{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# BentoML Example: PyTorch Fashion MNIST Classification\n", "\n", "\n", "**BentoML makes moving trained ML models to production easy:**\n", "\n", "* Package models trained with **any ML framework** and reproduce them for model serving in production\n", "* **Deploy anywhere** for online API serving or offline batch serving\n", "* High-Performance API model server with *adaptive micro-batching* support\n", "* Central hub for managing models and deployment process via Web UI and APIs\n", "* Modular and flexible design making it *adaptable to your infrastrcuture*\n", "\n", "BentoML is a framework for serving, managing, and deploying machine learning models. It is aiming to bridge the gap between Data Science and DevOps, and enable teams to deliver prediction services in a fast, repeatable, and scalable way.\n", "Before reading this example project, be sure to check out the [Getting started guide](https://github.com/bentoml/BentoML/blob/master/guides/quick-start/bentoml-quick-start-guide.ipynb) to learn about the basic concepts in BentoML.\n", "\n", "This notebook demonstrates how to use BentoML to turn a PyTorch model into a docker image containing a REST API server serving this model, how to use your ML service built with BentoML as a CLI tool, and how to distribute it a pypi package.\n", "\n", "This example was built based on https://github.com/baldassarreFe/zalando-pytorch/blob/master/notebooks/4.0-fb-autoencoder.ipynb, if you are familiar with this, jump start to [Model Serving using BentoML](#Define-ML-service-with-BentoML)\n", "\n", "![Impression](https://www.google-analytics.com/collect?v=1&tid=UA-112879361-3&cid=555&t=event&ec=pytorch&ea=pytorch-fashion-mnist&dt=pytorch-fashion-mnist)" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "%reload_ext autoreload\n", "%autoreload 2\n", "%matplotlib inline" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "!pip install -q bentoml \"torch==1.6.0\" \"torchvision==0.7.0\" \"sklearn>=0.23.2\" \"pillow==7.2.0\" \"pandas>=1.1.1\" \"numpy>=1.16.0\"" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Torch version: 1.4.0\n", "CUDA: True\n" ] } ], "source": [ "import bentoml\n", "import matplotlib.pyplot as plt\n", "\n", "import torch\n", "import torch.nn as nn\n", "import torch.optim as optim\n", "\n", "from torchvision import transforms\n", "from torch.autograd import Variable\n", "\n", "from sklearn.manifold import TSNE\n", "from sklearn.metrics import accuracy_score\n", "\n", "print(\"Torch version: \", torch.__version__)\n", "print(\"CUDA: \", torch.cuda.is_available())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Prepare Dataset" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "PyTorch supports FashionMNIST now, so we can import it directly." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "from torchvision.datasets import FashionMNIST\n", "FASHION_MNIST_CLASSES = ['T-shirt/top', 'Trouser', 'Pullover', 'Dress', 'Coat', 'Sandal', 'Shirt', 'Sneaker', 'Bag', 'Ankle boot']" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Load train and test set in batches of 1000.\n", "\n", "The `28x28` images are scaled up to `29x29` so that combining convolutions and transposed convolutions would not chop off pixels from the reconstructed images." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "batch_size = 1000\n", "\n", "train_dataset = FashionMNIST(\n", " '../data', train=True, download=True, \n", " transform=transforms.Compose([transforms.CenterCrop((29, 29)), transforms.ToTensor()]))\n", "train_loader = torch.utils.data.DataLoader(train_dataset, batch_size=batch_size, shuffle=True)\n", "\n", "test_dataset = FashionMNIST(\n", " '../data', train=False, download=True, \n", " transform=transforms.Compose([transforms.CenterCrop((29, 29)), transforms.ToTensor()]))\n", "test_loader = torch.utils.data.DataLoader(test_dataset, batch_size=batch_size, shuffle=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Unsupervised reconstruction\n", "Note that in this section we'll never use the image labels, the whole training is unsupervised.\n", "\n", "### Autoencoder\n", "The two components of the autoencoder are defined subclassing `nn.Module`, that gives more flexibility than `nn.Sequential`.\n", "\n", "#### Encoder\n", "A series of convolutions with `kernel_size=5` and `stride=2` is used to squeeze the images into a volume of 40x1x1, then a fully connected layer turns this vector in a vector of size `embedding_size`, that can be specified externally.\n", "\n", "#### Decoder\n", "The decoder takes up from where the encoder left, first transforming back the embedding of size `embedding_size` into a volume of size 40x1x1, then applying a series of Transposed Convolutions to yield an image of the same size of the original input.\n", "\n", "At this time we can show some images in this Dataloader." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "class Encoder(nn.Module):\n", " def __init__(self, embedding_size):\n", " super(Encoder, self).