755 ... 9.304375\n",
"49 30756 ... 6.913957\n",
"50 30757 ... 6.941987\n",
"51 30758 ... 6.408734\n",
"52 30759 ... 5.711936\n",
"53 30760 ... 5.180847\n",
"54 30761 ... 4.393548\n",
"55 30762 ... 4.547277\n",
"56 30763 ... 4.002431\n",
"\n",
"[15 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: qaitrbya \n",
"\n",
"wandb: Agent Starting Run: iouf2wvs with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 5\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: iouf2wvs\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/iouf2wvs
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 5\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 5\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 5\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 5\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
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" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
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"training_params:\n",
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" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"39.271602153778076\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 0\n",
"3.27263351281484\n",
"The running loss is:\n",
"20.22679728269577\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 1\n",
"1.6855664402246475\n",
"The running loss is:\n",
"12.615855321288109\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 2\n",
"1.051321276774009\n",
"The running loss is:\n",
"11.286904752254486\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 3\n",
"0.9405753960212072\n",
"The running loss is:\n",
"10.426268815994263\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 4\n",
"0.8688557346661886\n",
"The running loss is:\n",
"10.909985393285751\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"0.9091654494404793\n",
"The running loss is:\n",
"9.572229564189911\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.7976857970158259\n",
"The running loss is:\n",
"10.429155349731445\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.8690962791442871\n",
"The running loss is:\n",
"8.921477675437927\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.7434564729531606\n",
"The running loss is:\n",
"10.159409493207932\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.8466174577673277\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 5, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 8.940737\n",
"48 30755 ... 8.700059\n",
"49 30756 ... 7.716850\n",
"50 30757 ... 7.790635\n",
"51 30758 ... 7.375722\n",
"52 30759 ... 7.020612\n",
"53 30760 ... 7.071692\n",
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"\n",
"[15 rows x 32 columns]\n"
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"name": "stdout"
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{
"output_type": "stream",
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"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: iouf2wvs \n",
"\n",
"wandb: Agent Starting Run: hissdac6 with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 6\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: hissdac6\n"
],
"name": "stdout"
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{
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"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/hissdac6
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"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
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" framework: torch\n",
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" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
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" value:\n",
" batch_size: 3\n",
" class: default\n",
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" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
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" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
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" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
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"forward_params:\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 6\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
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" desc: null\n",
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" - MSE\n",
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" seq_len: 6\n",
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" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"16.642247676849365\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"1.280172898219182\n",
"The running loss is:\n",
"16.28763623908162\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"1.2528950953139708\n",
"The running loss is:\n",
"9.172755971550941\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"0.7055966131962262\n",
"The running loss is:\n",
"7.831138916313648\n",
"The number of items in train is: \n",
"13\n",
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"0.602395301254896\n",
"The running loss is:\n",
"7.456290934234858\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 4\n",
"0.5735608410949891\n",
"The running loss is:\n",
"7.011703036725521\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.5393617720558093\n",
"The running loss is:\n",
"6.7462056539952755\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"0.5189388964611751\n",
"The running loss is:\n",
"6.409943629056215\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.4930725868504781\n",
"The running loss is:\n",
"6.455305725336075\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.49656197887200576\n",
"The running loss is:\n",
"5.876091826707125\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.45200706359285575\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 6, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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{
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
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"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"48 30755 ... 14.496378\n",
"49 30756 ... 20.103035\n",
"50 30757 ... 14.229822\n",
"51 30758 ... 14.765225\n",
"52 30759 ... 15.657488\n",
"53 30760 ... 19.752836\n",
"54 30761 ... 19.353802\n",
"55 30762 ... 20.783958\n",
"56 30763 ... 22.710882\n",
"\n",
"[16 rows x 32 columns]\n"
],
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{
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"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: hissdac6 \n",
"\n",
"wandb: Agent Starting Run: sq780sr1 with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 6\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: sq780sr1\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/sq780sr1
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" "
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""
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
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" batch_size: 3\n",
" class: default\n",
" forecast_history: 6\n",
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" relevant_cols:\n",
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" - month\n",
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" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 6\n",
"forward_params:\n",
" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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"metrics:\n",
" desc: null\n",
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" - MSE\n",
"model_name:\n",
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"sweep:\n",
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" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"14.69208151102066\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 0\n",
"1.2243401259183884\n",
"The running loss is:\n",
"13.725030314177275\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 1\n",
"1.1437525261814396\n",
"The running loss is:\n",
"8.605534479022026\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 2\n",
"0.7171278732518355\n",
"The running loss is:\n",
"7.257033374160528\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 3\n",
"0.604752781180044\n",
"The running loss is:\n",
"6.742498558014631\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 4\n",
"0.5618748798345526\n",
"The running loss is:\n",
"6.170779198408127\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"0.5142315998673439\n",
"The running loss is:\n",
"5.943502962589264\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.49529191354910534\n",
"The running loss is:\n",
"6.512494046241045\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.5427078371867537\n",
"The running loss is:\n",
"5.600046152248979\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.4666705126874149\n",
"The running loss is:\n",
"6.0191479958593845\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.5015956663216153\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 6, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"51 30758 ... 5.453309\n",
"52 30759 ... 3.219275\n",
"53 30760 ... 1.562811\n",
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"56 30763 ... -0.067193\n",
"\n",
"[16 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: sq780sr1 \n",
"\n",
"wandb: Agent Starting Run: 3lkpbgj0 with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 6\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: 3lkpbgj0\n"
],
"name": "stdout"
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{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/3lkpbgj0
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 6\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 6\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 6\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 6\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"15.149451583623886\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 0\n",
"1.2624542986353238\n",
"The running loss is:\n",
"12.484605565667152\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 1\n",
"1.0403837971389294\n",
"The running loss is:\n",
"9.57485019415617\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 2\n",
"0.7979041828463475\n",
"The running loss is:\n",
"8.463449150323868\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 3\n",
"0.7052874291936556\n",
"The running loss is:\n",
"7.940030604600906\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 4\n",
"0.6616692170500755\n",
"The running loss is:\n",
"7.351875007152557\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"0.6126562505960464\n",
"The running loss is:\n",
"7.489130318164825\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.6240941931804022\n",
"The running loss is:\n",
"6.787940315902233\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.5656616929918528\n",
"The running loss is:\n",
"7.015684597194195\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.5846403830995163\n",
"The running loss is:\n",
"6.8622966930270195\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.5718580577522516\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 6, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"41 30748 ... 0.000000\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
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"48 30755 ... 8.451162\n",
"49 30756 ... 10.490123\n",
"50 30757 ... 3.936914\n",
"51 30758 ... 2.963327\n",
"52 30759 ... -1.098660\n",
"53 30760 ... -4.159821\n",
"54 30761 ... -6.189400\n",
"55 30762 ... -6.795932\n",
"56 30763 ... -6.658059\n",
"\n",
"[16 rows x 32 columns]\n"
],
"name": "stdout"
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 3lkpbgj0 \n",
"\n",
"wandb: Agent Starting Run: 5v3ml29k with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 6\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: 5v3ml29k\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/5v3ml29k
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
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}
},
{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 6\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 6\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
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" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
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" seq_len: 6\n",
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" desc: null\n",
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" desc: null\n",
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"sweep:\n",
" desc: null\n",
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" batch_size: 3\n",
" criterion: MSE\n",
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" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"12.161938413977623\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"0.9355337241521249\n",
"The running loss is:\n",
"28.572343215346336\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"2.1978725550266414\n",
"The running loss is:\n",
"12.400501441210508\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"0.9538847262469622\n",
"The running loss is:\n",
"9.189391441643238\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"0.7068762647417876\n",
"The running loss is:\n",
"7.397752322256565\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 4\n",
"0.5690578709428127\n",
"The running loss is:\n",
"6.42874202132225\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.4945186170247885\n",
"The running loss is:\n",
"6.827842012047768\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"0.5252186163113668\n",
"The running loss is:\n",
"6.1493959575891495\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.4730304582760884\n",
"The running loss is:\n",
"6.439127545803785\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.4953175035233681\n",
"The running loss is:\n",
"8.07044368237257\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.6208033601825054\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 6, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"Current historical dataframe\n",
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"50 30757 ... 13.947339\n",
"51 30758 ... 11.741467\n",
"52 30759 ... 10.111837\n",
"53 30760 ... 11.390107\n",
"54 30761 ... 8.920159\n",
"55 30762 ... 10.996446\n",
"56 30763 ... 16.557650\n",
"\n",
"[16 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
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{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 5v3ml29k \n",
"\n",
"wandb: Agent Starting Run: unibab00 with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 6\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: unibab00\n"
],
"name": "stdout"
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{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/unibab00
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 6\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 6\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
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" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 6\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 2\n",
" number_time_series: 3\n",
" output_seq_len: 2\n",
" seq_len: 6\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
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" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"10.454828664660454\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 0\n",
"0.8712357220550379\n",
"The running loss is:\n",
"29.681454718112946\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 1\n",
"2.4734545598427453\n",
"The running loss is:\n",
"10.859991066157818\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 2\n",
"0.9049992555131515\n",
"The running loss is:\n",
"10.422705300152302\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 3\n",
"0.8685587750126919\n",
"The running loss is:\n",
"8.322179265320301\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 4\n",
"0.6935149387766918\n",
"The running loss is:\n",
"7.16530604660511\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"0.5971088372170925\n",
"The running loss is:\n",
"6.654772460460663\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.5545643717050552\n",
"The running loss is:\n",
"6.77964261546731\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.5649702179556092\n",
"The running loss is:\n",
"6.088913932442665\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.5074094943702221\n",
"The running loss is:\n",
"6.501669891178608\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.541805824264884\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 6, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"41 30748 ... 0.000000\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
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"47 30754 ... 9.519657\n",
"48 30755 ... 11.527104\n",
"49 30756 ... 14.025534\n",
"50 30757 ... 9.028507\n",
"51 30758 ... 9.338325\n",
"52 30759 ... 9.590857\n",
"53 30760 ... 10.613542\n",
"54 30761 ... 10.388042\n",
"55 30762 ... 10.484270\n",
"56 30763 ... 10.389216\n",
"\n",
"[16 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: unibab00 \n",
"\n",
"wandb: Agent Starting Run: ifp9eb1p with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 6\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: ifp9eb1p\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/ifp9eb1p
\n",
" "
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""
]
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"metadata": {
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{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 6\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 6\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 6\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 6\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"12.416129767894745\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 0\n",
"1.0346774806578953\n",
"The running loss is:\n",
"24.20527493953705\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 1\n",
"2.0171062449614205\n",
"The running loss is:\n",
"11.19543930888176\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 2\n",
"0.9329532757401466\n",
"The running loss is:\n",
"10.788735710084438\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 3\n",
"0.8990613091737032\n",
"The running loss is:\n",
"9.559967994689941\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 4\n",
"0.7966639995574951\n",
"The running loss is:\n",
"8.618342891335487\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"0.718195240944624\n",
"The running loss is:\n",
"7.969642907381058\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.6641369089484215\n",
"The running loss is:\n",
"7.33133128285408\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.6109442735711733\n",
"The running loss is:\n",
"6.842497617006302\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.5702081347505251\n",
"The running loss is:\n",
"6.608101170510054\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.5506750975425044\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 6, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"41 30748 ... 0.000000\n",
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"49 30756 ... 11.673032\n",
"50 30757 ... 6.914804\n",
"51 30758 ... 6.505346\n",
"52 30759 ... 4.965737\n",
"53 30760 ... 4.142810\n",
"54 30761 ... 3.150626\n",
"55 30762 ... 3.350169\n",
"56 30763 ... 4.398151\n",
"\n",
"[16 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: ifp9eb1p \n",
"\n",
"wandb: Agent Starting Run: thts7qrs with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 6\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: thts7qrs\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/thts7qrs
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 6\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 6\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 6\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 1\n",
" number_time_series: 3\n",
" output_seq_len: 1\n",
" seq_len: 6\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
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"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"13.258691161870956\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"1.0198993201439197\n",
"The running loss is:\n",
"23.489024937152863\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"1.8068480720886817\n",
"The running loss is:\n",
"18.21075715869665\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"1.4008274737458963\n",
"The running loss is:\n",
"10.906683094799519\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"0.8389756226768861\n",
"The running loss is:\n",
"8.148265436291695\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 4\n",
"0.6267896489455149\n",
"The running loss is:\n",
"7.965685077011585\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.6127450059239681\n",
"The running loss is:\n",
"8.664709061384201\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"0.6665160816449386\n",
"The running loss is:\n",
"7.032974503934383\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.5409980387641833\n",
"The running loss is:\n",
"6.97207360714674\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.5363133543959031\n",
"The running loss is:\n",
"7.017210938036442\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.5397854567720339\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 6, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"41 30748 ... 0.000000\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
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"47 30754 ... 13.510240\n",
"48 30755 ... 16.805296\n",
"49 30756 ... 21.841839\n",
"50 30757 ... 16.963865\n",
"51 30758 ... 17.538879\n",
"52 30759 ... 19.097288\n",
"53 30760 ... 21.089573\n",
"54 30761 ... 22.992525\n",
"55 30762 ... 22.120745\n",
"56 30763 ... 20.562706\n",
"\n",
"[16 rows x 32 columns]\n"
],
"name": "stdout"
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: thts7qrs \n",
"\n",
"wandb: Agent Starting Run: 47lg0nn6 with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 6\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: 47lg0nn6\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/47lg0nn6
\n",
" "
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""
]
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{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 6\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 6\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 6\n",
" forecast_length: 2\n",
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" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
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" value:\n",
" forecast_length: 2\n",
" number_time_series: 3\n",
" output_seq_len: 2\n",
" seq_len: 6\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
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" desc: null\n",
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"out_seq_length:\n",
" desc: null\n",
" value: 2\n",
"sweep:\n",
" desc: null\n",
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"training_params:\n",
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" batch_size: 3\n",
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" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"10.835459772497416\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 0\n",
"0.9029549810414513\n",
"The running loss is:\n",
"22.96461908519268\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 1\n",
"1.91371825709939\n",
"The running loss is:\n",
"15.761415027081966\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 2\n",
"1.3134512522568305\n",
"The running loss is:\n",
"10.180416569113731\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 3\n",
"0.8483680474261442\n",
"The running loss is:\n",
"9.744838282465935\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 4\n",
"0.8120698568721613\n",
"The running loss is:\n",
"8.362954512238503\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"0.6969128760198752\n",
"The running loss is:\n",
"7.482268325984478\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.6235223604987065\n",
"The running loss is:\n",
"7.62644924223423\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.6355374368528525\n",
"The running loss is:\n",
"6.36828438937664\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.5306903657813867\n",
"The running loss is:\n",
"6.734523329883814\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.5612102774903178\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 6, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"41 30748 ... 0.000000\n",
"42 30749 ... 0.000000\n",
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"49 30756 ... 16.839764\n",
"50 30757 ... 11.906046\n",
"51 30758 ... 12.192764\n",
"52 30759 ... 13.010283\n",
"53 30760 ... 14.609374\n",
"54 30761 ... 13.891782\n",
"55 30762 ... 13.932491\n",
"56 30763 ... 13.201247\n",
"\n",
"[16 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 47lg0nn6 \n",
"\n",
"wandb: Agent Starting Run: rf0uogu2 with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 6\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: rf0uogu2\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/rf0uogu2
\n",
" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 6\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 6\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 6\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 6\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"11.08357983827591\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 0\n",
"0.9236316531896591\n",
"The running loss is:\n",
"22.382230758666992\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 1\n",
"1.8651858965555828\n",
"The running loss is:\n",
"15.076354868710041\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 2\n",
"1.2563629057258368\n",
"The running loss is:\n",
"10.64572124928236\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 3\n",
"0.8871434374401966\n",
"The running loss is:\n",
"10.859172463417053\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 4\n",
"0.9049310386180878\n",
