{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "%reload_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from fastai.learner import *\n",
    "from fastai.dataset import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = np.array([[0.,0.], [0,1], [1,0], [1,1]])\n",
    "y = np.array([0,1,1,0])\n",
    "data = (X,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "md = ImageClassifierData.from_arrays('.', data, data, bs=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "learn = Learner.from_model_data(SimpleNet([2, 10, 2]), md)\n",
    "learn.crit = nn.CrossEntropyLoss()\n",
    "learn.opt_fn = optim.SGD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "model_id": "4858fda4b41c4982b98d59cbfdab0ce1",
       "version_major": 2,
       "version_minor": 0
      },
      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>HBox</code>.</p>\n",
       "<p>\n",
       "  If you're reading this message in the Jupyter Notebook or JupyterLab Notebook, it may mean\n",
       "  that the widgets JavaScript is still loading. If this message persists, it\n",
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       "  Widgets Documentation</a> for setup instructions.\n",
       "</p>\n",
       "<p>\n",
       "  If you're reading this message in another frontend (for example, a static\n",
       "  rendering on GitHub or <a href=\"https://nbviewer.jupyter.org/\">NBViewer</a>),\n",
       "  it may mean that your frontend doesn't currently support widgets.\n",
       "</p>\n"
      ],
      "text/plain": [
       "HBox(children=(IntProgress(value=0, description='Epoch', max=30), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch      trn_loss   val_loss   accuracy                                                                              \n",
      "    0      0.703408   0.686116   0.5       \n",
      "    1      0.694675   0.680413   0.5                                                                                   \n",
      "    2      0.689824   0.672467   0.5                                                                                   \n",
      "    3      0.685353   0.6662     0.75                                                                                  \n",
      "    4      0.681366   0.656064   0.75                                                                                  \n",
      "    5      0.676933   0.645323   0.75                                                                                  \n",
      "    6      0.672139   0.634129   0.75                                                                                  \n",
      "    7      0.667045   0.614466   1.0                                                                                   \n",
      "    8      0.66072    0.59939    0.75                                                                                  \n",
      "    9      0.654014   0.579936   0.75                                                                                  \n",
      "    10     0.646579   0.552088   1.0                                                                                   \n",
      "    11     0.637801   0.547516   0.75                                                                                  \n",
      "    12     0.629983   0.531916   1.0                                                                                   \n",
      "    13     0.622022   0.483599   0.75                                                                                  \n",
      "    14     0.611432   0.464332   1.0                                                                                   \n",
      "    15     0.600781   0.439199   1.0                                                                                   \n",
      "    16     0.589663   0.439463   1.0                                                                                   \n",
      "    17     0.57981    0.3815     1.0                                                                                   \n",
      "    18     0.567367   0.345051   1.0                                                                                   \n",
      "    19     0.553991   0.324375   1.0                                                                                   \n",
      "    20     0.540708   0.295096   1.0                                                                                   \n",
      "    21     0.527019   0.266743   1.0                                                                                   \n",
      "    22     0.513012   0.237544   1.0                                                                                   \n",
      "    23     0.498673   0.230024   1.0                                                                                   \n",
      "    24     0.485123   0.199286   1.0                                                                                   \n",
      "    25     0.471132   0.196474   1.0                                                                                   \n",
      "    26     0.458067   0.200001   1.0                                                                                   \n",
      "    27     0.44612    0.152343   1.0                                                                                   \n",
      "    28     0.432868   0.143447   1.0                                                                                   \n",
      "    29     0.420133   0.126178   1.0                                                                                   \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[0.12617818, 1.0]"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "learn.fit(1., 30, metrics=[accuracy])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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