__init__()\n", " self.conv1 = nn.Conv2d(1, 10, kernel_size=5, stride=2)\n", " self.conv2 = nn.Conv2d(10, 20, kernel_size=5, stride=2)\n", " self.conv3 = nn.Conv2d(20, 40, kernel_size=5, stride=2)\n", " self.fully = nn.Linear(40, embedding_size)\n", "\n", " def forward(self, x):\n", " # 1x29x29\n", " x = torch.relu(self.conv1(x))\n", " # 10x13x13\n", " x = torch.relu(self.conv2(x))\n", " # 20x5x5\n", " x = torch.relu(self.conv3(x))\n", " # 40x1x1\n", " x = x.view(x.data.shape[0], 40)\n", " # 40\n", " x = self.fully(x)\n", " # output_size\n", " return x\n", "\n", "class Decoder(nn.Module):\n", " def __init__(self, input_size):\n", " super(Decoder, self).__init__()\n", " self.fully = nn.Linear(input_size, 40)\n", " self.conv1 = nn.ConvTranspose2d(40, 20, kernel_size=5, stride=2)\n", " self.conv2 = nn.ConvTranspose2d(20, 10, kernel_size=5, stride=2)\n", " self.conv3 = nn.ConvTranspose2d(10, 1, kernel_size=5, stride=2)\n", " \n", " def forward(self, x):\n", " x = self.fully(x)\n", " x = x.view(x.data.shape[0], 40, 1, 1)\n", " x = torch.relu(self.conv1(x))\n", " x = torch.relu(self.conv2(x))\n", " x = torch.sigmoid(self.conv3(x))\n", " return x" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We are going to use an embedding size of 20, this number has no particular reason, except that it is in the same range of the number of classes. Naively, the network could learn to encode coarse-grained information (i.e. the kind of dress) in half of the embedding vector and then use the other half for fine-grained information." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "embedding_size = 20\n", "encoder = Encoder(embedding_size)\n", "decoder = Decoder(embedding_size)\n", "\n", "autoencoder = nn.Sequential(encoder, decoder)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Sanity check\n", "A 29x29 black and white image passed through the autoencoder should give the same output dimension" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Input\t [1, 1, 29, 29]\n", "Embedding [1, 20]\n", "Output\t [1, 1, 29, 29]\n" ] } ], "source": [ "x = Variable(torch.ones(1, 1, 29, 29))\n", "e = encoder(x)\n", "d = decoder(e)\n", "\n", "print('Input\\t ', list(x.data.shape))\n", "print('Embedding', list(e.data.shape))\n", "print('Output\\t ', list(d.data.shape))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Training" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Epoch 0:\tloss 0.1321\n", "Epoch 1:\tloss 0.0710\n", "Epoch 2:\tloss 0.0438\n", "Epoch 3:\tloss 0.0373\n", "Epoch 4:\tloss 0.0321\n" ] } ], "source": [ "autoencoder.train()\n", "\n", "loss_fn = nn.MSELoss()\n", "optimizer = optim.Adam(autoencoder.parameters())\n", "epoch_loss = []\n", "\n", "for epoch in range(5):\n", " batch_loss = []\n", " for batch_num, (data, _) in enumerate(train_loader):\n", " data = Variable(data)\n", " optimizer.zero_grad()\n", " output = autoencoder(data)\n", " loss = loss_fn(output, data)\n", " loss.backward()\n", " optimizer.step()\n", " batch_loss.append(loss.item())\n", " epoch_loss.append(sum(batch_loss) / len(batch_loss))\n", " print('Epoch {}:\\tloss {:.4f}'.format(epoch, epoch_loss[-1]))" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.plot(epoch_loss)\n", "plt.title('Final value {:.4f}'.format(epoch_loss[-1]))\n", "plt.xlabel('Epoch')\n", "plt.grid(True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Evaluation\n", "\n", "Reconsruction evaluation on a single batch" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Test loss: 0.0295\n" ] } ], "source": [ "autoencoder.eval()\n", "data, targets = next(test_loader.__iter__())\n", "encodings = encoder(Variable(data))\n", "outputs = decoder(encodings)\n", "\n", "print('Test loss: {:.4f}'.format(loss_fn(outputs, Variable(data)).item()))" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, axes = plt.subplots(8, 8, figsize=(16, 16))\n", "axes = axes.ravel()\n", "\n", "zip_these = axes[::2], axes[1::2], data.numpy().squeeze(), outputs.data.numpy().squeeze(), targets\n", "for ax1, ax2, original, reconstructed, target in zip(*zip_these):\n", " ax1.imshow(original, cmap='gray')\n", " ax1.axis('off')\n", " ax1.set_title(FASHION_MNIST_CLASSES[target])\n", " ax2.imshow(reconstructed, cmap='gray')\n", " ax2.axis('off')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Embeddings\n", "\n", "The embeddings are 20-dimensional, t-SNE is used to visualize them as clusters in 2D space.\n", "\n", "Even though the autoencoder learned the embeddings in a completely unsupervised way we can observe the emergence of clusters:\n", "- __shoes__ (sandals, sneakers and ankle boot) are clustered together\n", "- __bags__ form a group on their own (they are the only images with a clear squared-rectangular shape)\n", "- same goes for __trousers__, that form their own group\n", "- all the others are quite mixed together, meaning that the network has learned the concept of _clothes for the upper body_, but is not able to tell a __coat__ from a __pullover__" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "pca = TSNE(n_components=2)\n", "encodings_2 = pca.fit_transform(encodings.data.numpy())\n", "plt.figure(figsize=(10, 10))\n", "for k in range(len(FASHION_MNIST_CLASSES)):\n", " class_indexes = (targets.numpy() == k)\n", " plt.scatter(encodings_2[class_indexes, 0], encodings_2[class_indexes, 1], label=FASHION_MNIST_CLASSES[k])\n", "plt.legend();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Supervised classification\n", "\n", "Once trained in an unsupervised fashion, the encoder module can be used to generate _fashion_ embeddings (see what I did here?), that can then be used to train a simple classifier on the original labels.