"The running loss is:\n",
"9.866730868816376\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"0.8222275724013647\n",
"The running loss is:\n",
"9.314311161637306\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.7761925968031088\n",
"The running loss is:\n",
"8.16476234793663\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.6803968623280525\n",
"The running loss is:\n",
"7.3978771567344666\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.6164897630612055\n",
"The running loss is:\n",
"8.245596423745155\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.6871330353120962\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 6, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"41 30748 ... 0.000000\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 6.262431\n",
"48 30755 ... 7.172925\n",
"49 30756 ... 10.437560\n",
"50 30757 ... 8.788393\n",
"51 30758 ... 7.332535\n",
"52 30759 ... 4.802159\n",
"53 30760 ... 2.583888\n",
"54 30761 ... -1.306381\n",
"55 30762 ... 0.795288\n",
"56 30763 ... 2.912030\n",
"\n",
"[16 rows x 32 columns]\n"
],
"name": "stdout"
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: rf0uogu2 \n",
"\n",
"wandb: Agent Starting Run: qeeauzm6 with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 6\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: qeeauzm6\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/qeeauzm6
\n",
" "
],
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""
]
},
"metadata": {
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}
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{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 6\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 6\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 6\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
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" forecast_length: 1\n",
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" seq_len: 6\n",
"model_type:\n",
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" value: PyTorch\n",
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" epochs: 10\n",
" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"83.36189612746239\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 0\n",
"6.412453548266337\n",
"The running loss is:\n",
"25.860291827470064\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 1\n",
"1.9892532174976973\n",
"The running loss is:\n",
"19.907233595848083\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 2\n",
"1.5313256612190833\n",
"The running loss is:\n",
"10.90076495707035\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 3\n",
"0.8385203813131039\n",
"The running loss is:\n",
"10.626565247774124\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 4\n",
"0.8174280959826249\n",
"The running loss is:\n",
"9.881012380123138\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 5\n",
"0.7600778753940876\n",
"The running loss is:\n",
"11.910851925611496\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 6\n",
"0.916219378893192\n",
"The running loss is:\n",
"7.531356927007437\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 7\n",
"0.5793351482313412\n",
"The running loss is:\n",
"10.415256395936012\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 8\n",
"0.8011735689181548\n",
"The running loss is:\n",
"9.927764600142837\n",
"The number of items in train is: \n",
"13\n",
"The loss for epoch 9\n",
"0.7636742000109874\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 6, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"49 30756 ... 12.626095\n",
"50 30757 ... 11.517555\n",
"51 30758 ... 11.598584\n",
"52 30759 ... 12.085279\n",
"53 30760 ... 12.707908\n",
"54 30761 ... 12.770116\n",
"55 30762 ... 12.778158\n",
"56 30763 ... 12.802703\n",
"\n",
"[16 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: qeeauzm6 \n",
"\n",
"wandb: Agent Starting Run: pfx7ru7f with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 6\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: pfx7ru7f\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/pfx7ru7f
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
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" class: default\n",
" forecast_history: 6\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 6\n",
"forward_params:\n",
" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 6\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
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" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"59.03156542778015\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 0\n",
"4.919297118981679\n",
"The running loss is:\n",
"20.912684738636017\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 1\n",
"1.7427237282196681\n",
"The running loss is:\n",
"12.18588924407959\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 2\n",
"1.0154907703399658\n",
"The running loss is:\n",
"10.648322485387325\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 3\n",
"0.8873602071156105\n",
"The running loss is:\n",
"10.730297669768333\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 4\n",
"0.8941914724806944\n",
"The running loss is:\n",
"9.87667851895094\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"0.8230565432459116\n",
"The running loss is:\n",
"9.237145557999611\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.769762129833301\n",
"The running loss is:\n",
"8.763213515281677\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.7302677929401398\n",
"The running loss is:\n",
"9.106015630066395\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.7588346358388662\n",
"The running loss is:\n",
"8.237487856298685\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.6864573213582238\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 6, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"41 30748 ... 0.000000\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
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"49 30756 ... 10.443715\n",
"50 30757 ... 7.849214\n",
"51 30758 ... 7.840856\n",
"52 30759 ... 7.540580\n",
"53 30760 ... 7.049789\n",
"54 30761 ... 6.162581\n",
"55 30762 ... 5.630850\n",
"56 30763 ... 5.403432\n",
"\n",
"[16 rows x 32 columns]\n"
],
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: pfx7ru7f \n",
"\n",
"wandb: Agent Starting Run: hf37aby9 with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 6\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: hf37aby9\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/hf37aby9
\n",
" "
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""
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},
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{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
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" desc: null\n",
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" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"48.265553653240204\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 0\n",
"4.022129471103351\n",
"The running loss is:\n",
"17.88239400088787\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 1\n",
"1.4901995000739892\n",
"The running loss is:\n",
"13.118484437465668\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 2\n",
"1.0932070364554722\n",
"The running loss is:\n",
"10.311319708824158\n",
"The number of items in train is: \n",
"12\n",
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"0.8592766424020132\n",
"The running loss is:\n",
"10.934739962220192\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 4\n",
"0.911228330185016\n",
"The running loss is:\n",
"10.6557736992836\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"0.8879811416069666\n",
"The running loss is:\n",
"10.139354795217514\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.8449462329347929\n",
"The running loss is:\n",
"8.855517655611038\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.7379598046342531\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"\u001b[34m\u001b[1mwandb\u001b[0m: Network error resolved after 0:00:11.468286, resuming normal operation.\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"The running loss is:\n",
"9.930634662508965\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.8275528885424137\n",
"The running loss is:\n",
"10.618825137615204\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.884902094801267\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 6, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
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},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
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"52 30759 ... 12.096951\n",
"53 30760 ... 11.761296\n",
"54 30761 ... 12.113394\n",
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"56 30763 ... 11.604386\n",
"\n",
"[16 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: hf37aby9 \n",
"\n",
"wandb: Agent Starting Run: u316b39b with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 7\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
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],
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{
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"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/u316b39b
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
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" desc: null\n",
" value: false\n",
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" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
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" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
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" file_path: Colorado_Douglas County.csv\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
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"wandb:\n",
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"\n",
"Torch is using cpu\n",
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"The number of items in train is: \n",
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"The loss for epoch 0\n",
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"The number of items in train is: \n",
"12\n",
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"2.0659098935623965\n",
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"8.455985829234123\n",
"The number of items in train is: \n",
"12\n",
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"0.7046654857695103\n",
"The running loss is:\n",
"7.967825371772051\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 3\n",
"0.6639854476476709\n",
"The running loss is:\n",
"7.571539465337992\n",
"The number of items in train is: \n",
"12\n",
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"0.6309616221114993\n",
"The running loss is:\n",
"7.022769663482904\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"0.5852308052902421\n",
"The running loss is:\n",
"6.53892756998539\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.5449106308321158\n",
"The running loss is:\n",
"6.44024109095335\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.5366867575794458\n",
"The running loss is:\n",
"6.065792869776487\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.5054827391480406\n",
"The running loss is:\n",
"6.28930689394474\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.5241089078287283\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 7, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"41 30748 ... 0.000000\n",
"42 30749 ... 0.000000\n",
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"\n",
"[17 rows x 32 columns]\n"
],
"name": "stdout"
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: u316b39b \n",
"\n",
"wandb: Agent Starting Run: n6k80t2e with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 7\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: n6k80t2e\n"
],
"name": "stdout"
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{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/n6k80t2e
\n",
" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 7\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 7\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 7\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 2\n",
" number_time_series: 3\n",
" output_seq_len: 2\n",
" seq_len: 7\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 2\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"13.276512056589127\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 0\n",
"1.1063760047157605\n",
"The running loss is:\n",
"18.049271062016487\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 1\n",
"1.5041059218347073\n",
"The running loss is:\n",
"8.319267615675926\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 2\n",
"0.6932723013063272\n",
"The running loss is:\n",
"7.965411841869354\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 3\n",
"0.6637843201557795\n",
"The running loss is:\n",
"7.3311899825930595\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 4\n",
"0.6109324985494217\n",
"The running loss is:\n",
"6.7873126193881035\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"0.5656093849490086\n",
"The running loss is:\n",
"6.498296394944191\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.5415246995786825\n",
"The running loss is:\n",
"6.533873878419399\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.5444894898682833\n",
"The running loss is:\n",
"6.097821369767189\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.5081517808139324\n",
"The running loss is:\n",
"6.265468001365662\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.5221223334471384\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 7, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"41 30748 ... 0.000000\n",
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"50 30757 ... 8.368803\n",
"51 30758 ... 2.633995\n",
"52 30759 ... 1.451626\n",
"53 30760 ... -2.860904\n",
"54 30761 ... -3.623986\n",
"55 30762 ... -4.194643\n",
"56 30763 ... -4.595941\n",
"\n",
"[17 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: n6k80t2e \n",
"\n",
"wandb: Agent Starting Run: ynqfy2li with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 7\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: ynqfy2li\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/ynqfy2li
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 7\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 7\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 7\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 7\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
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"training_params:\n",
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" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"14.121348142623901\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 0\n",
"1.1767790118853252\n",
"The running loss is:\n",
"11.962568417191505\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 1\n",
"0.9968807014326254\n",
"The running loss is:\n",
"8.415272369980812\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 2\n",
"0.701272697498401\n",
"The running loss is:\n",
"7.760982871055603\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 3\n",
"0.6467485725879669\n",
"The running loss is:\n",
"7.097700580954552\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 4\n",
"0.5914750484128793\n",
"The running loss is:\n",
"6.845601633191109\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"0.5704668027659258\n",
"The running loss is:\n",
"6.674819730222225\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.5562349775185188\n",
"The running loss is:\n",
"6.4955049604177475\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.5412920800348123\n",
"The running loss is:\n",
"5.942568197846413\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.49521401648720104\n",
"The running loss is:\n",
"6.2821846306324005\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.5235153858860334\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 7, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"40 30747 ... 0.000000\n",
"41 30748 ... 0.000000\n",
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"53 30760 ... 9.016667\n",
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"55 30762 ... 8.878509\n",
"56 30763 ... 8.781803\n",
"\n",
"[17 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: ynqfy2li \n",
"\n",
"wandb: Agent Starting Run: z3a45bpw with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 7\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: z3a45bpw\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/z3a45bpw
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" "
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""
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 7\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 7\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 7\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 1\n",
" number_time_series: 3\n",
" output_seq_len: 1\n",
" seq_len: 7\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 1\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"9.900953810662031\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 0\n",
"0.825079484221836\n",
"The running loss is:\n",
"30.638646006584167\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 1\n",
"2.5532205005486808\n",
"The running loss is:\n",
"13.565400153398514\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 2\n",
"1.1304500127832096\n",
"The running loss is:\n",
"12.18923476524651\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 3\n",
"1.0157695637705426\n",
"The running loss is:\n",
"9.495965160429478\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 4\n",
"0.7913304300357898\n",
"The running loss is:\n",
"8.144568987190723\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"0.6787140822658936\n",
"The running loss is:\n",
"7.078736245632172\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.5898946871360143\n",
"The running loss is:\n",
"6.726401956751943\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.5605334963959953\n",
"The running loss is:\n",
"6.241230476647615\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.5201025397206346\n",
"The running loss is:\n",
"6.079278342425823\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.5066065285354853\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 7, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"40 30747 ... 0.000000\n",
"41 30748 ... 0.000000\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 8.471974\n",
"48 30755 ... 10.483409\n",
"49 30756 ... 10.175096\n",
"50 30757 ... 10.090322\n",
"51 30758 ... 6.847208\n",
"52 30759 ... 6.857956\n",
"53 30760 ... 6.441480\n",
"54 30761 ... 5.431954\n",
"55 30762 ... 5.906725\n",
"56 30763 ... 5.729991\n",
"\n",
"[17 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: z3a45bpw \n",
"\n",
"wandb: Agent Starting Run: sqgiswkh with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 7\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: sqgiswkh\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/sqgiswkh
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 7\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 7\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 7\n",
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" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
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" forecast_length: 2\n",
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" seq_len: 7\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
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"sweep:\n",
" desc: null\n",
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"training_params:\n",
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" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"10.352339945733547\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 0\n",
"0.8626949954777956\n",
"The running loss is:\n",
"27.420582100749016\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 1\n",
"2.2850485083957515\n",
"The running loss is:\n",
"11.992324955761433\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 2\n",
"0.9993604129801194\n",
"The running loss is:\n",
"11.289713278412819\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 3\n",
"0.9408094398677349\n",
"The running loss is:\n",
"8.813286826014519\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 4\n",
"0.7344405688345432\n",
"The running loss is:\n",
"7.834414124488831\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"0.6528678437074026\n",
"The running loss is:\n",
"7.225820302963257\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.6021516919136047\n",
"The running loss is:\n",
"6.88609754294157\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.5738414619117975\n",
"The running loss is:\n",
"6.201435163617134\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.5167862636347612\n",
"The running loss is:\n",
"6.14191147685051\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.5118259564042091\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 7, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
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"[17 rows x 32 columns]\n"
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"name": "stdout"
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"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
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{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: sqgiswkh \n",
"\n",
"wandb: Agent Starting Run: ihyxflsp with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 7\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
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],
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{
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"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/ihyxflsp
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
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" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
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" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
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" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
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"forward_params:\n",
" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 7\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
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" seq_len: 7\n",
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" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
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" desc: null\n",
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" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"11.217051550745964\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 0\n",
"0.934754295895497\n",
"The running loss is:\n",
"23.319495856761932\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 1\n",
"1.9432913213968277\n",
"The running loss is:\n",
"10.772423923015594\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 2\n",
"0.8977019935846329\n",
"The running loss is:\n",
"10.515882782638073\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 3\n",
"0.8763235652198395\n",
"The running loss is:\n",
"8.058349311351776\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 4\n",
"0.6715291092793146\n",
"The running loss is:\n",
"7.961005441844463\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"0.6634171201537052\n",
"The running loss is:\n",
"7.059004873037338\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.5882504060864449\n",
"The running loss is:\n",
"6.685458019375801\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.5571215016146501\n",
"The running loss is:\n",
"6.883459039032459\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.5736215865860382\n",
"The running loss is:\n",
"7.376760378479958\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.6147300315399965\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 7, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"40 30747 ... 0.000000\n",
"41 30748 ... 0.000000\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
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"49 30756 ... 11.776529\n",
"50 30757 ... 12.432104\n",
"51 30758 ... 9.630356\n",
"52 30759 ... 9.944347\n",
"53 30760 ... 10.629821\n",
"54 30761 ... 10.653158\n",
"55 30762 ... 11.109354\n",
"56 30763 ... 10.805975\n",
"\n",
"[17 rows x 32 columns]\n"
],
"name": "stdout"
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: ihyxflsp \n",
"\n",
"wandb: Agent Starting Run: 3b2n88ri with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 7\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: 3b2n88ri\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/3b2n88ri
\n",
" "
],
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""
]
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
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" value:\n",
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" class: default\n",
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" relevant_cols:\n",
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" scaler: StandardScaler\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 7\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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" desc: null\n",
" value:\n",
" - MSE\n",
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"sweep:\n",
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" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"18.48319063708186\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 0\n",
"1.5402658864234884\n",
"The running loss is:\n",
"18.761643692851067\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 1\n",
"1.5634703077375889\n",
"The running loss is:\n",
"21.986995615065098\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 2\n",
"1.8322496345887582\n",
"The running loss is:\n",
"9.689714223146439\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 3\n",
"0.8074761852622032\n",
"The running loss is:\n",
"9.407272886484861\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 4\n",
