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  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "7ec1278b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os \n",
    "os.environ[\"OMP_NUM_THREADS\"] = \"1\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e6b48302",
   "metadata": {},
   "outputs": [],
   "source": [
    "from fastai.vision.all import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "4af2b248",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/danielching/miniforge3/envs/fastai/lib/python3.10/site-packages/fastbook/__init__.py:11: UserWarning: Missing `ipywidgets` - please install it\n",
      "  except ModuleNotFoundError: warn(\"Missing `ipywidgets` - please install it\")\n"
     ]
    }
   ],
   "source": [
    "import fastbook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9b33221c",
   "metadata": {},
   "outputs": [],
   "source": [
    "from fastbook import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "59089808",
   "metadata": {},
   "outputs": [],
   "source": [
    "fastbook.setup_book()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0f5c2587",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading a new version of this dataset...\n"
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       "      100.00% [811712512/811706944 01:51&lt;00:00]\n",
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     "text": [
      "/Users/danielching/miniforge3/envs/fastai/lib/python3.10/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.\n",
      "  warnings.warn(\n",
      "/Users/danielching/miniforge3/envs/fastai/lib/python3.10/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=ResNet34_Weights.IMAGENET1K_V1`. You can also use `weights=ResNet34_Weights.DEFAULT` to get the most up-to-date weights.\n",
      "  warnings.warn(msg)\n",
      "Downloading: \"https://download.pytorch.org/models/resnet34-b627a593.pth\" to /Users/danielching/.cache/torch/hub/checkpoints/resnet34-b627a593.pth\n",
      "100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 83.3M/83.3M [00:09<00:00, 8.84MB/s]\n"
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       "\n",
       "<style>\n",
       "    /* Turns off some styling */\n",
       "    progress {\n",
       "        /* gets rid of default border in Firefox and Opera. */\n",
       "        border: none;\n",
       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
       "        background-size: auto;\n",
       "    }\n",
       "    progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
       "        background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
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       "    \n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: left;\">\n",
       "      <th>epoch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>valid_loss</th>\n",
       "      <th>error_rate</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
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       "</table><p>\n",
       "\n",
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       "      68.48% [63/92 10:03&lt;04:37 0.2883]\n",
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   ],
   "source": [
    "from fastai.vision.all import *\n",
    "path = untar_data(URLs.PETS)/'images'\n",
    "\n",
    "def is_cat(x): return x[0].isupper()\n",
    "dls = ImageDataLoaders.from_name_func(\n",
    "    path, get_image_files(path), valid_pct=0.2, seed=42,\n",
    "    label_func=is_cat, item_tfms=Resize(224))\n",
    "\n",
    "learn = vision_learner(dls, resnet34, metrics=error_rate)\n",
    "learn.fine_tune(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "05c39c1e",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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