\n", "\n", "### Model\n", "The weights of the encoder are freezed, so only the classifier will be trained.\n", "\n", "(later on, when the classifier starts performing decently, we could unfreeze them and do some fine-tuning)" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "for param in encoder.parameters():\n", " param.requires_grad = False\n", "\n", "classifier = nn.Sequential(\n", " encoder, \n", " nn.Linear(embedding_size, 15),\n", " nn.ReLU(),\n", " nn.Linear(15, len(FASHION_MNIST_CLASSES)),\n", " nn.LogSoftmax()\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Training" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/opt/conda/envs/bentoml-dev-py36/lib/python3.6/site-packages/torch/nn/modules/container.py:100: UserWarning: Implicit dimension choice for log_softmax has been deprecated. Change the call to include dim=X as an argument.\n", " input = module(input)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Epoch 0:\tloss 2.3179\taccuracy 45.70%\n", "Epoch 1:\tloss 1.2234\taccuracy 59.00%\n", "Epoch 2:\tloss 1.0394\taccuracy 62.90%\n", "Epoch 3:\tloss 0.9558\taccuracy 63.00%\n", "Epoch 4:\tloss 0.9095\taccuracy 68.10%\n" ] } ], "source": [ "classifier.train()\n", "\n", "loss_fn = nn.NLLLoss()\n", "optimizer = optim.Adam([p for p in classifier.parameters() if p.requires_grad])\n", "epoch_loss = []\n", "\n", "for epoch in range(5):\n", " batch_loss = []\n", " for batch_num, (data, targets) in enumerate(train_loader):\n", " data, targets = Variable(data), Variable(targets)\n", " optimizer.zero_grad()\n", " output = classifier(data)\n", " loss = loss_fn(output, targets)\n", " loss.backward()\n", " optimizer.step()\n", " batch_loss.append(loss.item())\n", " epoch_loss.append(sum(batch_loss) / len(batch_loss))\n", " accuracy = accuracy_score(targets.data.numpy(), output.data.numpy().argmax(axis=1))\n", " print('Epoch {}:\\tloss {:.4f}\\taccuracy {:.2%}'.format(epoch, epoch_loss[-1], accuracy))" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.plot(epoch_loss)\n", "plt.title('Final value {:.4f}'.format(epoch_loss[-1]))\n", "plt.xlabel('Epoch')\n", "plt.grid(True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Evaluation\n", "\n", "Reconsruction evaluation on a single batch" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Accuracy: 64.70%\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/opt/conda/envs/bentoml-dev-py36/lib/python3.6/site-packages/torch/nn/modules/container.py:100: UserWarning: Implicit dimension choice for log_softmax has been deprecated. Change the call to include dim=X as an argument.\n", " input = module(input)\n" ] } ], "source": [ "classifier.eval()\n", "data, targets = next(test_loader.__iter__())\n", "outputs = classifier(Variable(data))\n", "log_probs, output_classes = outputs.max(dim=1)\n", "\n", "accuracy = accuracy_score(targets.numpy(), output_classes.data.numpy())\n", "print('Accuracy: {:.2%}'.format(accuracy))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 16, "metadata": { "scrolled": true }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, axex = plt.subplots(8, 8, figsize=(16, 16))\n", "\n", "zip_these = axex.ravel(), log_probs.data.exp(), output_classes.data, targets, data.numpy().squeeze()\n", "for ax, prob, output_class, target, img in zip(*zip_these):\n", " ax.imshow(img, cmap='gray' if output_class == target else 'autumn')\n", " ax.axis('off')\n", " ax.set_title('{} {:.1%}'.format(FASHION_MNIST_CLASSES[output_class], prob))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Define BentoService for model serving" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Overwriting pytorch_fashion_mnist.py\n" ] } ], "source": [ "%%writefile pytorch_fashion_mnist.py\n", "\n", "from typing import BinaryIO, List\n", "\n", "import bentoml\n", "from PIL import Image\n", "import torch\n", "from torchvision import transforms\n", "\n", "from bentoml.frameworks.pytorch import PytorchModelArtifact\n", "from bentoml.adapters import FileInput, JsonOutput\n", "\n", "\n", "FASHION_MNIST_CLASSES = ['T-shirt/top', 'Trouser', 'Pullover', 'Dress', 'Coat',\n", " 'Sandal', 'Shirt', 'Sneaker', 'Bag', 'Ankle boot']\n", "\n", "\n", "@bentoml.env(pip_packages=['torch', 'numpy', 'torchvision', 'scikit-learn'])\n", "@bentoml.artifacts([PytorchModelArtifact('classifier')])\n", "class PyTorchFashionClassifier(bentoml.BentoService):\n", " \n", " @bentoml.utils.cached_property # reuse transformer\n", " def transform(self):\n", " return transforms.Compose([transforms.CenterCrop((29, 29)), transforms.ToTensor()])\n", "\n", " @bentoml.api(input=FileInput(), output=JsonOutput(), batch=True)\n", " def predict(self, file_streams: List[BinaryIO]) -> List[str]:\n", " img_tensors = []\n", " for fs in file_streams:\n", " img = Image.open(fs).convert(mode=\"L\").resize((28, 28))\n", " img_tensors.append(self.transform(img))\n", " outputs = self.artifacts.classifier(torch.stack(img_tensors))\n", " _, output_classes = outputs.max(dim=1)\n", " \n", " return [FASHION_MNIST_CLASSES[output_class] for output_class in output_classes]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Save BentoService\n" ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[2020-09-23 11:40:29,693] WARNING - Using BentoML installed in `editable` model, the local BentoML repository including all code changes will be packaged together with saved bundle created, under the './bundled_pip_dependencies' directory of the saved bundle.