"0.7839394072070718\n",
"The running loss is:\n",
"8.005861973389983\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"0.6671551644491652\n",
"The running loss is:\n",
"7.884846691042185\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.6570705575868487\n",
"The running loss is:\n",
"7.528995893895626\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.6274163244913021\n",
"The running loss is:\n",
"8.065547659993172\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.6721289716660976\n",
"The running loss is:\n",
"6.982815816998482\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.5819013180832068\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 7, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
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{
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"\n",
"[17 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
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"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 3b2n88ri \n",
"\n",
"wandb: Agent Starting Run: no85t7az with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 7\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: no85t7az\n"
],
"name": "stdout"
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{
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"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/no85t7az
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 7\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 7\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 7\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
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" forecast_length: 2\n",
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" seq_len: 7\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
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"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"15.000954568386078\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 0\n",
"1.2500795473655064\n",
"The running loss is:\n",
"21.221872463822365\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 1\n",
"1.768489371985197\n",
"The running loss is:\n",
"19.358168706297874\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 2\n",
"1.613180725524823\n",
"The running loss is:\n",
"9.955740116536617\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 3\n",
"0.8296450097113848\n",
"The running loss is:\n",
"9.47061137482524\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 4\n",
"0.7892176145687699\n",
"The running loss is:\n",
"8.324287980794907\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"0.6936906650662422\n",
"The running loss is:\n",
"7.854575924575329\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.6545479937146107\n",
"The running loss is:\n",
"7.608733028173447\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.6340610856811205\n",
"The running loss is:\n",
"6.9321389347314835\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.577678244560957\n",
"The running loss is:\n",
"6.323972467333078\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.5269977056110898\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 7, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"40 30747 ... 0.000000\n",
"41 30748 ... 0.000000\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
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"52 30759 ... 4.554304\n",
"53 30760 ... 2.250141\n",
"54 30761 ... -1.074027\n",
"55 30762 ... 1.474841\n",
"56 30763 ... -1.939803\n",
"\n",
"[17 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: no85t7az \n",
"\n",
"wandb: Agent Starting Run: qrike4wt with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 7\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: qrike4wt\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/qrike4wt
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
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}
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{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 7\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 7\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 7\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 7\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
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" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"11.473877847194672\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 0\n",
"0.9561564872662226\n",
"The running loss is:\n",
"17.159127980470657\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 1\n",
"1.429927331705888\n",
"The running loss is:\n",
"13.055007100105286\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 2\n",
"1.087917258342107\n",
"The running loss is:\n",
"9.946389883756638\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 3\n",
"0.8288658236463865\n",
"The running loss is:\n",
"8.777176484465599\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 4\n",
"0.7314313737054666\n",
"The running loss is:\n",
"8.020771831274033\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"0.6683976526061693\n",
"The running loss is:\n",
"7.233478561043739\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.6027898800869783\n",
"The running loss is:\n",
"6.712913706898689\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.5594094755748907\n",
"The running loss is:\n",
"5.935887351632118\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.4946572793026765\n",
"The running loss is:\n",
"6.456776849925518\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.5380647374937931\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 7, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
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"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
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{
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"Current historical dataframe\n",
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"\n",
"[17 rows x 32 columns]\n"
],
"name": "stdout"
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{
"output_type": "stream",
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"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: qrike4wt \n",
"\n",
"wandb: Agent Starting Run: p21rcgtl with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 7\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: p21rcgtl\n"
],
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{
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"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
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" framework: torch\n",
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" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
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" relevant_cols:\n",
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" scaler: StandardScaler\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
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" value: MultiAttnHeadSimple\n",
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" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"106.6566134095192\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 0\n",
"8.888051117459932\n",
"The running loss is:\n",
"24.606463849544525\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 1\n",
"2.0505386541287103\n",
"The running loss is:\n",
"21.61753984540701\n",
"The number of items in train is: \n",
"12\n",
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"1.8014616537839174\n",
"The running loss is:\n",
"23.79516276717186\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 3\n",
"1.982930230597655\n",
"The running loss is:\n",
"11.609253287315369\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 4\n",
"0.9674377739429474\n",
"The running loss is:\n",
"11.628214344382286\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"0.9690178620318571\n",
"The running loss is:\n",
"9.073524564504623\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.7561270470420519\n",
"The running loss is:\n",
"9.348070994019508\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.7790059161682924\n",
"The running loss is:\n",
"9.628808468580246\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.8024007057150205\n",
"The running loss is:\n",
"9.66310379654169\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.8052586497118076\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 7, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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},
{
"output_type": "stream",
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"torch.Size([10])\n",
"test_data scale\n",
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"name": "stdout"
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{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"40 30747 ... 0.000000\n",
"41 30748 ... 0.000000\n",
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"43 30750 ... 0.000000\n",
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"51 30758 ... 10.287642\n",
"52 30759 ... 10.387918\n",
"53 30760 ... 10.812337\n",
"54 30761 ... 9.955990\n",
"55 30762 ... 11.362534\n",
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"\n",
"[17 rows x 32 columns]\n"
],
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: p21rcgtl \n",
"\n",
"wandb: Agent Starting Run: k6byrhpo with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 7\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: k6byrhpo\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/k6byrhpo
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
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" python_version: 3.6.9\n",
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" relevant_cols:\n",
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" scaler: StandardScaler\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
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" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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" desc: null\n",
" value:\n",
" - MSE\n",
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" optimizer: Adam\n",
"wandb:\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"81.6181215941906\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 0\n",
"6.8015101328492165\n",
"The running loss is:\n",
"22.043223172426224\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 1\n",
"1.836935264368852\n",
"The running loss is:\n",
"14.447735771536827\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 2\n",
"1.2039779809614022\n",
"The running loss is:\n",
"15.471910580992699\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 3\n",
"1.2893258817493916\n",
"The running loss is:\n",
"11.04138045758009\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 4\n",
"0.9201150381316742\n",
"The running loss is:\n",
"12.106047950685024\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"1.008837329223752\n",
"The running loss is:\n",
"10.577641814947128\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.881470151245594\n",
"The running loss is:\n",
"9.409645445644855\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.7841371204704046\n",
"The running loss is:\n",
"8.933936536312103\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.744494711359342\n",
"The running loss is:\n",
"8.221374459564686\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.6851145382970572\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 7, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"49 30756 ... 9.267735\n",
"50 30757 ... 11.273976\n",
"51 30758 ... 9.497227\n",
"52 30759 ... 8.919030\n",
"53 30760 ... 7.004339\n",
"54 30761 ... 4.377275\n",
"55 30762 ... 3.087500\n",
"56 30763 ... 4.338648\n",
"\n",
"[17 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: k6byrhpo \n",
"\n",
"wandb: Agent Starting Run: 52seuqzl with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 7\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: 52seuqzl\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/52seuqzl
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 7\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 7\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 7\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 7\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"56.113191187381744\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 0\n",
"4.676099265615146\n",
"The running loss is:\n",
"18.30052262544632\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 1\n",
"1.5250435521205266\n",
"The running loss is:\n",
"11.604714661836624\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 2\n",
"0.967059555153052\n",
"The running loss is:\n",
"14.872128278017044\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 3\n",
"1.239344023168087\n",
"The running loss is:\n",
"10.402111932635307\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 4\n",
"0.8668426610529423\n",
"The running loss is:\n",
"10.397299006581306\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"0.8664415838817755\n",
"The running loss is:\n",
"9.851659432053566\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.8209716193377972\n",
"The running loss is:\n",
"9.47095012664795\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.7892458438873291\n",
"The running loss is:\n",
"8.210800468921661\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.6842333724101385\n",
"The running loss is:\n",
"8.250100195407867\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.6875083496173223\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 7, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"40 30747 ... 0.000000\n",
"41 30748 ... 0.000000\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
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"47 30754 ... 11.827257\n",
"48 30755 ... 13.631978\n",
"49 30756 ... 11.137757\n",
"50 30757 ... 6.047119\n",
"51 30758 ... 6.934722\n",
"52 30759 ... 6.921974\n",
"53 30760 ... 6.659066\n",
"54 30761 ... 6.745699\n",
"55 30762 ... 8.320328\n",
"56 30763 ... 4.086565\n",
"\n",
"[17 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 52seuqzl \n",
"\n",
"wandb: Agent Starting Run: 4i7r4tc9 with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 8\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: 4i7r4tc9\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/4i7r4tc9
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
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},
{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 8\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 8\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 8\n",
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" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
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"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
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" forecast_length: 1\n",
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" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"14.96486447751522\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 0\n",
"1.2470720397929351\n",
"The running loss is:\n",
"12.224298192188144\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 1\n",
"1.0186915160156786\n",
"The running loss is:\n",
"8.319845624268055\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 2\n",
"0.6933204686890045\n",
"The running loss is:\n",
"7.175463631749153\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 3\n",
"0.5979553026457628\n",
"The running loss is:\n",
"6.868135239928961\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 4\n",
"0.5723446033274134\n",
"The running loss is:\n",
"6.5902868285775185\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"0.5491905690481266\n",
"The running loss is:\n",
"5.774220548570156\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.4811850457141797\n",
"The running loss is:\n",
"5.966882690787315\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.49724022423227626\n",
"The running loss is:\n",
"6.034196428954601\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.5028497024128834\n",
"The running loss is:\n",
"5.637171816080809\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.46976431800673407\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 8, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"Current historical dataframe\n",
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"52 30759 ... 10.219217\n",
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"[18 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 4i7r4tc9 \n",
"\n",
"wandb: Agent Starting Run: ik2lbrgv with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 8\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: ik2lbrgv\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/ik2lbrgv
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
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" relevant_cols:\n",
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" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
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" relevant_cols:\n",
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" - month\n",
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" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
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" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
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" optimizer: Adam\n",
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" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"16.35646590590477\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 0\n",
"1.3630388254920642\n",
"The running loss is:\n",
"13.501704521477222\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 1\n",
"1.1251420434564352\n",
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"10.06986141204834\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 2\n",
"0.839155117670695\n",
"The running loss is:\n",
"9.339474618434906\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 3\n",
"0.7782895515362421\n",
"The running loss is:\n",
"8.55732698738575\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 4\n",
"0.7131105822821459\n",
"The running loss is:\n",
"7.9432243257761\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"0.6619353604813417\n",
"The running loss is:\n",
"7.743864074349403\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.6453220061957836\n",
"The running loss is:\n",
"8.010289520025253\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.6675241266687711\n",
"The running loss is:\n",
"8.142023041844368\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.6785019201536974\n",
"The running loss is:\n",
"7.777196206152439\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.6480996838460366\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 8, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"39 30746 ... 0.000000\n",
"40 30747 ... 0.000000\n",
"41 30748 ... 0.000000\n",
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"50 30757 ... 14.083817\n",
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"52 30759 ... 12.242359\n",
"53 30760 ... 13.066635\n",
"54 30761 ... 13.783864\n",
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"56 30763 ... 13.984291\n",
"\n",
"[18 rows x 32 columns]\n"
],
"name": "stdout"
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: ik2lbrgv \n",
"\n",
"wandb: Agent Starting Run: 7774hcks with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 8\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: 7774hcks\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/7774hcks
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" "
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""
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
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" optimizer: Adam\n",
"wandb:\n",
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"\n",
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"13.757839009165764\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 0\n",
"1.2507126371968875\n",
"The running loss is:\n",
"12.586623467504978\n",
"The number of items in train is: \n",
"11\n",
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"1.1442384970459072\n",
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"7.428445756435394\n",
"The number of items in train is: \n",
"11\n",
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"0.6753132505850359\n",
"The running loss is:\n",
"7.001081258058548\n",
"The number of items in train is: \n",
"11\n",
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"0.6364619325507771\n",
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"6.894729509949684\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 4\n",
"0.6267935918136076\n",
"The running loss is:\n",
"6.393982410430908\n",
"The number of items in train is: \n",
"11\n",
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"0.5812711282209917\n",
"The running loss is:\n",
"6.316303074359894\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 6\n",
"0.574209370396354\n",
"The running loss is:\n",
"6.03164541721344\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 7\n",
"0.5483314015648582\n",
"The running loss is:\n",
"6.234783947467804\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 8\n",
"0.5667985406788912\n",
"The running loss is:\n",
"5.846083365380764\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 9\n",
"0.531462124125524\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 8, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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},
{
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"torch.Size([10])\n",
"test_data scale\n",
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},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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{
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"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
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},
{
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"wandb: Agent Finished Run: 7774hcks \n",
"\n",
"wandb: Agent Starting Run: fazaiyk7 with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 8\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
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" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
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"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/fazaiyk7
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
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" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
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" unsqueeze_dim: 1\n",
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" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
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"12\n",
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"6.961419679224491\n",
"The number of items in train is: \n",
"12\n",
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"0.5801183066020409\n",
"The running loss is:\n",
"6.35853485763073\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.5298779048025608\n",
"The running loss is:\n",
"6.827462054789066\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.5689551712324222\n",
"The running loss is:\n",
"6.0002028569579124\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.5000169047464927\n",
"The running loss is:\n",
"5.485427591949701\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.4571189659958084\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 8, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
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{
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"name": "stdout"
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{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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{
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"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: fazaiyk7 \n",
"\n",
"wandb: Agent Starting Run: 1n7vdt7z with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 8\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: 1n7vdt7z\n"
],
"name": "stdout"
},
{
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"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/1n7vdt7z
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 8\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 8\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 8\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 2\n",
" number_time_series: 3\n",
" output_seq_len: 2\n",
" seq_len: 8\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 2\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"13.794403530657291\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 0\n",
"1.1495336275547743\n",
"The running loss is:\n",
"24.844410978257656\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 1\n",
"2.0703675815214715\n",
"The running loss is:\n",
"12.776588022708893\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 2\n",
"1.0647156685590744\n",
"The running loss is:\n",
"11.807799771428108\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 3\n",
"0.9839833142856756\n",
"The running loss is:\n",
"9.790398374199867\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 4\n",
"0.8158665311833223\n",
"The running loss is:\n",
"8.584115162491798\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"0.7153429302076498\n",
"The running loss is:\n",
"8.691331028938293\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.7242775857448578\n",
"The running loss is:\n",
"8.91648381948471\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.7430403182903925\n",
"The running loss is:\n",
"7.640511985868216\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.6367093321556846\n",
"The running loss is:\n",
"7.013014301657677\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.5844178584714731\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 8, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"50 30757 ... 13.174250\n",