\n", "[2020-09-23 11:40:29,733] WARNING - BentoML by default does not include spacy and torchvision package when using PytorchModelArtifact. To make sure BentoML bundle those packages if they are required for your model, either import those packages in BentoService definition file or manually add them via `@env(pip_packages=['torchvision'])` when defining a BentoService\n", "[2020-09-23 11:40:29,734] WARNING - pip package requirement torch already exist\n", "[2020-09-23 11:40:31,270] INFO - Detected non-PyPI-released BentoML installed, copying local BentoML modulefiles to target saved bundle path..\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/opt/conda/envs/bentoml-dev-py36/lib/python3.6/site-packages/setuptools/distutils_patch.py:26: UserWarning: Distutils was imported before Setuptools. This usage is discouraged and may exhibit undesirable behaviors or errors. Please use Setuptools' objects directly or at least import Setuptools first.\n", " \"Distutils was imported before Setuptools. This usage is discouraged \"\n", "/opt/conda/envs/bentoml-dev-py36/lib/python3.6/site-packages/setuptools/dist.py:458: UserWarning: Normalizing '0.9.0.pre+7.g8af1c8b' to '0.9.0rc0+7.g8af1c8b'\n", " warnings.warn(tmpl.format(**locals()))\n", "warning: no previously-included files matching '*~' found anywhere in distribution\n", "warning: no previously-included files matching '*.pyo' found anywhere in distribution\n", "warning: no previously-included files matching '.git' found anywhere in distribution\n", "warning: no previously-included files matching '.ipynb_checkpoints' found anywhere in distribution\n", "warning: no previously-included files matching '__pycache__' found anywhere in distribution\n", "warning: no directories found matching 'bentoml/yatai/web/dist'\n", "no previously-included directories found matching 'e2e_tests'\n", "no previously-included directories found matching 'tests'\n", "no previously-included directories found matching 'benchmark'\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "UPDATING BentoML-0.9.0rc0+7.g8af1c8b/bentoml/_version.py\n", "set BentoML-0.9.0rc0+7.g8af1c8b/bentoml/_version.py to '0.9.0.pre+7.g8af1c8b'\n", "[2020-09-23 11:40:32,018] INFO - BentoService bundle 'PyTorchFashionClassifier:20200923114030_0CC108' saved to: /home/bentoml/bentoml/repository/PyTorchFashionClassifier/20200923114030_0CC108\n" ] } ], "source": [ "# 1) import the custom BentoService defined above\n", "from pytorch_fashion_mnist import PyTorchFashionClassifier\n", "\n", "# 2) `pack` it with required artifacts\n", "bento_svc = PyTorchFashionClassifier()\n", "bento_svc.pack('classifier', classifier)\n", "\n", "# 3) save your BentoSerivce\n", "saved_path = bento_svc.save()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## REST API Model Serving\n", "\n", "\n", "To start a REST API model server with the BentoService saved above, use the bentoml serve command:" ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[2020-09-23 11:42:36,540] INFO - Getting latest version PyTorchFashionClassifier:20200923114030_0CC108\n", "[2020-09-23 11:42:36,541] INFO - Starting BentoML API server in development mode..\n", "[2020-09-23 11:42:37,708] WARNING - Using BentoML installed in `editable` model, the local BentoML repository including all code changes will be packaged together with saved bundle created, under the './bundled_pip_dependencies' directory of the saved bundle.\n", "[2020-09-23 11:42:37,722] WARNING - Saved BentoService bundle version mismatch: loading BentoService bundle create with BentoML version 0.9.0.pre, but loading from BentoML version 0.9.0.pre+7.g8af1c8b\n", "[2020-09-23 11:42:38,187] WARNING - BentoML by default does not include spacy and torchvision package when using PytorchModelArtifact. To make sure BentoML bundle those packages if they are required for your model, either import those packages in BentoService definition file or manually add them via `@env(pip_packages=['torchvision'])` when defining a BentoService\n", "[2020-09-23 11:42:38,188] WARNING - pip package requirement torch already exist\n", " * Serving Flask app \"PyTorchFashionClassifier\" (lazy loading)\n", " * Environment: production\n", "\u001b[31m WARNING: This is a development server. Do not use it in a production deployment.\u001b[0m\n", "\u001b[2m Use a production WSGI server instead.\u001b[0m\n", " * Debug mode: off\n", " * Running on http://127.0.0.1:5000/ (Press CTRL+C to quit)\n", "/opt/conda/envs/bentoml-dev-py36/lib/python3.6/site-packages/torch/nn/modules/container.py:100: UserWarning: Implicit dimension choice for log_softmax has been deprecated. Change the call to include dim=X as an argument.