"51 30758 ... 13.365698\n",
"52 30759 ... 11.487959\n",
"53 30760 ... 11.916497\n",
"54 30761 ... 11.573297\n",
"55 30762 ... 12.028158\n",
"56 30763 ... 12.942216\n",
"\n",
"[18 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 1n7vdt7z \n",
"\n",
"wandb: Agent Starting Run: mxzlg74h with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 8\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: mxzlg74h\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/mxzlg74h
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 8\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 8\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 8\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 8\n",
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" desc: null\n",
" value: PyTorch\n",
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" desc: null\n",
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"sweep:\n",
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"training_params:\n",
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" batch_size: 3\n",
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" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"10.668571203947067\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 0\n",
"0.9698701094497334\n",
"The running loss is:\n",
"23.13605907559395\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 1\n",
"2.103278097781268\n",
"The running loss is:\n",
"9.648351326584816\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 2\n",
"0.8771228478713469\n",
"The running loss is:\n",
"8.99851730465889\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 3\n",
"0.8180470276962627\n",
"The running loss is:\n",
"7.207675918936729\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 4\n",
"0.6552432653578845\n",
"The running loss is:\n",
"6.6272143721580505\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 5\n",
"0.60247403383255\n",
"The running loss is:\n",
"6.662739872932434\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 6\n",
"0.6057036248120394\n",
"The running loss is:\n",
"6.596592366695404\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 7\n",
"0.5996902151541277\n",
"The running loss is:\n",
"6.8548741936683655\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 8\n",
"0.6231703812425787\n",
"The running loss is:\n",
"6.773262917995453\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 9\n",
"0.615751174363223\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 8, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"39 30746 ... 0.000000\n",
"40 30747 ... 0.000000\n",
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"\n",
"[18 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: mxzlg74h \n",
"\n",
"wandb: Agent Starting Run: 2n0cdb0f with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 8\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: 2n0cdb0f\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/2n0cdb0f
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
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" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 8\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 8\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 8\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
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" seq_len: 8\n",
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" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
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" desc: null\n",
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"sweep:\n",
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" value: true\n",
"training_params:\n",
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" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"11.547422602772713\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 0\n",
"0.9622852168977261\n",
"The running loss is:\n",
"18.635728433728218\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 1\n",
"1.5529773694773514\n",
"The running loss is:\n",
"13.359365157783031\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 2\n",
"1.1132804298152525\n",
"The running loss is:\n",
"8.741095915436745\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 3\n",
"0.7284246596197287\n",
"The running loss is:\n",
"7.996406886726618\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 4\n",
"0.6663672405605515\n",
"The running loss is:\n",
"8.061928812414408\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"0.671827401034534\n",
"The running loss is:\n",
"7.5982563234865665\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.6331880269572139\n",
"The running loss is:\n",
"9.899934113025665\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.8249945094188055\n",
"The running loss is:\n",
"9.39713741093874\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.783094784244895\n",
"The running loss is:\n",
"7.772306106984615\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.6476921755820513\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 8, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
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},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"39 30746 ... 0.000000\n",
"40 30747 ... 0.000000\n",
"41 30748 ... 0.000000\n",
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"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 11.623840\n",
"48 30755 ... 13.129992\n",
"49 30756 ... 15.464817\n",
"50 30757 ... 14.150119\n",
"51 30758 ... 11.621802\n",
"52 30759 ... 11.351404\n",
"53 30760 ... 11.836058\n",
"54 30761 ... 11.804684\n",
"55 30762 ... 12.114832\n",
"56 30763 ... 12.380978\n",
"\n",
"[18 rows x 32 columns]\n"
],
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 2n0cdb0f \n",
"\n",
"wandb: Agent Starting Run: 2l8cqkpb with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 8\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: 2l8cqkpb\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/2l8cqkpb
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" "
],
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""
]
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
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"dataset_params:\n",
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" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 8\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 8\n",
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" desc: null\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
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"sweep:\n",
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" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"11.721733957529068\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 0\n",
"0.9768111631274223\n",
"The running loss is:\n",
"20.882812559604645\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 1\n",
"1.7402343799670537\n",
"The running loss is:\n",
"15.462991893291473\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 2\n",
"1.2885826577742894\n",
"The running loss is:\n",
"10.39606124162674\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 3\n",
"0.8663384368022283\n",
"The running loss is:\n",
"11.118731543421745\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 4\n",
"0.9265609619518121\n",
"The running loss is:\n",
"9.71517413854599\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"0.8095978448788325\n",
"The running loss is:\n",
"9.132946863770485\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.7610789053142071\n",
"The running loss is:\n",
"8.82024759054184\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.7350206325451533\n",
"The running loss is:\n",
"9.627787470817566\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.8023156225681305\n",
"The running loss is:\n",
"9.905424669384956\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.8254520557820797\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 8, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
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"[18 rows x 32 columns]\n"
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"name": "stdout"
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"output_type": "stream",
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"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 2l8cqkpb \n",
"\n",
"wandb: Agent Starting Run: gujj856e with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 8\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
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],
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{
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"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/gujj856e
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"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
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"batch_size:\n",
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" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
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" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
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" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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" desc: null\n",
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" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"11.164023727178574\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 0\n",
"1.0149112479253248\n",
"The running loss is:\n",
"17.79230636358261\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 1\n",
"1.6174823966893284\n",
"The running loss is:\n",
"17.12361752986908\n",
"The number of items in train is: \n",
"11\n",
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"1.5566925027153709\n",
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"9.037766844034195\n",
"The number of items in train is: \n",
"11\n",
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"0.8216151676394723\n",
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"8.182956509292126\n",
"The number of items in train is: \n",
"11\n",
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"0.743905137208375\n",
"The running loss is:\n",
"7.224704436957836\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 5\n",
"0.6567913124507124\n",
"The running loss is:\n",
"7.649267762899399\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 6\n",
"0.6953879784453999\n",
"The running loss is:\n",
"8.003631204366684\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 7\n",
"0.7276028367606077\n",
"The running loss is:\n",
"6.828029468655586\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 8\n",
"0.6207299516959623\n",
"The running loss is:\n",
"6.247038394212723\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 9\n",
"0.5679125812920657\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 8, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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{
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
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{
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"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"52 30759 ... 5.413992\n",
"53 30760 ... 5.787818\n",
"54 30761 ... 3.973889\n",
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"56 30763 ... 7.866238\n",
"\n",
"[18 rows x 32 columns]\n"
],
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"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: gujj856e \n",
"\n",
"wandb: Agent Starting Run: g7si3dxc with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 8\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: g7si3dxc\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/g7si3dxc
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" "
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""
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
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" scaler: StandardScaler\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
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" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
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" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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"wandb:\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"61.024581253528595\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 0\n",
"5.085381771127383\n",
"The running loss is:\n",
"19.56476752460003\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 1\n",
"1.630397293716669\n",
"The running loss is:\n",
"13.355403766036034\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 2\n",
"1.1129503138363361\n",
"The running loss is:\n",
"8.840511664748192\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 3\n",
"0.7367093053956827\n",
"The running loss is:\n",
"11.761417895555496\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 4\n",
"0.980118157962958\n",
"The running loss is:\n",
"7.811135046184063\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"0.6509279205153385\n",
"The running loss is:\n",
"10.606959201395512\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.8839132667829593\n",
"The running loss is:\n",
"10.005793422460556\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.8338161185383797\n",
"The running loss is:\n",
"10.245696619153023\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.8538080515960852\n",
"The running loss is:\n",
"8.148609265685081\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.6790507721404234\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 8, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"Current historical dataframe\n",
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"\n",
"[18 rows x 32 columns]\n"
],
"name": "stdout"
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"output_type": "stream",
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"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
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{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: g7si3dxc \n",
"\n",
"wandb: Agent Starting Run: v0u99efc with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 8\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: v0u99efc\n"
],
"name": "stdout"
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{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/v0u99efc
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 8\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 8\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 8\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 2\n",
" number_time_series: 3\n",
" output_seq_len: 2\n",
" seq_len: 8\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 2\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"51.21212914586067\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 0\n",
"4.267677428821723\n",
"The running loss is:\n",
"17.462961047887802\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 1\n",
"1.4552467539906502\n",
"The running loss is:\n",
"11.688251674175262\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 2\n",
"0.9740209728479385\n",
"The running loss is:\n",
"11.13100489974022\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 3\n",
"0.9275837416450182\n",
"The running loss is:\n",
"13.137617707252502\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 4\n",
"1.0948014756043751\n",
"The running loss is:\n",
"11.458725690841675\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"0.9548938075701395\n",
"The running loss is:\n",
"11.170249596238136\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.9308541330198447\n",
"The running loss is:\n",
"12.042376711964607\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"1.0035313926637173\n",
"The running loss is:\n",
"11.790812149643898\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.9825676791369915\n",
"The running loss is:\n",
"10.290245652198792\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.8575204710165659\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 8, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"39 30746 ... 0.000000\n",
"40 30747 ... 0.000000\n",
"41 30748 ... 0.000000\n",
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"52 30759 ... 9.919448\n",
"53 30760 ... 9.927864\n",
"54 30761 ... 9.905344\n",
"55 30762 ... 9.926155\n",
"56 30763 ... 9.923842\n",
"\n",
"[18 rows x 32 columns]\n"
],
"name": "stdout"
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: v0u99efc \n",
"\n",
"wandb: Agent Starting Run: 1ly9p6oz with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 8\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: 1ly9p6oz\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/1ly9p6oz
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
"tags": []
}
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{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 8\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 8\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 8\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 8\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
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" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"72.31613194942474\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 0\n",
"6.574193813584068\n",
"The running loss is:\n",
"14.23465946316719\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 1\n",
"1.2940599511970172\n",
"The running loss is:\n",
"15.22510826587677\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 2\n",
"1.3841007514433428\n",
"The running loss is:\n",
"9.192183136940002\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 3\n",
"0.8356530124490912\n",
"The running loss is:\n",
"13.560538858175278\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 4\n",
"1.232776259834116\n",
"The running loss is:\n",
"9.145589001476765\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 5\n",
"0.8314171819524332\n",
"The running loss is:\n",
"9.26624071598053\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 6\n",
"0.8423855196345936\n",
"The running loss is:\n",
"8.879170209169388\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 7\n",
"0.8071972917426716\n",
"The running loss is:\n",
"8.084219574928284\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 8\n",
"0.7349290522662076\n",
"The running loss is:\n",
"7.389895915985107\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 9\n",
"0.6718087196350098\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 8, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
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"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"Current historical dataframe\n",
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"52 30759 ... 10.368646\n",
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"54 30761 ... 9.573850\n",
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"\n",
"[18 rows x 32 columns]\n"
],
"name": "stdout"
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 1ly9p6oz \n",
"\n",
"wandb: Agent Starting Run: fpttgkw6 with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 9\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: fpttgkw6\n"
],
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{
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"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/fpttgkw6
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
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" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 9\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 9\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
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" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 9\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
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" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"14.689834764227271\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 0\n",
"1.2241528970189393\n",
"The running loss is:\n",
"17.333957076072693\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 1\n",
"1.4444964230060577\n",
"The running loss is:\n",
"8.697230853140354\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 2\n",
"0.7247692377616962\n",
"The running loss is:\n",
"7.709598541259766\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 3\n",
"0.6424665451049805\n",
"The running loss is:\n",
"7.4310178607702255\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 4\n",
"0.6192514883975188\n",
"The running loss is:\n",
"7.121323108673096\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"0.5934435923894247\n",
"The running loss is:\n",
"7.340858735144138\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.6117382279286782\n",
"The running loss is:\n",
"6.431899104267359\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.5359915920222799\n",
"The running loss is:\n",
"6.767576105892658\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.5639646754910549\n",
"The running loss is:\n",
"5.908991951495409\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.49241599595795077\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 9, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"38 30745 ... 0.000000\n",
"39 30746 ... 0.000000\n",
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"51 30758 ... 14.614594\n",
"52 30759 ... 12.398319\n",
"53 30760 ... 10.582185\n",
"54 30761 ... 11.137925\n",
"55 30762 ... 11.406140\n",
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"\n",
"[19 rows x 32 columns]\n"
],
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{
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"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: fpttgkw6 \n",
"\n",
"wandb: Agent Starting Run: 8l1gnmez with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 9\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: 8l1gnmez\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/8l1gnmez
\n",
" "
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""
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
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" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 9\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
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"forward_params:\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
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" value: MultiAttnHeadSimple\n",
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" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"13.333956763148308\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 0\n",
"1.212177887558937\n",
"The running loss is:\n",
"10.76390040293336\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 1\n",
"0.978536400266669\n",
"The running loss is:\n",
"7.724426813423634\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 2\n",
"0.7022206194021485\n",
"The running loss is:\n",
"6.70024798065424\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 3\n",
"0.6091134527867491\n",
"The running loss is:\n",
"6.150171548128128\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 4\n",
"0.5591065043752844\n",
"The running loss is:\n",
"5.95460768789053\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 5\n",
"0.5413279716264118\n",
"The running loss is:\n",
"5.616045318543911\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 6\n",
"0.5105495744130828\n",
"The running loss is:\n",
"5.45828965306282\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 7\n",
"0.49620815027843823\n",
"The running loss is:\n",
"5.082308158278465\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 8\n",
"0.4620280143889514\n",
"The running loss is:\n",
"5.413075998425484\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 9\n",
"0.49209781803868036\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 9, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
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"52 30759 ... 8.894649\n",
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"\n",
"[19 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 8l1gnmez \n",
"\n",
"wandb: Agent Starting Run: r504iyh8 with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 9\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: r504iyh8\n"
],
"name": "stdout"
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{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/r504iyh8
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 9\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 9\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 9\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 9\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"11.602686673402786\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 0\n",
"1.0547896975820714\n",
"The running loss is:\n",
"22.047383695840836\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 1\n",
"2.004307608712803\n",
"The running loss is:\n",
"8.506498038768768\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 2\n",
"0.7733180035244335\n",
"The running loss is:\n",
"7.987618550658226\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 3\n",
"0.7261471409689296\n",
"The running loss is:\n",
"7.208950437605381\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 4\n",
"0.6553591306913983\n",
"The running loss is:\n",
"6.687433920800686\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 5\n",
"0.6079485382546078\n",
"The running loss is:\n",
"6.712285548448563\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 6\n",
"0.6102077771316875\n",
"The running loss is:\n",
"6.500350695103407\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 7\n",
"0.5909409722821279\n",
"The running loss is:\n",
"6.381061501801014\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 8\n",
"0.5800965001637285\n",
"The running loss is:\n",
"6.392539195716381\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 9\n",
"0.5811399268833074\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 9, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"38 30745 ... 0.000000\n",
"39 30746 ... 0.000000\n",
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"41 30748 ... 0.000000\n",
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"53 30760 ... 4.665875\n",
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"\n",
"[19 rows x 32 columns]\n"
],
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: r504iyh8 \n",
"\n",
"wandb: Agent Starting Run: aw63m4rp with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 9\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: aw63m4rp\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/aw63m4rp
\n",
" "
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""
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{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
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"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 9\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 9\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 9\n",
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" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
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" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"12.29787865281105\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 0\n",
"1.0248232210675876\n",
"The running loss is:\n",
"19.8064456731081\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 1\n",
"1.6505371394256751\n",
"The running loss is:\n",
"11.618107497692108\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 2\n",
"0.9681756248076757\n",
"The running loss is:\n",
"8.902291357517242\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 3\n",
"0.7418576131264368\n",
"The running loss is:\n",
"7.879129042848945\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 4\n",
"0.6565940869040787\n",
"The running loss is:\n",
"6.330558676272631\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"0.5275465563560525\n",
"The running loss is:\n",
"7.807648062705994\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.6506373385588328\n",
"The running loss is:\n",
"7.306606873869896\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.6088839061558247\n",
"The running loss is:\n",
"6.763071320950985\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.5635892767459154\n",
"The running loss is:\n",
"6.004747994244099\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.5003956661870083\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 9, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"Current historical dataframe\n",
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"53 30760 ... 12.368917\n",
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"[19 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: aw63m4rp \n",
"\n",
"wandb: Agent Starting Run: bv5gfbfq with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 9\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: bv5gfbfq\n"
],
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{
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"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/bv5gfbfq
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
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" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
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" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"11.102504268288612\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 0\n",
"1.0093185698444194\n",
"The running loss is:\n",
"19.026846826076508\n",
"The number of items in train is: \n",
"11\n",
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"1.729713347825137\n",
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"9.341200038790703\n",
"The number of items in train is: \n",
"11\n",
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"0.8492000035264275\n",
"The running loss is:\n",
"8.422987721860409\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 3\n",
"0.7657261565327644\n",
"The running loss is:\n",
"6.793850138783455\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 4\n",
"0.617622739889405\n",
"The running loss is:\n",
"6.612731076776981\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 5\n",
"0.6011573706160892\n",
"The running loss is:\n",
"6.01167730987072\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 6\n",
"0.5465161190791563\n",
"The running loss is:\n",
"5.346388012170792\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 7\n",
"0.4860352738337083\n",
"The running loss is:\n",
"5.20254971832037\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 8\n",
"0.4729590653018518\n",
"The running loss is:\n",
"4.780299365520477\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 9\n",
"0.4345726695927707\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 9, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"38 30745 ... 0.000000\n",
"39 30746 ... 0.000000\n",
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"[19 rows x 32 columns]\n"
],
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{
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"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: bv5gfbfq \n",
"\n",
"wandb: Agent Starting Run: 4ui25iwt with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 9\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: 4ui25iwt\n"
],
"name": "stdout"
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{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/4ui25iwt
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""
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
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" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"10.894896239042282\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 0\n",
"0.9904451126402075\n",
"The running loss is:\n",
"24.960272923111916\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 1\n",
"2.2691157202829015\n",
"The running loss is:\n",
"14.597070783376694\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 2\n",
"1.3270064348524266\n",
"The running loss is:\n",
"10.560084193944931\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 3\n",
"0.9600076539949938\n",
"The running loss is:\n",
"8.262078568339348\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 4\n",
"0.7510980516672134\n",
"The running loss is:\n",
"7.327546648681164\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 5\n",
"0.6661406044255603\n",
"The running loss is:\n",
"7.109338231384754\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 6\n",
"0.6463034755804322\n",
"The running loss is:\n",
"6.8406630009412766\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 7\n",
"0.6218784546310251\n",
"The running loss is:\n",
"6.650714844465256\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 8\n",
"0.6046104404059324\n",
"The running loss is:\n",
"6.704959943890572\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 9\n",
"0.609541813080961\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 9, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
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"53 30760 ... 7.191575\n",
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"[19 rows x 32 columns]\n"
],
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},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
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{
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"wandb: Agent Finished Run: 4ui25iwt \n",
"\n",
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"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
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"_wandb:\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
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" desc: null\n",
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" - MSE\n",
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"12\n",
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"The number of items in train is: \n",
"12\n",
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"9.513798125088215\n",
"The number of items in train is: \n",
"12\n",
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"0.7928165104240179\n",
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"9.432423368096352\n",
"The number of items in train is: \n",
"12\n",
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"0.786035280674696\n",
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"7.66383171826601\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.6386526431888342\n",
"The running loss is:\n",
"7.818079452961683\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.6515066210801402\n",
"The running loss is:\n",
"6.671020977199078\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.5559184147665898\n",
"The running loss is:\n",
"6.739705860614777\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.5616421550512314\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 9, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"39 30746 ... 0.000000\n",
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"[19 rows x 32 columns]\n"
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{
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"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
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{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: efkau42q \n",
"\n",
"wandb: Agent Starting Run: yxy354fp with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 9\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
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{
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"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/yxy354fp
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
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" framework: torch\n",
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" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
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"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 9\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 9\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 9\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 2\n",
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" output_seq_len: 2\n",
" seq_len: 9\n",
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" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
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" desc: null\n",
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" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"10.336272045969963\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 0\n",
"0.9396610950881784\n",
"The running loss is:\n",
"18.13731163740158\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 1\n",
"1.6488465124910527\n",
"The running loss is:\n",
"13.977685883641243\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 2\n",
"1.2706987166946584\n",
"The running loss is:\n",
"9.119788710027933\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 3\n",
"0.8290717009116303\n",
"The running loss is:\n",
"8.845211759209633\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 4\n",
"0.8041101599281485\n",
"The running loss is:\n",
"7.916596710681915\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 5\n",
"0.7196906100619923\n",
"The running loss is:\n",
"7.592547062784433\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 6\n",
"0.6902315511622212\n",
"The running loss is:\n",
"6.01723700016737\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 7\n",
"0.5470215454697609\n",
"The running loss is:\n",
"6.154241532087326\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 8\n",
"0.5594765029170297\n",
"The running loss is:\n",
"6.210500963032246\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 9\n",
"0.564590996639295\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 9, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"51 30758 ... 13.010987\n",
"52 30759 ... 12.134022\n",
"53 30760 ... 11.068122\n",
"54 30761 ... 12.273049\n",
"55 30762 ... 9.667723\n",
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"\n",
"[19 rows x 32 columns]\n"
],
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},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: yxy354fp \n",
"\n",
"wandb: Agent Starting Run: x068md6t with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 9\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: x068md6t\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/x068md6t
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
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}
},
{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 9\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 9\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 9\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
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" seq_len: 9\n",
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" desc: null\n",
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" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"19.163715958595276\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 0\n",
"1.742155996235934\n",
"The running loss is:\n",
"15.844000786542892\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 1\n",
"1.4403637078675358\n",
"The running loss is:\n",
"27.519839078187943\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 2\n",
"2.5018035525625404\n",
"The running loss is:\n",
"10.582634881138802\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 3\n",
"0.9620577164671638\n",
"The running loss is:\n",
"11.661602854728699\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 4\n",
"1.0601457140662454\n",
"The running loss is:\n",
"7.782229453325272\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 5\n",
"0.707475404847752\n",
"The running loss is:\n",
"7.696709528565407\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 6\n",
"0.6997008662332188\n",
"The running loss is:\n",
"7.128703862428665\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 7\n",
"0.648063987493515\n",
"The running loss is:\n",
"6.206833004951477\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 8\n",
"0.5642575459046797\n",
"The running loss is:\n",
"6.452411137521267\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 9\n",
"0.5865828306837515\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 9, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"38 30745 ... 0.000000\n",
"39 30746 ... 0.000000\n",
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"53 30760 ... 7.030075\n",
"54 30761 ... 7.186663\n",
"55 30762 ... 6.990386\n",
"56 30763 ... 6.843461\n",
"\n",
"[19 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: x068md6t \n",
"\n",
"wandb: Agent Starting Run: ya3scy4m with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 9\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: ya3scy4m\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/ya3scy4m
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 9\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 9\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 9\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 1\n",
" number_time_series: 3\n",
" output_seq_len: 1\n",
" seq_len: 9\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 1\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"88.53303991630673\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 0\n",
"7.377753326358895\n",
"The running loss is:\n",
"15.117607243359089\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 1\n",
"1.2598006036132574\n",
"The running loss is:\n",
"21.78238356113434\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 2\n",
"1.8151986300945282\n",
"The running loss is:\n",
"9.938564524054527\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 3\n",
"0.8282137103378773\n",
"The running loss is:\n",
"13.54171159863472\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 4\n",
"1.1284759665528934\n",
"The running loss is:\n",
"11.289286583662033\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 5\n",
"0.9407738819718361\n",
"The running loss is:\n",
"10.076805599033833\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 6\n",
"0.839733799919486\n",
"The running loss is:\n",
"9.40070765465498\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 7\n",
"0.7833923045545816\n",
"The running loss is:\n",
"9.233762472867966\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 8\n",
"0.7694802060723305\n",
"The running loss is:\n",
"7.18392214179039\n",
"The number of items in train is: \n",
"12\n",
"The loss for epoch 9\n",
"0.5986601784825325\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 9, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
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},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"38 30745 ... 0.000000\n",
"39 30746 ... 0.000000\n",
"40 30747 ... 0.000000\n",
"41 30748 ... 0.000000\n",
"42 30749 ... 0.000000\n",
"43 30750 ... 0.000000\n",
"44 30751 ... 0.000000\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 18.421427\n",
"48 30755 ... 11.026144\n",
"49 30756 ... 8.737643\n",
"50 30757 ... 17.112108\n",
"51 30758 ... 16.133114\n",
"52 30759 ... 14.757212\n",
"53 30760 ... 12.639726\n",
"54 30761 ... 13.369624\n",
"55 30762 ... 12.039531\n",
"56 30763 ... 11.453431\n",
"\n",
"[19 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: ya3scy4m \n",
"\n",
"wandb: Agent Starting Run: fp8m3p5p with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 9\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: fp8m3p5p\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/fp8m3p5p
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 9\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 9\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 9\n",
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" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
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" seq_len: 9\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
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" desc: null\n",
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" desc: null\n",
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"sweep:\n",
" desc: null\n",
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" epochs: 10\n",
" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"56.73506325483322\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 0\n",
"5.1577330231666565\n",
"The running loss is:\n",
"14.081439599394798\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 1\n",
"1.2801308726722544\n",
"The running loss is:\n",
"11.768588274717331\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 2\n",
"1.069871661337939\n",
"The running loss is:\n",
"11.529130071401596\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 3\n",
"1.0481027337637814\n",
"The running loss is:\n",
"8.909016866236925\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 4\n",
"0.8099106242033568\n",
"The running loss is:\n",
"8.021973967552185\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 5\n",
"0.7292703606865623\n",
"The running loss is:\n",
"7.132795467972755\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 6\n",
"0.6484359516338869\n",
"The running loss is:\n",
"6.869528941810131\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 7\n",
"0.6245026310736482\n",
"The running loss is:\n",
"7.365066081285477\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 8\n",
"0.6695514619350433\n",
"The running loss is:\n",
"7.568959094583988\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 9\n",
"0.6880871904167262\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 9, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"Current historical dataframe\n",
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"38 30745 ... 0.000000\n",
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"53 30760 ... 10.215710\n",
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"\n",
"[19 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
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"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: fp8m3p5p \n",
"\n",
"wandb: Agent Starting Run: nl9f3zyh with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 9\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: nl9f3zyh\n"
],
"name": "stdout"
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{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/nl9f3zyh
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
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" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 9\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 9\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
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" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 9\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
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" value:\n",
" forecast_length: 3\n",
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" output_seq_len: 3\n",
" seq_len: 9\n",
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" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
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" desc: null\n",
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"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"119.16718634963036\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 0\n",
"10.833380577239124\n",
"The running loss is:\n",
"14.289708197116852\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 1\n",
"1.2990643815560774\n",
"The running loss is:\n",
"13.934945285320282\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 2\n",
"1.2668132077563892\n",
"The running loss is:\n",
"16.21449938416481\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 3\n",
"1.4740453985604374\n",
"The running loss is:\n",
"16.993614554405212\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 4\n",
"1.5448740504004739\n",
"The running loss is:\n",
"14.635781586170197\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 5\n",
"1.3305255987427451\n",
"The running loss is:\n",
"11.63321104645729\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 6\n",
"1.0575646405870265\n",
"The running loss is:\n",
"8.882433205842972\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 7\n",
"0.8074939278039065\n",
"The running loss is:\n",
"7.281253471970558\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 8\n",
"0.6619321338155053\n",
"The running loss is:\n",
"7.735475331544876\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 9\n",
"0.7032250301404432\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 9, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"38 30745 ... 0.000000\n",
"39 30746 ... 0.000000\n",
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"50 30757 ... 8.519957\n",
"51 30758 ... 8.564201\n",
"52 30759 ... 8.558195\n",
"53 30760 ... 8.048856\n",
"54 30761 ... 7.787209\n",
"55 30762 ... 7.811332\n",
"56 30763 ... 6.481368\n",
"\n",
"[19 rows x 32 columns]\n"
],
"name": "stdout"
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: nl9f3zyh \n",
"\n",
"wandb: Agent Starting Run: egq37mix with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 10\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: egq37mix\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/egq37mix
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 10\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
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"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 10\n",
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" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
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" seq_len: 10\n",
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" desc: null\n",
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" desc: null\n",
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"sweep:\n",
" desc: null\n",
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" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"13.937215354293585\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 0\n",
"1.267019577663053\n",
"The running loss is:\n",
"12.927820309996605\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 1\n",
"1.1752563918178731\n",
"The running loss is:\n",
"7.380629554390907\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 2\n",
"0.6709663231264461\n",
"The running loss is:\n",
"7.143720369786024\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 3\n",
"0.6494291245260022\n",
"The running loss is:\n",
"6.624908953905106\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 4\n",
"0.6022644503550096\n",
"The running loss is:\n",
"6.404768772423267\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 5\n",
"0.5822517065839334\n",
"The running loss is:\n",
"6.25363489612937\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 6\n",
"0.5685122632844881\n",
"The running loss is:\n",
"5.978661727160215\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 7\n",
"0.5435147024691105\n",
"The running loss is:\n",
"5.826105419546366\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 8\n",
"0.5296459472314878\n",
"The running loss is:\n",
"5.398386839777231\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 9\n",
"0.4907624399797483\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 10, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
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"\n",
"[20 rows x 32 columns]\n"
],
"name": "stdout"
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: egq37mix \n",
"\n",
"wandb: Agent Starting Run: 055yta4y with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 10\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: 055yta4y\n"
],
"name": "stdout"
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{
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"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/055yta4y
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
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" framework: torch\n",