\n", " input = module(input)\n", "[2020-09-23 11:42:50,983] INFO - {'service_name': 'PyTorchFashionClassifier', 'service_version': '20200923114030_0CC108', 'api': 'predict', 'task': {'data': {'name': 'sample_image.png'}, 'task_id': 'bf7a3fda-4130-47b5-9ce7-b9a9baabcfec', 'http_headers': (('Host', '127.0.0.1:5000'), ('User-Agent', 'curl/7.72.0'), ('Content-Length', '133877'), ('Accept', '*/*'), ('Content-Type', 'multipart/form-data; boundary=------------------------2302fdd2ee5a02cc'))}, 'result': {'data': '\"Ankle boot\"', 'http_status': 200, 'http_headers': (('Content-Type', 'application/json'),)}, 'request_id': 'bf7a3fda-4130-47b5-9ce7-b9a9baabcfec'}\n", "127.0.0.1 - - [23/Sep/2020 11:42:50] \"\u001b[37mPOST /predict HTTP/1.1\u001b[0m\" 200 -\n", "^C\n" ] } ], "source": [ "!bentoml serve PyTorchFashionClassifier:latest" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "If you are running this notebook from Google Colab, you can start the dev server with `--run-with-ngrok` option, to gain acccess to the API endpoint via a public endpoint managed by [ngrok](https://ngrok.com/):" ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[2020-09-23 11:41:46,832] INFO - Getting latest version PyTorchFashionClassifier:20200923114030_0CC108\n", "[2020-09-23 11:41:46,833] INFO - Starting BentoML API server in development mode..\n", "[2020-09-23 11:41:47,995] WARNING - Using BentoML installed in `editable` model, the local BentoML repository including all code changes will be packaged together with saved bundle created, under the './bundled_pip_dependencies' directory of the saved bundle.\n", "[2020-09-23 11:41:48,010] WARNING - Saved BentoService bundle version mismatch: loading BentoService bundle create with BentoML version 0.9.0.pre, but loading from BentoML version 0.9.0.pre+7.g8af1c8b\n", "[2020-09-23 11:41:48,473] WARNING - BentoML by default does not include spacy and torchvision package when using PytorchModelArtifact. To make sure BentoML bundle those packages if they are required for your model, either import those packages in BentoService definition file or manually add them via `@env(pip_packages=['torchvision'])` when defining a BentoService\n", "[2020-09-23 11:41:48,474] WARNING - pip package requirement torch already exist\n", " * Serving Flask app \"PyTorchFashionClassifier\" (lazy loading)\n", " * Environment: production\n", "\u001b[31m WARNING: This is a development server. Do not use it in a production deployment.\u001b[0m\n", "\u001b[2m Use a production WSGI server instead.\u001b[0m\n", " * Debug mode: off\n", " * Running on http://127.0.0.1:5000/ (Press CTRL+C to quit)\n", "\u001b7\u001b[?47h\u001b[?1h\u001b=\u0002\u0007\u001b[H\u001b[2J\u001b[m\u001b[38;5;6m\u001b[48;5;16m\u001b[1m\u001b[1;1Hngrok\u001b[m\u001b[38;5;16m\u001b[48;5;16m \u001b[m\u001b[38;5;7m\u001b[48;5;16mby\u001b[m\u001b[38;5;16m\u001b[48;5;16m \u001b[m\u001b[38;5;6m\u001b[48;5;16m\u001b[1m@inconshreveable\u001b[m\u001b[38;5;16m\u001b[48;5;16m \u001b[m\u001b[38;5;7m\u001b[48;5;16m(Ctrl+C to quit)\u001b[m\u001b[38;5;16m\u001b[48;5;16m\u001b[2;1H \u001b[m\u001b[38;5;6m\u001b[48;5;16m\u001b[3;1HSession Status connecting\u001b[m\u001b[38;5;16m\u001b[48;5;16m \u001b[m\u001b[38;5;7m\u001b[48;5;16m\u001b[4;1HVersion 2.3.35\u001b[m\u001b[38;5;16m\u001b[48;5;16m \u001b[m\u001b[38;5;7m\u001b[48;5;16m\u001b[5;1HRegion United States (us)\u001b[m\u001b[38;5;16m\u001b[48;5;16m \u001b[m\u001b[38;5;7m\u001b[48;5;16m\u001b[6;1HWeb Interface http://127.0.0.1:4040\u001b[m\u001b[38;5;16m\u001b[48;5;16m \u001b[7;1H \u001b[m\u001b[38;5;7m\u001b[48;5;16m\u001b[8;1HConnections ttl opn rt1 rt5 p50 p90 \u001b[m\u001b[38;5;16m\u001b[48;5;16m \u001b[m\u001b[38;5;7m\u001b[48;5;16m\u001b[9;1H 0 0 0.00 0.00 0.00 0.00 \u001b[m\u001b[38;5;16m\u001b[48;5;16m \u001b[10;1H \u001b[11;1H \u001b[12;1H \u001b[13;1H \u001b[14;1H \u001b[15;1H \u001b[16;1H \u001b[17;1H \u001b[18;1H \u001b[19;1H \u001b[20;1H \u001b[21;1H \u001b[22;1H \u001b[23;1H \u001b[24;1H /opt/conda/envs/bentoml-dev-py36/lib/python3.6/site-packages/torch/nn/modules/container.py:100: UserWarning: Implicit dimension choice for log_softmax has been deprecated. Change the call to include dim=X as an argument.\n", " input = module(input)\n", "[2020-09-23 11:42:00,516] INFO - {'service_name': 'PyTorchFashionClassifier', 'service_version': '20200923114030_0CC108', 'api': 'predict', 'task': {'data': {'name': 'sample_image.png'}, 'task_id': 'a5ca2ed5-1a5f-444f-a118-ba6f9217db9e', 'http_headers': (('Host', '127.0.0.1:5000'), ('User-Agent', 'curl/7.72.0'), ('Content-Length', '133877'), ('Accept', '*/*'), ('Content-Type', 'multipart/form-data; boundary=------------------------502072ce3c68f738'))}, 'result': {'data': '\"Ankle boot\"', 'http_status': 200, 'http_headers': (('Content-Type', 'application/json'),)}, 'request_id': 'a5ca2ed5-1a5f-444f-a118-ba6f9217db9e'}\n", "127.0.0.1 - - [23/Sep/2020 11:42:00] \"\u001b[37mPOST /predict HTTP/1.1\u001b[0m\" 200 -\n", "Exception in thread Thread-1:\n", "Traceback (most recent call last):\n", " File \"/opt/conda/envs/bentoml-dev-py36/lib/python3.6/threading.py\", line 916, in _bootstrap_inner\n", " self.run()\n", " File \"/opt/conda/envs/bentoml-dev-py36/lib/python3.6/threading.py\", line 1182, in run\n", " self.function(*self.args, **self.kwargs)\n", " File \"/home/bentoml/BentoML/bentoml/utils/flask_ngrok.py\", line 90, in start_ngrok\n", " ngrok_address = _run_ngrok(port)\n", " File \"/home/bentoml/BentoML/bentoml/utils/flask_ngrok.py\", line 47, in _run_ngrok\n", " tunnel_url = j['tunnels'][0]['public_url'] # Do the parsing of the get\n", "IndexError: list index out of range\n", "\n", "\u001b[m\u001b[38;5;2m\u001b[48;5;16m\u001b[3;1HSession Status online\u001b[m\u001b[38;5;16m\u001b[48;5;16m \u001b[m\u001b[38;5;7m\u001b[48;5;16m\u001b[4;1HS\u001b[4;3Hs\u001b[4;9HExpires\u001b[4;31H7 hours, 59 minutes\u001b[5;1HV\u001b[5;3Hrsion\u001b[5;31H2.3.35\u001b[m\u001b[38;5;16m\u001b[48;5;16m \u001b[m\u001b[38;5;7m\u001b[48;5;16m\u001b[6;1HR\u001b[6;3Hgio\u001b[6;7H \u001b[6;31HUnited States (us)\u001b[m\u001b[38;5;16m\u001b[48;5;16m \u001b[m\u001b[38;5;7m\u001b[48;5;16m\u001b[7;1HWeb Interface http://127.0.0.1:4040\u001b[8;1HF\u001b[8;3Hrward\u001b[8;9Hng \u001b[8;31Hh\u001b[8;33Htps://ab6aa3a6575b.ngrok.io\u001b[8;61H-> http://localhost:\u001b[m\u001b[38;5;16m\u001b[48;5;16m\u001b[9;1H \u001b[m\u001b[38;5;7m\u001b[48;5;16m\u001b[10;1HConnections ttl opn rt1 rt5 p50 p90 \u001b[11;1H 0 0 0.00 0.00 0.00 0.00 \u001b[8;35H:/\u001b[8;38Hab6a\u001b[8;43H3a6575b.ngrok.io -> ht\u001b[8;66Hp:/\u001b[8;70Hlocalhost:5\u001b[9;1HForwarding https://ab6aa3a6575b.ngrok.io -> http://localhost:\u001b[m\u001b[38;5;16m\u001b[48;5;16m\u001b[10;1H \u001b[m\u001b[38;5;7m\u001b[48;5;16m\u001b[11;1HConnections\u001b[11;31Httl\u001b[11;39Hopn\u001b[11;47Hrt1 \u001b[11;55Hrt5 \u001b[11;63Hp5\u001b[11;66H \u001b[11;71Hp9\u001b[11;74H \u001b[12;1H 0 0 0.00 0.00 0.00 0.00 [2020-09-23 11:42:02,526] INFO - {'service_name': 'PyTorchFashionClassifier', 'service_version': '20200923114030_0CC108', 'api': 'predict', 'task': {'data': {'name': 'sample_image.png'}, 'task_id': 'e591c974-f161-4bf2-8d4f-22ea8b0b7f80', 'http_headers': (('Host', '127.0.0.1:5000'), ('User-Agent', 'curl/7.72.0'), ('Content-Length', '133877'), ('Accept', '*/*'), ('Content-Type', 'multipart/form-data; boundary=------------------------2577acc72fed9629'))}, 'result': {'data': '\"Ankle boot\"', 'http_status': 200, 'http_headers': (('Content-Type', 'application/json'),)}, 'request_id': 'e591c974-f161-4bf2-8d4f-22ea8b0b7f80'}\n", "127.0.0.1 - - [23/Sep/2020 11:42:02] \"\u001b[37mPOST /predict HTTP/1.1\u001b[0m\" 200 -\n", "\u0002\u0007\u001b[m\u001b[H\u001b[2J\u001b[2J\u001b[?47l\u001b8\u001b[?1l\u001b>\u001b[?1006l\u001b[?1015l\u001b[?1002l\u001b[?1000l" ] } ], "source": [ "!bentoml serve PyTorchFashionClassifier:latest --run-with-ngrok" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Call REST API from a client" ] }, { "attachments": { "image.png": { "image/png": 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" } }, "cell_type": "markdown", "metadata": {}, "source": [ "Sending POST request from termnial:\n", "```bash\n", "curl -X POST \"http://127.0.0.1:5000/predict\" -F image=@sample_image.png\n", "```\n", "\n", "```bash\n", "curl -X POST \"http://127.0.0.1:5000/predict\" -H \"Content-Type: image/png\" --data-binary @sample_image.png\n", "```\n", "\n", "Go visit http://127.0.0.1:5000/ from your browser, click `/predict` -> `Try it out` -> `Choose File` -> `Execute` to sumbit an image from your computer\n", "\n", "![image.png](attachment:image.png)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Containerize model server with Docker\n", "\n", "\n", "One common way of distributing this model API server for production deployment, is via Docker containers. And BentoML provides a convenient way to do that.\n", "\n", "Note that docker is **not available in Google Colab**. You will need to download and run this notebook locally to try out this containerization with docker feature.\n", "\n", "If you already have docker configured, simply run the follow command to product a docker container serving the IrisClassifier prediction service created above:" ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[2020-09-23 11:48:08,611] INFO - Getting latest version PyTorchFashionClassifier:20200923114030_0CC108\n", "\u001b[39mFound Bento: /home/bentoml/bentoml/repository/PyTorchFashionClassifier/20200923114030_0CC108\u001b[0m\n", "[2020-09-23 11:48:08,628] WARNING - Using BentoML installed in `editable` model, the local BentoML repository including all code changes will be packaged together with saved bundle created, under the './bundled_pip_dependencies' directory of the saved bundle.\n", "[2020-09-23 11:48:08,642] WARNING - Saved BentoService bundle version mismatch: loading BentoService bundle create with BentoML version 0.9.0.pre, but loading from BentoML version 0.9.0.pre+7.g8af1c8b\n", "Building Docker image pytorch-fashion-mnist:latest from PyTorchFashionClassifier:latest \n", "-\u001b[39mStep 1/15 : FROM bentoml/model-server:0.9.0.pre-py36\u001b[0m\n", "\u001b[39m ---> 4aac43d10e50\u001b[0m\n", "\u001b[39mStep 2/15 : ARG EXTRA_PIP_INSTALL_ARGS=\u001b[0m\n", "\u001b[39m ---> Using cache\u001b[0m\n", "\u001b[39m ---> 790054f5ad85\u001b[0m\n", "\u001b[39mStep 3/15 : ENV EXTRA_PIP_INSTALL_ARGS $EXTRA_PIP_INSTALL_ARGS\u001b[0m\n", "\u001b[39m ---> Using cache\u001b[0m\n", "\u001b[39m ---> 85b0a1b40542\u001b[0m\n", "\u001b[39mStep 4/15 : COPY environment.yml requirements.txt setup.sh* bentoml-init.sh python_version* /bento/\u001b[0m\n", "\u001b[39m ---> Using cache\u001b[0m\n", "\u001b[39m ---> 402d59d511dd\u001b[0m\n", "\u001b[39mStep 5/15 : WORKDIR /bento\u001b[0m\n", "\u001b[39m ---> Using cache\u001b[0m\n", "\u001b[39m ---> 1c1ac445d3fb\u001b[0m\n", "\u001b[39mStep 6/15 : RUN chmod +x /bento/bentoml-init.sh\u001b[0m\n", "\u001b[39m ---> Using cache\u001b[0m\n", "\u001b[39m ---> 8a52a24d4cce\u001b[0m\n", "\u001b[39mStep 7/15 : RUN if [ -f /bento/bentoml-init.sh ]; then bash -c /bento/bentoml-init.sh; fi\u001b[0m\n", "\u001b[39m ---> Using cache\u001b[0m\n", "\u001b[39m ---> 4b5cabf794af\u001b[0m\n", "\u001b[39mStep 8/15 : COPY . /bento\u001b[0m\n", "\u001b[39m ---> Using cache\u001b[0m\n", "\u001b[39m ---> 28d18e3337dd\u001b[0m\n", "\u001b[39mStep 9/15 : RUN if [ -d /bento/bundled_pip_dependencies ]; then pip install -U bundled_pip_dependencies/* ;fi\u001b[0m\n", "\u001b[39m ---> Using cache\u001b[0m\n", "\u001b[39m ---> e9298aab0108\u001b[0m\n", "\u001b[39mStep 10/15 : ENV PORT 5000\u001b[0m\n", "\u001b[39m ---> Using cache\u001b[0m\n", "\u001b[39m ---> 6198b75aecbb\u001b[0m\n", "\u001b[39mStep 11/15 : EXPOSE $PORT\u001b[0m\n", "\u001b[39m ---> Using cache\u001b[0m\n", "\u001b[39m ---> ca4e3a6bf3e6\u001b[0m\n", "\u001b[39mStep 12/15 : COPY docker-entrypoint.sh /usr/local/bin/\u001b[0m\n", "\u001b[39m ---> Using cache\u001b[0m\n", "\u001b[39m ---> 62bb9d1d6295\u001b[0m\n", "\u001b[39mStep 13/15 : RUN chmod +x /usr/local/bin/docker-entrypoint.sh\u001b[0m\n", "\u001b[39m ---> Using cache\u001b[0m\n", "\u001b[39m ---> 8643f9e6b6f5\u001b[0m\n", "\u001b[39mStep 14/15 : ENTRYPOINT [ \"docker-entrypoint.sh\" ]\u001b[0m\n", "\u001b[39m ---> Using cache\u001b[0m\n", "\u001b[39m ---> 6d0bdfc6d739\u001b[0m\n", "\u001b[39mStep 15/15 : CMD [\"bentoml\", \"serve-gunicorn\", \"/bento\"]\u001b[0m\n", "\u001b[39m ---> Using cache\u001b[0m\n", "\u001b[39m ---> 9c43cb9fcf07\u001b[0m\n", "\u001b[39mSuccessfully built 9c43cb9fcf07\u001b[0m\n", "\u001b[39mSuccessfully tagged pytorch-fashion-mnist:latest\u001b[0m\n", "\u001b[32mFinished building pytorch-fashion-mnist:latest from PyTorchFashionClassifier:latest\u001b[0m\n" ] } ], "source": [ "!bentoml containerize PyTorchFashionClassifier:latest -t pytorch-fashion-mnist:latest" ] }, { "cell_type": "code", "execution_count": 26, "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[2020-09-23 03:48:13,508] INFO - Starting BentoML API server in production mode..\n", "[2020-09-23 03:48:13,728] INFO - get_gunicorn_num_of_workers: 3, calculated by cpu count\n", "[2020-09-23 03:48:13 +0000] [1] [INFO] Starting gunicorn 20.0.4\n", "[2020-09-23 03:48:13 +0000] [1] [INFO] Listening at: http://0.0.0.0:5000 (1)\n", "[2020-09-23 03:48:13 +0000] [1] [INFO] Using worker: sync\n", "[2020-09-23 03:48:13 +0000] [12] [INFO] Booting worker with pid: 12\n", "[2020-09-23 03:48:13 +0000] [13] [INFO] Booting worker with pid: 13\n", "[2020-09-23 03:48:13 +0000] [14] [INFO] Booting worker with pid: 14\n", "[2020-09-23 03:48:14,747] WARNING - Using BentoML not from official PyPI release. In order to find the same version of BentoML when deploying your BentoService, you must set the 'core/bentoml_deploy_version' config to a http/git location of your BentoML fork, e.g.: 'bentoml_deploy_version = git+https://github.com/{username}/bentoml.git@{branch}'\n", "[2020-09-23 03:48:14,767] WARNING - Saved BentoService bundle version mismatch: loading BentoService bundle create with BentoML version 0.9.0.pre, but loading from BentoML version 0.9.0.pre+7.g8af1c8b\n", "[2020-09-23 03:48:14,767] WARNING - Saved BentoService Python version mismatch: loading BentoService bundle created with Python version 3.6.10, but current environment version is 3.6.12.\n", "[2020-09-23 03:48:14,773] WARNING - Using BentoML not from official PyPI release. In order to find the same version of BentoML when deploying your BentoService, you must set the 'core/bentoml_deploy_version' config to a http/git location of your BentoML fork, e.g.: 'bentoml_deploy_version = git+https://github.com/{username}/bentoml.git@{branch}'\n", "[2020-09-23 03:48:14,791] WARNING - Saved BentoService bundle version mismatch: loading BentoService bundle create with BentoML version 0.9.0.pre, but loading from BentoML version 0.9.0.pre+7.g8af1c8b\n", "[2020-09-23 03:48:14,791] WARNING - Saved BentoService Python version mismatch: loading BentoService bundle created with Python version 3.6.10, but current environment version is 3.6.12.\n", "[2020-09-23 03:48:14,864] WARNING - Using BentoML not from official PyPI release. In order to find the same version of BentoML when deploying your BentoService, you must set the 'core/bentoml_deploy_version' config to a http/git location of your BentoML fork, e.g.: 'bentoml_deploy_version = git+https://github.com/{username}/bentoml.git@{branch}'\n", "[2020-09-23 03:48:14,882] WARNING - Saved BentoService bundle version mismatch: loading BentoService bundle create with BentoML version 0.9.0.pre, but loading from BentoML version 0.9.0.pre+7.g8af1c8b\n", "[2020-09-23 03:48:14,883] WARNING - Saved BentoService Python version mismatch: loading BentoService bundle created with Python version 3.6.10, but current environment version is 3.6.12.