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" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 10\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 10\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 10\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
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" seq_len: 10\n",
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" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
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" desc: null\n",
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" desc: null\n",
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"training_params:\n",
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" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"13.16464938223362\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 0\n",
"1.1967863074757836\n",
"The running loss is:\n",
"14.236513704061508\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 1\n",
"1.2942285185510463\n",
"The running loss is:\n",
"7.635823279619217\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 2\n",
"0.6941657526926561\n",
"The running loss is:\n",
"6.894759684801102\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 3\n",
"0.6267963349819183\n",
"The running loss is:\n",
"6.464241176843643\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 4\n",
"0.5876582888039675\n",
"The running loss is:\n",
"6.639204442501068\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 5\n",
"0.6035640402273699\n",
"The running loss is:\n",
"6.4581106305122375\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 6\n",
"0.5871009664102034\n",
"The running loss is:\n",
"5.75249408185482\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 7\n",
"0.5229540074413473\n",
"The running loss is:\n",
"6.132444128394127\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 8\n",
"0.5574949207631025\n",
"The running loss is:\n",
"5.399658687412739\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 9\n",
"0.49087806249206717\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 10, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"37 30744 ... 0.000000\n",
"38 30745 ... 0.000000\n",
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"50 30757 ... 7.652623\n",
"51 30758 ... 6.561896\n",
"52 30759 ... 6.862144\n",
"53 30760 ... 6.056333\n",
"54 30761 ... 1.668644\n",
"55 30762 ... 1.731342\n",
"56 30763 ... 1.537274\n",
"\n",
"[20 rows x 32 columns]\n"
],
"name": "stdout"
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 055yta4y \n",
"\n",
"wandb: Agent Starting Run: iybnn54g with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 10\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: iybnn54g\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/iybnn54g
\n",
" "
],
"text/plain": [
""
]
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"metadata": {
"tags": []
}
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{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 10\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 10\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 10\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 10\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
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" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"13.125202730298042\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 0\n",
"1.193200248208913\n",
"The running loss is:\n",
"12.032076135277748\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 1\n",
"1.093825103207068\n",
"The running loss is:\n",
"7.3690506517887115\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 2\n",
"0.6699136956171556\n",
"The running loss is:\n",
"6.6424713134765625\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 3\n",
"0.6038610284978693\n",
"The running loss is:\n",
"6.352311864495277\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 4\n",
"0.5774828967722979\n",
"The running loss is:\n",
"6.089945591986179\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 5\n",
"0.553631417453289\n",
"The running loss is:\n",
"6.11835578083992\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 6\n",
"0.5562141618945382\n",
"The running loss is:\n",
"6.080555185675621\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 7\n",
"0.5527777441523292\n",
"The running loss is:\n",
"5.575134560465813\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 8\n",
"0.5068304145878012\n",
"The running loss is:\n",
"5.911937691271305\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 9\n",
"0.5374488810246641\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 10, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"\n",
"[20 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: iybnn54g \n",
"\n",
"wandb: Agent Starting Run: 0c5rtc4t with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 10\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: 0c5rtc4t\n"
],
"name": "stdout"
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{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/0c5rtc4t
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 10\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 10\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 10\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 1\n",
" number_time_series: 3\n",
" output_seq_len: 1\n",
" seq_len: 10\n",
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" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
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" desc: null\n",
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"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"11.56395823508501\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 0\n",
"1.0512689304622738\n",
"The running loss is:\n",
"21.39585980027914\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 1\n",
"1.94507816366174\n",
"The running loss is:\n",
"9.437215507030487\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 2\n",
"0.857928682457317\n",
"The running loss is:\n",
"8.832013815641403\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 3\n",
"0.8029103468764912\n",
"The running loss is:\n",
"7.06958132237196\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 4\n",
"0.6426892111247237\n",
"The running loss is:\n",
"6.77753984183073\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 5\n",
"0.6161399856209755\n",
"The running loss is:\n",
"6.557316467165947\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 6\n",
"0.5961196788332679\n",
"The running loss is:\n",
"6.02478714287281\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 7\n",
"0.5477079220793464\n",
"The running loss is:\n",
"5.408392807468772\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 8\n",
"0.491672073406252\n",
"The running loss is:\n",
"4.902979908511043\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 9\n",
"0.4457254462282766\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 10, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"37 30744 ... 0.000000\n",
"38 30745 ... 0.000000\n",
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"52 30759 ... 8.632397\n",
"53 30760 ... 9.842757\n",
"54 30761 ... 5.808178\n",
"55 30762 ... 5.270340\n",
"56 30763 ... 5.360891\n",
"\n",
"[20 rows x 32 columns]\n"
],
"name": "stdout"
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 0c5rtc4t \n",
"\n",
"wandb: Agent Starting Run: dmof87c1 with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 10\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: dmof87c1\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/dmof87c1
\n",
" "
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""
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
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" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
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"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 10\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
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" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
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" value: 2\n",
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" value: true\n",
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" epochs: 10\n",
" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"11.552351400256157\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 0\n",
"1.0502137636596507\n",
"The running loss is:\n",
"22.925799906253815\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 1\n",
"2.084163627841256\n",
"The running loss is:\n",
"10.040516801178455\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 2\n",
"0.9127742546525869\n",
"The running loss is:\n",
"8.72734984010458\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 3\n",
"0.7933954400095072\n",
"The running loss is:\n",
"7.016648806631565\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 4\n",
"0.6378771642392332\n",
"The running loss is:\n",
"7.162662923336029\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 5\n",
"0.6511511748487299\n",
"The running loss is:\n",
"6.340226337313652\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 6\n",
"0.5763842124830593\n",
"The running loss is:\n",
"6.102388359606266\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 7\n",
"0.5547625781460241\n",
"The running loss is:\n",
"6.945028610527515\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 8\n",
"0.6313662373206832\n",
"The running loss is:\n",
"6.08937419205904\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 9\n",
"0.5535794720053673\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 10, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
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{
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"Current historical dataframe\n",
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"[20 rows x 32 columns]\n"
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"name": "stdout"
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{
"output_type": "stream",
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"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: dmof87c1 \n",
"\n",
"wandb: Agent Starting Run: a607o3ai with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 10\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
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],
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{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/a607o3ai
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
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"batch_size:\n",
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" class: default\n",
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" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
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" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
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" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
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" - MSE\n",
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" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"11.085680603981018\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 0\n",
"1.0077891458164563\n",
"The running loss is:\n",
"20.121261298656464\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 1\n",
"1.829205572605133\n",
"The running loss is:\n",
"9.134558081626892\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 2\n",
"0.8304143710569902\n",
"The running loss is:\n",
"8.571861386299133\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 3\n",
"0.779260126027194\n",
"The running loss is:\n",
"7.1886313408613205\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 4\n",
"0.6535119400783018\n",
"The running loss is:\n",
"6.905544355511665\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 5\n",
"0.6277767595919695\n",
"The running loss is:\n",
"6.2731651067733765\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 6\n",
"0.5702877369793978\n",
"The running loss is:\n",
"6.410836488008499\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 7\n",
"0.5828033170916818\n",
"The running loss is:\n",
"5.631247833371162\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 8\n",
"0.5119316212155602\n",
"The running loss is:\n",
"5.932000920176506\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 9\n",
"0.5392728109251369\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 10, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"37 30744 ... 0.000000\n",
"38 30745 ... 0.000000\n",
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"[20 rows x 32 columns]\n"
],
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{
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"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: a607o3ai \n",
"\n",
"wandb: Agent Starting Run: s2l615c4 with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 10\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: s2l615c4\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/s2l615c4
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""
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{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
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"batch_size:\n",
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"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 10\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
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" optimizer: Adam\n",
"wandb:\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
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"11\n",
"The loss for epoch 0\n",
"1.2654306522824548\n",
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"14.05555833876133\n",
"The number of items in train is: \n",
"11\n",
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"1.2777780307964846\n",
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"The number of items in train is: \n",
"11\n",
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"1.3914601599628276\n",
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"8.069633159786463\n",
"The number of items in train is: \n",
"11\n",
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"0.733603014526042\n",
"The running loss is:\n",
"8.077630437910557\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 4\n",
"0.7343300398100506\n",
"The running loss is:\n",
"7.786269728094339\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 5\n",
"0.7078427025540308\n",
"The running loss is:\n",
"7.286909453570843\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 6\n",
"0.6624463139609857\n",
"The running loss is:\n",
"6.560916505753994\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 7\n",
"0.596446955068545\n",
"The running loss is:\n",
"6.199817832559347\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 8\n",
"0.5636198029599406\n",
"The running loss is:\n",
"6.044604599475861\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 9\n",
"0.54950950904326\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 10, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
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"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
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},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
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{
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"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: s2l615c4 \n",
"\n",
"wandb: Agent Starting Run: 684gik0b with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 10\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
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" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/684gik0b
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
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" class: default\n",
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" interpolate: false\n",
" relevant_cols:\n",
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" scaler: StandardScaler\n",
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" training_path: Colorado_Douglas County.csv\n",
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" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
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" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
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"\n",
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"The number of items in train is: \n",
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"1.2986711670051923\n",
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"The number of items in train is: \n",
"11\n",
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"The running loss is:\n",
"7.985045664012432\n",
"The number of items in train is: \n",
"11\n",
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"0.7259132421829484\n",
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"7.957685396075249\n",
"The number of items in train is: \n",
"11\n",
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"0.7234259450977499\n",
"The running loss is:\n",
"8.26042753458023\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 7\n",
"0.7509479576891119\n",
"The running loss is:\n",
"8.252448678016663\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 8\n",
"0.7502226070924238\n",
"The running loss is:\n",
"5.690807230770588\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 9\n",
"0.5173461118882353\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 10, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
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},
{
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"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
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{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
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{
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"text": [
"Current historical dataframe\n",
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"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 684gik0b \n",
"\n",
"wandb: Agent Starting Run: e8tpi7lb with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 10\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
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{
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"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/e8tpi7lb
\n",
" "
],
"text/plain": [
""
]
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 10\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 10\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 10\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 10\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"12.106163665652275\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 0\n",
"1.100560333241116\n",
"The running loss is:\n",
"15.11037127673626\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 1\n",
"1.3736701160669327\n",
"The running loss is:\n",
"18.565093740820885\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 2\n",
"1.6877357946200804\n",
"The running loss is:\n",
"8.801799945533276\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 3\n",
"0.800163631412116\n",
"The running loss is:\n",
"8.399221360683441\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 4\n",
"0.7635655782439492\n",
"The running loss is:\n",
"8.407545536756516\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 5\n",
"0.7643223215233196\n",
"The running loss is:\n",
"6.584027715027332\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 6\n",
"0.5985479740933939\n",
"The running loss is:\n",
"7.207642734050751\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 7\n",
"0.6552402485500682\n",
"The running loss is:\n",
"6.850147262215614\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 8\n",
"0.6227406602014195\n",
"The running loss is:\n",
"7.071139693260193\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 9\n",
"0.642830881205472\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 10, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"37 30744 ... 0.000000\n",
"38 30745 ... 0.000000\n",
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"49 30756 ... 3.027868\n",
"50 30757 ... 8.111265\n",
"51 30758 ... 10.138385\n",
"52 30759 ... 10.469387\n",
"53 30760 ... 8.697634\n",
"54 30761 ... 7.158179\n",
"55 30762 ... 7.428538\n",
"56 30763 ... 8.332012\n",
"\n",
"[20 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: e8tpi7lb \n",
"\n",
"wandb: Agent Starting Run: d3o40cfk with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 10\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: d3o40cfk\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/d3o40cfk
\n",
" "
],
"text/plain": [
""
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 10\n",
" forecast_length: 1\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 10\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 10\n",
" forecast_length: 1\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 1\n",
" number_time_series: 3\n",
" output_seq_len: 1\n",
" seq_len: 10\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
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" desc: null\n",
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"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"90.30369505286217\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 0\n",
"8.209426822987469\n",
"The running loss is:\n",
"15.560469098389149\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 1\n",
"1.414588099853559\n",
"The running loss is:\n",
"20.279406629502773\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 2\n",
"1.8435824208638885\n",
"The running loss is:\n",
"13.721642754971981\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 3\n",
"1.2474220686338164\n",
"The running loss is:\n",
"9.624975465238094\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 4\n",
"0.8749977695670995\n",
"The running loss is:\n",
"9.650864725932479\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 5\n",
"0.8773513387211345\n",
"The running loss is:\n",
"9.389308098703623\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 6\n",
"0.8535734635185112\n",
"The running loss is:\n",
"8.569266445934772\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 7\n",
"0.7790242223577066\n",
"The running loss is:\n",
"7.809198591858149\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 8\n",
"0.7099271447143771\n",
"The running loss is:\n",
"9.43609918653965\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 9\n",
"0.8578271987763318\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 10, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"38 30745 ... 0.000000\n",
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"\n",
"[20 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: d3o40cfk \n",
"\n",
"wandb: Agent Starting Run: fc1ir6hp with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 10\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: fc1ir6hp\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
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"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/fc1ir6hp
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
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" framework: torch\n",
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" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
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" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
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"forward_params:\n",
" desc: null\n",
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" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 10\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.01\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
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" value: MultiAttnHeadSimple\n",
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" seq_len: 10\n",
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" batch_size: 3\n",
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" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"84.87001064419746\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 0\n",
"7.715455513108861\n",
"The running loss is:\n",
"11.632207192480564\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 1\n",
"1.0574733811345967\n",
"The running loss is:\n",
"20.81926593184471\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 2\n",
"1.8926605392586102\n",
"The running loss is:\n",
"9.084724470973015\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 3\n",
"0.8258840428157286\n",
"The running loss is:\n",
"10.560272850096226\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 4\n",
"0.9600248045542024\n",
"The running loss is:\n",
"10.19235224276781\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 5\n",
"0.9265774766152556\n",
"The running loss is:\n",
"9.287791468203068\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 6\n",
"0.8443446789275516\n",
"The running loss is:\n",
"7.80347640812397\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 7\n",
"0.7094069461930882\n",
"The running loss is:\n",
"9.036721609532833\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 8\n",
"0.8215201463211667\n",
"The running loss is:\n",
"8.998482886701822\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 9\n",
"0.8180438987910748\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 10, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
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},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"37 30744 ... 0.000000\n",
"38 30745 ... 0.000000\n",
"39 30746 ... 0.000000\n",
"40 30747 ... 0.000000\n",
"41 30748 ... 0.000000\n",
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"45 30752 ... 0.000000\n",
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"47 30754 ... 11.811060\n",
"48 30755 ... 11.055724\n",
"49 30756 ... 7.466121\n",
"50 30757 ... 7.228861\n",
"51 30758 ... 12.189958\n",
"52 30759 ... 11.982655\n",
"53 30760 ... 10.075672\n",
"54 30761 ... 8.466732\n",
"55 30762 ... 9.425452\n",
"56 30763 ... 11.071779\n",
"\n",
"[20 rows x 32 columns]\n"
],
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{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: fc1ir6hp \n",
"\n",
"wandb: Agent Starting Run: f1mlp38o with config:\n",
"\tbatch_size: 3\n",
"\tforecast_history: 10\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: f1mlp38o\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/f1mlp38o
\n",
" "
],
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""
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}
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 3\n",
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" desc: null\n",
" value:\n",
" batch_size: 3\n",
" class: default\n",
" forecast_history: 10\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
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" desc: null\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
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" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"67.69290640950203\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 0\n",
"6.153900582682002\n",
"The running loss is:\n",
"9.668513655662537\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 1\n",
"0.8789557868784125\n",
"The running loss is:\n",
"9.981049299240112\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 2\n",
"0.9073681181127374\n",
"The running loss is:\n",
"10.219359934329987\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 3\n",
"0.9290327213027261\n",
"The running loss is:\n",
"11.357643961906433\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 4\n",
"1.0325130874460393\n",
"The running loss is:\n",
"8.35865232348442\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 5\n",
"0.7598774839531292\n",
"The running loss is:\n",
"7.621890068054199\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 6\n",
"0.6928990970958363\n",
"The running loss is:\n",
"8.405842632055283\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 7\n",
"0.7641675120050256\n",
"The running loss is:\n",
"7.759170785546303\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 8\n",
"0.7053791623223912\n",
"The running loss is:\n",
"7.550814151763916\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 9\n",
"0.686437650160356\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 10, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
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"\n",
"[20 rows x 32 columns]\n"
],
"name": "stdout"
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"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
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{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: f1mlp38o \n",
"\n",
"wandb: Agent Starting Run: waidlena with config:\n",
"\tbatch_size: 4\n",
"\tforecast_history: 1\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
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],
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"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/waidlena
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"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
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"batch_size:\n",
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" relevant_cols:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
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" file_path: Colorado_Douglas County.csv\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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" desc: null\n",
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" - MSE\n",
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" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"13.497929081320763\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 0\n",
"1.227084461938251\n",
"The running loss is:\n",
"8.768787369132042\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 1\n",
"0.7971624881029129\n",
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"8.496358714997768\n",
"The number of items in train is: \n",
"11\n",
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"0.7723962468179789\n",
"The running loss is:\n",
"7.1095104441046715\n",
"The number of items in train is: \n",
"11\n",
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"0.6463191312822428\n",
"The running loss is:\n",
"8.59556758403778\n",
"The number of items in train is: \n",
"11\n",
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"0.7814152349125255\n",
"The running loss is:\n",
"7.4800353944301605\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 5\n",
"0.6800032176754691\n",
"The running loss is:\n",
"7.584153085947037\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 6\n",
"0.6894684623588215\n",
"The running loss is:\n",
"8.128714382648468\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 7\n",
"0.7389740347862244\n",
"The running loss is:\n",
"8.35108682513237\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 8\n",
"0.75918971137567\n",
"The running loss is:\n",
"8.158496677875519\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 9\n",
"0.7416815161705017\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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{
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
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{
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"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
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"47 30754 ... 12.112806\n",
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"49 30756 ... 11.945765\n",
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"53 30760 ... 12.966658\n",
"54 30761 ... 12.097885\n",
"55 30762 ... 11.875657\n",
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"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
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"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
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{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: waidlena \n",
"\n",
"wandb: Agent Starting Run: qjfpgo60 with config:\n",
"\tbatch_size: 4\n",
"\tforecast_history: 1\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: qjfpgo60\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/qjfpgo60
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
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" python_version: 3.6.9\n",
"batch_size:\n",
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" relevant_cols:\n",
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" scaler: StandardScaler\n",
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" test_path: Colorado_Douglas County.csv\n",
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" training_path: Colorado_Douglas County.csv\n",
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"forecast_history:\n",
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" - month\n",
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" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
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" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
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"wandb:\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
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"The number of items in train is: \n",
"11\n",
"The loss for epoch 0\n",
"1.7627645839344372\n",
"The running loss is:\n",
"14.094916045665741\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 1\n",
"1.281356004151431\n",
"The running loss is:\n",
"13.58062994480133\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 2\n",
"1.2346027222546665\n",
"The running loss is:\n",
"13.59209805727005\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 3\n",
"1.2356452779336409\n",
"The running loss is:\n",
"13.201426059007645\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 4\n",
"1.2001296417279677\n",
"The running loss is:\n",
"12.879163593053818\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 5\n",
"1.1708330539139835\n",
"The running loss is:\n",
"12.814834147691727\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 6\n",
"1.1649849225174298\n",
"The running loss is:\n",
"12.698356926441193\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 7\n",
"1.1543960842219265\n",
"The running loss is:\n",
"12.411805510520935\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 8\n",
"1.128345955501903\n",
"The running loss is:\n",
"12.614239037036896\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 9\n",
"1.1467490033669905\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
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},
{
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"name": "stdout"
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{
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"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
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"name": "stderr"
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"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 17.735096\n",
"48 30755 ... 21.072258\n",
"49 30756 ... 23.510662\n",
"50 30757 ... 25.371246\n",
"51 30758 ... 26.860338\n",
"52 30759 ... 28.110594\n",
"53 30760 ... 29.207296\n",
"54 30761 ... 28.155012\n",
"55 30762 ... 27.771378\n",
"56 30763 ... 27.817627\n",
"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
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"name": "stderr"
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{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: qjfpgo60 \n",
"\n",
"wandb: Agent Starting Run: szcbpw5m with config:\n",
"\tbatch_size: 4\n",
"\tforecast_history: 1\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
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],
"name": "stdout"
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{
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"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/szcbpw5m
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
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" python_version: 3.6.9\n",
"batch_size:\n",
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" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
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" file_path: Colorado_Douglas County.csv\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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" desc: null\n",
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" - MSE\n",
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" seq_len: 1\n",
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" value: PyTorch\n",
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" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"16.532336503267288\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 0\n",
"1.6532336503267289\n",
"The running loss is:\n",
"11.091062128543854\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 1\n",
"1.1091062128543854\n",
"The running loss is:\n",
"10.856420874595642\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 2\n",
"1.0856420874595643\n",
"The running loss is:\n",
"10.523346066474915\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 3\n",
"1.0523346066474915\n",
"The running loss is:\n",
"10.397574484348297\n",
"The number of items in train is: \n",
"10\n",
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"1.0397574484348298\n",
"The running loss is:\n",
"10.013593643903732\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 5\n",
"1.0013593643903733\n",
"The running loss is:\n",
"9.911922216415405\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 6\n",
"0.9911922216415405\n",
"The running loss is:\n",
"10.10109493136406\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 7\n",
"1.0101094931364059\n",
"The running loss is:\n",
"9.99822461605072\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 8\n",
"0.999822461605072\n",
"The running loss is:\n",
"10.047543227672577\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 9\n",
"1.0047543227672577\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
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{
"output_type": "stream",
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"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
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{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 7.451673\n",
"48 30755 ... 4.557664\n",
"49 30756 ... 2.783484\n",
"50 30757 ... 1.481748\n",
"51 30758 ... 0.379330\n",
"52 30759 ... -0.638998\n",
"53 30760 ... -1.621848\n",
"54 30761 ... 1.282873\n",
"55 30762 ... 1.955114\n",
"56 30763 ... 1.685496\n",
"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
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{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: szcbpw5m \n",
"\n",
"wandb: Agent Starting Run: fqtu6656 with config:\n",
"\tbatch_size: 4\n",
"\tforecast_history: 1\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: fqtu6656\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/fqtu6656
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" "
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""
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
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"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 4\n",
" class: default\n",
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" relevant_cols:\n",
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" scaler: StandardScaler\n",
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" test_path: Colorado_Douglas County.csv\n",
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" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 1\n",
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" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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" desc: null\n",
" value:\n",
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" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"12.279194861650467\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 0\n",
"1.1162904419682242\n",
"The running loss is:\n",
"16.839398562908173\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 1\n",
"1.530854414809834\n",
"The running loss is:\n",
"8.657114937901497\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 2\n",
"0.787010448900136\n",
"The running loss is:\n",
"8.566754624247551\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 3\n",
"0.7787958749315955\n",
"The running loss is:\n",
"8.194050922989845\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 4\n",
"0.7449137202718041\n",
"The running loss is:\n",
"7.402128949761391\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 5\n",
"0.6729208136146719\n",
"The running loss is:\n",
"7.638427227735519\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 6\n",
"0.6944024752486836\n",
"The running loss is:\n",
"7.960539147257805\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 7\n",
"0.7236853770234368\n",
"The running loss is:\n",
"8.493246629834175\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 8\n",
"0.772113329984925\n",
"The running loss is:\n",
"7.924744144082069\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 9\n",
"0.7204312858256426\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 11.971193\n",
"48 30755 ... 11.706475\n",
"49 30756 ... 11.781940\n",
"50 30757 ... 12.008855\n",
"51 30758 ... 12.303199\n",
"52 30759 ... 12.627563\n",
"53 30760 ... 12.965292\n",
"54 30761 ... 11.955740\n",
"55 30762 ... 11.699595\n",
"56 30763 ... 11.778876\n",
"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: fqtu6656 \n",
"\n",
"wandb: Agent Starting Run: 44l5rduh with config:\n",
"\tbatch_size: 4\n",
"\tforecast_history: 1\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: 44l5rduh\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/44l5rduh
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" "
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 4\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 4\n",
" class: default\n",
" forecast_history: 1\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 1\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
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" desc: null\n",
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" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 1\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 2\n",
" number_time_series: 3\n",
" output_seq_len: 2\n",
" seq_len: 1\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 2\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 4\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"18.85647228360176\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 0\n",
"1.7142247530547055\n",
"The running loss is:\n",
"20.30205523967743\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 1\n",
"1.845641385425221\n",
"The running loss is:\n",
"13.520971089601517\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 2\n",
"1.2291791899637743\n",
"The running loss is:\n",
"13.447545528411865\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 3\n",
"1.2225041389465332\n",
"The running loss is:\n",
"12.76877212524414\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 4\n",
"1.1607974659312854\n",
"The running loss is:\n",
"12.522136121988297\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 5\n",
"1.138376011089845\n",
"The running loss is:\n",
"12.232091456651688\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 6\n",
"1.1120083142410626\n",
"The running loss is:\n",
"12.113570183515549\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 7\n",
"1.101233653046868\n",
"The running loss is:\n",
"11.928546637296677\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 8\n",
"1.0844133306633343\n",
"The running loss is:\n",
"11.618478044867516\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 9\n",
"1.0562252768061378\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 16.801399\n",
"48 30755 ... 19.427036\n",
"49 30756 ... 21.332169\n",
"50 30757 ... 22.795780\n",
"51 30758 ... 23.988827\n",
"52 30759 ... 25.016071\n",
"53 30760 ... 25.941715\n",
"54 30761 ... 24.732052\n",
"55 30762 ... 24.286921\n",
"56 30763 ... 24.310295\n",
"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 44l5rduh \n",
"\n",
"wandb: Agent Starting Run: euxxg89q with config:\n",
"\tbatch_size: 4\n",
"\tforecast_history: 1\n",
"\tlr: 0.002\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: euxxg89q\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/euxxg89q
\n",
" "
],
"text/plain": [
""
]
},
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}
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{
"output_type": "stream",
"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 4\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 4\n",
" class: default\n",
" forecast_history: 1\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 1\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 1\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.002\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 1\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
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"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 4\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.002\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"15.137496054172516\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 0\n",
"1.5137496054172517\n",
"The running loss is:\n",
"19.171320110559464\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 1\n",
"1.9171320110559464\n",
"The running loss is:\n",
"10.694960564374924\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 2\n",
"1.0694960564374925\n",
"The running loss is:\n",
"10.60001027584076\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 3\n",
"1.0600010275840759\n",
"The running loss is:\n",
"10.514416992664337\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 4\n",
"1.0514416992664337\n",
"The running loss is:\n",
"9.992541253566742\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 5\n",
"0.9992541253566742\n",
"The running loss is:\n",
"10.011631518602371\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 6\n",
"1.001163151860237\n",
"The running loss is:\n",
"9.713776409626007\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 7\n",
"0.9713776409626007\n",
"The running loss is:\n",
"9.765309482812881\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 8\n",
"0.9765309482812882\n",
"The running loss is:\n",
"9.576499074697495\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 9\n",
"0.9576499074697494\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
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"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
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"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
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{
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
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{
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"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 7.637028\n",
"48 30755 ... 5.024141\n",
"49 30756 ... 3.497705\n",
"50 30757 ... 2.400480\n",
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"52 30759 ... 0.612151\n",
"53 30760 ... -0.222054\n",
"54 30761 ... 2.413519\n",
"55 30762 ... 2.960541\n",
"56 30763 ... 2.682458\n",
"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
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{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: euxxg89q \n",
"\n",
"wandb: Agent Starting Run: 1bqhr29t with config:\n",
"\tbatch_size: 4\n",
"\tforecast_history: 1\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: 1bqhr29t\n"
],
"name": "stdout"
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{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/1bqhr29t
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"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
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" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 4\n",
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" desc: null\n",
" value:\n",
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" scaler: StandardScaler\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
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" file_path: Colorado_Douglas County.csv\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
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" value: MultiAttnHeadSimple\n",
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" seq_len: 1\n",
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" desc: null\n",
" value: PyTorch\n",
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" value: Adam\n",
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" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"10.885171070694923\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 0\n",
"0.9895610064268112\n",
"The running loss is:\n",
"22.15847496688366\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 1\n",
"2.0144068151712418\n",
"The running loss is:\n",
"15.519859187304974\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 2\n",
"1.4108962897549977\n",
"The running loss is:\n",
"9.152763716876507\n",
"11\n",
"The number of items in train is: \n",
"The loss for epoch 3\n",
"0.8320694288069551\n",
"The running loss is:\n",
"8.221307665109634\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 4\n",
"0.7473916059190576\n",
"The running loss is:\n",
"8.884836662560701\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 5\n",
"0.8077124238691546\n",
"The running loss is:\n",
"8.030499786138535\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 6\n",
"0.7300454351035032\n",
"The running loss is:\n",
"8.168342098593712\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 7\n",
"0.7425765544176102\n",
"The running loss is:\n",
"8.518066614866257\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 8\n",
"0.7743696922605688\n",
"The running loss is:\n",
"8.19113241136074\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 9\n",
"0.7446484010327946\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
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{
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"test_data scale\n",
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{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
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{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 11.825364\n",
"48 30755 ... 11.594109\n",
"49 30756 ... 11.774220\n",
"50 30757 ... 12.133711\n",
"51 30758 ... 12.571421\n",
"52 30759 ... 13.043240\n",
"53 30760 ... 13.529931\n",
"54 30761 ... 12.056443\n",
"55 30762 ... 11.694873\n",
"56 30763 ... 11.818159\n",
"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 1bqhr29t \n",
"\n",
"wandb: Agent Starting Run: 2mcqkbzi with config:\n",
"\tbatch_size: 4\n",
"\tforecast_history: 1\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: 2mcqkbzi\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/2mcqkbzi
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
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" desc: null\n",
" value:\n",
" batch_size: 4\n",
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" relevant_cols:\n",
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" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
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" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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" desc: null\n",
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" - MSE\n",
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" seq_len: 1\n",
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" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"16.28933358192444\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 0\n",
"1.4808485074476763\n",
"The running loss is:\n",
"31.518853425979614\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 1\n",