\n", "[2020-09-23 03:48:15,102] WARNING - BentoML by default does not include spacy and torchvision package when using PytorchModelArtifact. To make sure BentoML bundle those packages if they are required for your model, either import those packages in BentoService definition file or manually add them via `@env(pip_packages=['torchvision'])` when defining a BentoService\n", "[2020-09-23 03:48:15,103] WARNING - pip package requirement torch already exist\n", "[2020-09-23 03:48:15,107] WARNING - BentoML by default does not include spacy and torchvision package when using PytorchModelArtifact. To make sure BentoML bundle those packages if they are required for your model, either import those packages in BentoService definition file or manually add them via `@env(pip_packages=['torchvision'])` when defining a BentoService\n", "[2020-09-23 03:48:15,107] WARNING - pip package requirement torch already exist\n", "[2020-09-23 03:48:15,209] WARNING - BentoML by default does not include spacy and torchvision package when using PytorchModelArtifact. To make sure BentoML bundle those packages if they are required for your model, either import those packages in BentoService definition file or manually add them via `@env(pip_packages=['torchvision'])` when defining a BentoService\n", "[2020-09-23 03:48:15,209] WARNING - pip package requirement torch already exist\n", "^C\n", "[2020-09-23 03:49:53 +0000] [1] [INFO] Handling signal: int\n", "[2020-09-23 03:49:53 +0000] [12] [INFO] Worker exiting (pid: 12)\n", "[2020-09-23 03:49:53 +0000] [14] [INFO] Worker exiting (pid: 14)\n", "[2020-09-23 03:49:53 +0000] [13] [INFO] Worker exiting (pid: 13)\n" ] } ], "source": [ "!docker run -p 5000:5000 pytorch-fashion-mnist" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Launch inference job from CLI\n", "\n", "BentoML cli supports loading and running a packaged model from CLI. With the DataframeInput adapter, the CLI command supports reading input Dataframe data from CLI argument or local csv or json files:" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[2020-09-23 11:57:28,103] INFO - Getting latest version PyTorchFashionClassifier:20200923114030_0CC108\n", "[2020-09-23 11:57:28,167] WARNING - Using BentoML installed in `editable` model, the local BentoML repository including all code changes will be packaged together with saved bundle created, under the './bundled_pip_dependencies' directory of the saved bundle.\n", "[2020-09-23 11:57:28,182] WARNING - Saved BentoService bundle version mismatch: loading BentoService bundle create with BentoML version 0.9.0.pre, but loading from BentoML version 0.9.0.pre+7.g8af1c8b\n", "[2020-09-23 11:57:28,646] WARNING - BentoML by default does not include spacy and torchvision package when using PytorchModelArtifact. To make sure BentoML bundle those packages if they are required for your model, either import those packages in BentoService definition file or manually add them via `@env(pip_packages=['torchvision'])` when defining a BentoService\n", "[2020-09-23 11:57:28,647] WARNING - pip package requirement torch already exist\n", "/opt/conda/envs/bentoml-dev-py36/lib/python3.6/site-packages/torch/nn/modules/container.py:100: UserWarning: Implicit dimension choice for log_softmax has been deprecated. Change the call to include dim=X as an argument.\n", " input = module(input)\n", "[2020-09-23 11:57:28,711] INFO - {'service_name': 'PyTorchFashionClassifier', 'service_version': '20200923114030_0CC108', 'api': 'predict', 'task': {'data': {'uri': 'file:///home/bentoml/lab/gallery/pytorch/fashion-mnist/sample_image.png', 'name': 'sample_image.png'}, 'task_id': 'a02ae2b7-2fb7-4880-87ea-ac9f53878c1b', 'cli_args': ('--input-file', 'sample_image.png')}, 'result': {'data': '\"Ankle boot\"', 'http_status': 200, 'http_headers': (('Content-Type', 'application/json'),)}, 'request_id': 'a02ae2b7-2fb7-4880-87ea-ac9f53878c1b'}\n", "\"Ankle boot\"\n" ] } ], "source": [ "!bentoml run PyTorchFashionClassifier:latest predict --input-file sample_image.png" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Deployment Options\n", "\n", "If you are at a small team with limited engineering or DevOps resources, try out automated deployment with BentoML CLI, currently supporting AWS Lambda, AWS SageMaker, and Azure Functions:\n", "- [AWS Lambda Deployment Guide](https://docs.bentoml.org/en/latest/deployment/aws_lambda.html)\n", "- [AWS SageMaker Deployment Guide](https://docs.bentoml.org/en/latest/deployment/aws_sagemaker.html)\n", "- [Azure Functions Deployment Guide](https://docs.bentoml.org/en/latest/deployment/azure_functions.html)\n", "\n", "If the cloud platform you are working with is not on the list above, try out these step-by-step guide on manually deploying BentoML packaged model to cloud platforms:\n", "- [AWS ECS Deployment](https://docs.bentoml.org/en/latest/deployment/aws_ecs.html)\n", "- [Google Cloud Run Deployment](https://docs.bentoml.org/en/latest/deployment/google_cloud_run.html)\n", "- [Azure container instance Deployment](https://docs.bentoml.org/en/latest/deployment/azure_container_instance.html)\n", "- [Heroku Deployment](https://docs.bentoml.org/en/latest/deployment/heroku.html)\n", "\n", "Lastly, if you have a DevOps or ML Engineering team who's operating a Kubernetes or OpenShift cluster, use the following guides as references for implementating your deployment strategy:\n", "- [Kubernetes Deployment](https://docs.bentoml.org/en/latest/deployment/kubernetes.html)\n", "- [Knative Deployment](https://docs.bentoml.org/en/latest/deployment/knative.html)\n", "- [Kubeflow Deployment](https://docs.bentoml.org/en/latest/deployment/kubeflow.html)\n", "- [KFServing Deployment](https://docs.bentoml.org/en/latest/deployment/kfserving.html)\n", "- [Clipper.ai Deployment Guide](https://docs.bentoml.org/en/latest/deployment/clipper.html)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.3" } }, "nbformat": 4, "nbformat_minor": 4 }