"2.8653503114526924\n",
"The running loss is:\n",
"19.339537233114243\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 2\n",
"1.758139748464931\n",
"The running loss is:\n",
"13.648087859153748\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 3\n",
"1.2407352599230679\n",
"The running loss is:\n",
"12.581658080220222\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 4\n",
"1.1437870982018383\n",
"The running loss is:\n",
"13.421542048454285\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 5\n",
"1.2201401862231167\n",
"The running loss is:\n",
"12.218509554862976\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 6\n",
"1.1107735958966343\n",
"The running loss is:\n",
"11.046258971095085\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 7\n",
"1.004205361008644\n",
"The running loss is:\n",
"10.9622243642807\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 8\n",
"0.9965658512982455\n",
"The running loss is:\n",
"10.555041283369064\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 9\n",
"0.9595492075790059\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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},
{
"output_type": "stream",
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
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{
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"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 16.295586\n",
"48 30755 ... 18.512218\n",
"49 30756 ... 20.077642\n",
"50 30757 ... 21.250025\n",
"51 30758 ... 22.185184\n",
"52 30759 ... 22.977167\n",
"53 30760 ... 23.682737\n",
"54 30761 ... 22.743214\n",
"55 30762 ... 22.403723\n",
"56 30763 ... 22.426382\n",
"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 2mcqkbzi \n",
"\n",
"wandb: Agent Starting Run: xv0nyvna with config:\n",
"\tbatch_size: 4\n",
"\tforecast_history: 1\n",
"\tlr: 0.004\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: xv0nyvna\n"
],
"name": "stdout"
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{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/xv0nyvna
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 4\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 4\n",
" class: default\n",
" forecast_history: 1\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 1\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
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" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 1\n",
" forecast_length: 3\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.004\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 3\n",
" number_time_series: 3\n",
" output_seq_len: 3\n",
" seq_len: 1\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
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" desc: null\n",
" value: 3\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 4\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.004\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"11.87590116262436\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 0\n",
"1.1875901162624358\n",
"The running loss is:\n",
"28.522132337093353\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 1\n",
"2.8522132337093353\n",
"The running loss is:\n",
"15.147392272949219\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 2\n",
"1.5147392272949218\n",
"The running loss is:\n",
"12.158874988555908\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 3\n",
"1.2158874988555908\n",
"The running loss is:\n",
"12.22810235619545\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 4\n",
"1.222810235619545\n",
"The running loss is:\n",
"10.145126044750214\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 5\n",
"1.0145126044750215\n",
"The running loss is:\n",
"10.802199751138687\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 6\n",
"1.0802199751138688\n",
"The running loss is:\n",
"9.540551364421844\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 7\n",
"0.9540551364421844\n",
"The running loss is:\n",
"9.32604005932808\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 8\n",
"0.9326040059328079\n",
"The running loss is:\n",
"8.828394114971161\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 9\n",
"0.8828394114971161\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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{
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 8.527145\n",
"48 30755 ... 6.231841\n",
"49 30756 ... 4.828226\n",
"50 30757 ... 3.789749\n",
"51 30758 ... 2.900795\n",
"52 30759 ... 2.073069\n",
"53 30760 ... 1.270414\n",
"54 30761 ... 3.723977\n",
"55 30762 ... 4.264983\n",
"56 30763 ... 4.022814\n",
"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: xv0nyvna \n",
"\n",
"wandb: Agent Starting Run: l8weyaf1 with config:\n",
"\tbatch_size: 4\n",
"\tforecast_history: 1\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
"wandb: Agent Started Run: l8weyaf1\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/l8weyaf1
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""
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
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" desc: null\n",
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" class: default\n",
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" relevant_cols:\n",
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" - weekday\n",
" scaler: StandardScaler\n",
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" test_path: Colorado_Douglas County.csv\n",
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" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
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" file_path: Colorado_Douglas County.csv\n",
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" relevant_cols:\n",
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" - month\n",
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" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
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" desc: null\n",
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" - MSE\n",
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" forecast_length: 1\n",
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" output_seq_len: 1\n",
" seq_len: 1\n",
"model_type:\n",
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" optim_params:\n",
" lr: 0.01\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"31.63803505897522\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 0\n",
"2.8761850053613838\n",
"The running loss is:\n",
"18.769451931118965\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 1\n",
"1.706313811919906\n",
"The running loss is:\n",
"11.642233811318874\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 2\n",
"1.0583848919380794\n",
"The running loss is:\n",
"10.180661663413048\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 3\n",
"0.9255146966739134\n",
"The running loss is:\n",
"11.987961947917938\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 4\n",
"1.0898147225379944\n",
"The running loss is:\n",
"9.060462906956673\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 5\n",
"0.8236784460869703\n",
"The running loss is:\n",
"9.576754912734032\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 6\n",
"0.8706140829758211\n",
"The running loss is:\n",
"9.787697870284319\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 7\n",
"0.8897907154803927\n",
"The running loss is:\n",
"11.934325933456421\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 8\n",
"1.084938721223311\n",
"The running loss is:\n",
"9.142074868083\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 9\n",
"0.8310977152802728\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
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"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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},
{
"output_type": "stream",
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
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{
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"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 13.001091\n",
"48 30755 ... 12.799424\n",
"49 30756 ... 12.547743\n",
"50 30757 ... 12.283724\n",
"51 30758 ... 12.016661\n",
"52 30759 ... 11.748848\n",
"53 30760 ... 11.480849\n",
"54 30761 ... 12.626358\n",
"55 30762 ... 12.706987\n",
"56 30763 ... 12.524940\n",
"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: l8weyaf1 \n",
"\n",
"wandb: Agent Starting Run: b15ovsca with config:\n",
"\tbatch_size: 4\n",
"\tforecast_history: 1\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: b15ovsca\n"
],
"name": "stdout"
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{
"output_type": "display_data",
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"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/b15ovsca
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
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" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 4\n",
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" class: default\n",
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" interpolate: false\n",
" relevant_cols:\n",
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" scaler: StandardScaler\n",
" target_col:\n",
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" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
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" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
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" file_path: Colorado_Douglas County.csv\n",
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" relevant_cols:\n",
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" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
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" desc: null\n",
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" - MSE\n",
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" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"31.673054099082947\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 0\n",
"2.879368554462086\n",
"The running loss is:\n",
"22.425230860710144\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 1\n",
"2.0386573509736494\n",
"The running loss is:\n",
"16.475321352481842\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 2\n",
"1.4977564865892583\n",
"The running loss is:\n",
"13.716146633028984\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 3\n",
"1.2469224211844532\n",
"The running loss is:\n",
"14.30988696217537\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 4\n",
"1.3008988147432154\n",
"The running loss is:\n",
"10.958332479000092\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 5\n",
"0.9962120435454629\n",
"The running loss is:\n",
"10.916476994752884\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 6\n",
"0.9924069995229895\n",
"The running loss is:\n",
"9.848691046237946\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 7\n",
"0.895335549657995\n",
"The running loss is:\n",
"10.236702859401703\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 8\n",
"0.9306093508547003\n",
"The running loss is:\n",
"9.222264111042023\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 9\n",
"0.8383876464583657\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
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},
{
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"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
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"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 13.620722\n",
"48 30755 ... 13.905069\n",
"49 30756 ... 14.085255\n",
"50 30757 ... 14.233186\n",
"51 30758 ... 14.371129\n",
"52 30759 ... 14.505979\n",
"53 30760 ... 14.639871\n",
"54 30761 ... 14.128526\n",
"55 30762 ... 14.062317\n",
"56 30763 ... 14.133948\n",
"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: b15ovsca \n",
"\n",
"wandb: Agent Starting Run: 5ly0x251 with config:\n",
"\tbatch_size: 4\n",
"\tforecast_history: 1\n",
"\tlr: 0.01\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: 5ly0x251\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/5ly0x251
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
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"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 4\n",
" class: default\n",
" forecast_history: 1\n",
" forecast_length: 3\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 1\n",
"forward_params:\n",
" desc: null\n",
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"inference_params:\n",
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" relevant_cols:\n",
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"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"32.99864113330841\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 0\n",
"3.299864113330841\n",
"The running loss is:\n",
"17.60329395532608\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 1\n",
"1.760329395532608\n",
"The running loss is:\n",
"11.215231776237488\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 2\n",
"1.1215231776237489\n",
"The running loss is:\n",
"12.638816893100739\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 3\n",
"1.263881689310074\n",
"The running loss is:\n",
"10.019712716341019\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 4\n",
"1.0019712716341018\n",
"The running loss is:\n",
"9.607232719659805\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 5\n",
"0.9607232719659805\n",
"The running loss is:\n",
"9.590596705675125\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 6\n",
"0.9590596705675125\n",
"The running loss is:\n",
"8.71025364100933\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 7\n",
"0.8710253641009331\n",
"The running loss is:\n",
"8.37963554263115\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 8\n",
"0.837963554263115\n",
"The running loss is:\n",
"8.494551599025726\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 9\n",
"0.8494551599025726\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 1, 3])\n",
"Add debugging crap below\n"
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"name": "stdout"
},
{
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"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
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"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
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{
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"Un-transforming data\n"
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{
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"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
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{
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" Unnamed: 0 ... preds\n",
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"49 30756 ... 8.310846\n",
"50 30757 ... 7.426092\n",
"51 30758 ... 6.592715\n",
"52 30759 ... 5.778941\n",
"53 30760 ... 4.972645\n",
"54 30761 ... 7.639882\n",
"55 30762 ... 8.161717\n",
"56 30763 ... 7.865005\n",
"\n",
"[11 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 5ly0x251 \n",
"\n",
"wandb: Agent Starting Run: 0atkj0td with config:\n",
"\tbatch_size: 4\n",
"\tforecast_history: 2\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 1\n",
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],
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{
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"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
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"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
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" python_version: 3.6.9\n",
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" scaling: StandardScaler\n",
" target_col:\n",
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" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
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" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
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"\n",
"Torch is using cpu\n",
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"The number of items in train is: \n",
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"The loss for epoch 0\n",
"1.3600851812145927\n",
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"8.476144537329674\n",
"The number of items in train is: \n",
"11\n",
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"0.7705585943026976\n",
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"7.245350956916809\n",
"The number of items in train is: \n",
"11\n",
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"0.658668268810619\n",
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"6.171432768926024\n",
"The number of items in train is: \n",
"11\n",
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"0.5610393426296386\n",
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"6.489634156227112\n",
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"11\n",
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"0.589966741475192\n",
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"6.0105889942497015\n",
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"11\n",
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"0.5464171812954274\n",
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"6.208764992654324\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 6\n",
"0.5644331811503931\n",
"The running loss is:\n",
"6.286208868026733\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 7\n",
"0.5714735334569757\n",
"The running loss is:\n",
"5.633164703845978\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 8\n",
"0.5121058821678162\n",
"The running loss is:\n",
"5.67748536169529\n",
"The number of items in train is: \n",
"11\n",
"The loss for epoch 9\n",
"0.51613503288139\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 2, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
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"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
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{
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"Un-transforming data\n"
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{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 16.709024\n",
"48 30755 ... 21.198261\n",
"49 30756 ... 23.084475\n",
"50 30757 ... 24.721453\n",
"51 30758 ... 25.047770\n",
"52 30759 ... 24.897585\n",
"53 30760 ... 24.002348\n",
"54 30761 ... 27.997509\n",
"55 30762 ... 29.285919\n",
"56 30763 ... 30.621237\n",
"\n",
"[12 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
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"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: 0atkj0td \n",
"\n",
"wandb: Agent Starting Run: yr3r9v0z with config:\n",
"\tbatch_size: 4\n",
"\tforecast_history: 2\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 2\n",
"wandb: Agent Started Run: yr3r9v0z\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to Weights & Biases (Documentation).
\n",
" Project page: https://app.wandb.ai/igodfried/covid-forecast
\n",
" Sweep page: https://app.wandb.ai/igodfried/covid-forecast/sweeps/dmjolbmp
\n",
"Run page: https://app.wandb.ai/igodfried/covid-forecast/runs/yr3r9v0z
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{
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"text": [
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"Using Wandb config:\n",
"wandb_version: 1\n",
"\n",
"GCS:\n",
" desc: null\n",
" value: false\n",
"_wandb:\n",
" desc: null\n",
" value:\n",
" cli_version: 0.8.35\n",
" framework: torch\n",
" is_jupyter_run: true\n",
" is_kaggle_kernel: false\n",
" python_version: 3.6.9\n",
"batch_size:\n",
" desc: null\n",
" value: 4\n",
"dataset_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 4\n",
" class: default\n",
" forecast_history: 2\n",
" forecast_length: 2\n",
" interpolate: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaler: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" test_path: Colorado_Douglas County.csv\n",
" train_end: 45\n",
" training_path: Colorado_Douglas County.csv\n",
" valid_end: 58\n",
" valid_start: 46\n",
" validation_path: Colorado_Douglas County.csv\n",
"forecast_history:\n",
" desc: null\n",
" value: 2\n",
"forward_params:\n",
" desc: null\n",
" value: {}\n",
"inference_params:\n",
" desc: null\n",
" value:\n",
" dataset_params:\n",
" file_path: Colorado_Douglas County.csv\n",
" forecast_history: 2\n",
" forecast_length: 2\n",
" interpolate_param: false\n",
" relevant_cols:\n",
" - new_cases\n",
" - month\n",
" - weekday\n",
" scaling: StandardScaler\n",
" target_col:\n",
" - new_cases\n",
" datetime_start: '2020-04-21'\n",
" decoder_params:\n",
" decoder_function: simple_decode\n",
" unsqueeze_dim: 1\n",
" hours_to_forecast: 10\n",
" test_csv_path: Colorado_Douglas County.csv\n",
"lr:\n",
" desc: null\n",
" value: 0.001\n",
"metrics:\n",
" desc: null\n",
" value:\n",
" - MSE\n",
"model_name:\n",
" desc: null\n",
" value: MultiAttnHeadSimple\n",
"model_params:\n",
" desc: null\n",
" value:\n",
" forecast_length: 2\n",
" number_time_series: 3\n",
" output_seq_len: 2\n",
" seq_len: 2\n",
"model_type:\n",
" desc: null\n",
" value: PyTorch\n",
"optimizer:\n",
" desc: null\n",
" value: Adam\n",
"out_seq_length:\n",
" desc: null\n",
" value: 2\n",
"sweep:\n",
" desc: null\n",
" value: true\n",
"training_params:\n",
" desc: null\n",
" value:\n",
" batch_size: 4\n",
" criterion: MSE\n",
" epochs: 10\n",
" optim_params:\n",
" lr: 0.001\n",
" optimizer: Adam\n",
"wandb:\n",
" desc: null\n",
" value: false\n",
"\n",
"Torch is using cpu\n",
"The running loss is:\n",
"13.673433274030685\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 0\n",
"1.3673433274030686\n",
"The running loss is:\n",
"9.724617719650269\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 1\n",
"0.9724617719650268\n",
"The running loss is:\n",
"8.894245147705078\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 2\n",
"0.8894245147705078\n",
"The running loss is:\n",
"8.056756377220154\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 3\n",
"0.8056756377220153\n",
"The running loss is:\n",
"7.75899001955986\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 4\n",
"0.775899001955986\n",
"The running loss is:\n",
"7.6932626366615295\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 5\n",
"0.769326263666153\n",
"The running loss is:\n",
"7.423785865306854\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 6\n",
"0.7423785865306854\n",
"The running loss is:\n",
"7.368699312210083\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 7\n",
"0.7368699312210083\n",
"The running loss is:\n",
"7.208283305168152\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 8\n",
"0.7208283305168152\n",
"The running loss is:\n",
"6.594608038663864\n",
"The number of items in train is: \n",
"10\n",
"The loss for epoch 9\n",
"0.6594608038663864\n",
"interpolate should be below\n",
"Now loading and scaling Colorado_Douglas County.csv\n",
"CSV Path below\n",
"Colorado_Douglas County.csv\n",
"torch.Size([1, 2, 3])\n",
"Add debugging crap below\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:134: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame.\n",
"Try using .loc[row_indexer,col_indexer] = value instead\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'] = 0\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:135: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor.numpy().tolist()\n",
"/usr/local/lib/python3.6/dist-packages/pandas/core/series.py:1042: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" self._set_with(key, value)\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:59: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df, end_tensor, forecast_history, junk, test_data = infer_on_torch_model(model, **inference_params)\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"torch.Size([10])\n",
"test_data scale\n",
"Un-transforming data\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/content/github_aistream-peelout_flow-forecast/flood_forecast/evaluator.py:67: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" df['preds'][history_length:] = end_tensor_list\n",
"/content/github_aistream-peelout_flow-forecast/flood_forecast/trainer.py:30: SettingWithCopyWarning: \n",
"A value is trying to be set on a copy of a slice from a DataFrame\n",
"\n",
"See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
" test_acc = evaluate_model(trained_model, model_type, params[\"dataset_params\"][\"target_col\"], params[\"metrics\"], params[\"inference_params\"], {})\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"Current historical dataframe\n",
" Unnamed: 0 ... preds\n",
"45 30752 ... 0.000000\n",
"46 30753 ... 0.000000\n",
"47 30754 ... 14.148539\n",
"48 30755 ... 17.949636\n",
"49 30756 ... 19.337902\n",
"50 30757 ... 21.656553\n",
"51 30758 ... 22.667198\n",
"52 30759 ... 23.891888\n",
"53 30760 ... 24.308977\n",
"54 30761 ... 29.522865\n",
"55 30762 ... 30.020037\n",
"56 30763 ... 33.703957\n",
"\n",
"[12 rows x 32 columns]\n"
],
"name": "stdout"
},
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mplexporter/exporter.py:84: UserWarning:\n",
"\n",
"Blended transforms not yet supported. Zoom behavior may not work as expected.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/mpltools.py:368: MatplotlibDeprecationWarning:\n",
"\n",
"\n",
"The is_frame_like function was deprecated in Matplotlib 3.1 and will be removed in 3.3.\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:410: UserWarning:\n",
"\n",
"Bummer! Plotly can currently only draw Line2D objects from matplotlib that are in 'data' coordinates!\n",
"\n",
"/usr/local/lib/python3.6/dist-packages/plotly/matplotlylib/renderer.py:512: UserWarning:\n",
"\n",
"I found a path object that I don't think is part of a bar chart. Ignoring.\n",
"\n"
],
"name": "stderr"
},
{
"output_type": "stream",
"text": [
"wandb: Agent Finished Run: yr3r9v0z \n",
"\n",
"wandb: Agent Starting Run: likqeqie with config:\n",
"\tbatch_size: 4\n",
"\tforecast_history: 2\n",
"\tlr: 0.001\n",
"\toptimizer: Adam\n",
"\tout_seq_length: 3\n",
"wandb: Agent Started Run: likqeqie\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" Logging results to