2. Training.ipynb

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   "source": [
    "## Reading Dataset"
   ]
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   "source": [
    "from utils.agent import *\n",
    "from utils.dataset import read_voc_dataset\n",
    "from IPython.display import clear_output\n",
    "import tqdm.notebook as tq\n",
    "import time\n",
    "%reload_ext autoreload\n",
    "%autoreload 2"
   ]
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   "source": [
    "train_loader2007, val_loader2007 = read_voc_dataset(path=\".\" ,year='2007')\n",
    "train_loader2012, val_loader2012 = read_voc_dataset(path=\".\" ,year='2012')"
   ]
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   "source": [
    "## Dataset Organization"
   ]
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    "#put datalist in list in case of combination of different datasets\n",
    "#For example: [train_loader2007, train_loader2012]\n",
    "datasets_per_class = sort_class_extract([train_loader2007, val_loader2007, train_loader2012, val_loader2012])"
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    "## Training Loop"
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     "text": [
      "Classe cat...\n",
      "Episode 0\n",
      "Saved\n",
      "Complete\n",
      "Episode 1\n",
      "Saved\n",
      "Complete\n",
      "Episode 2\n",
      "Saved\n",
      "Complete\n",
      "Episode 3\n",
      "Saved\n",
      "Complete\n",
      "Episode 4\n",
      "Saved\n",
      "Complete\n",
      "Episode 5\n",
      "Saved\n",
      "Complete\n",
      "Episode 6\n",
      "Saved\n",
      "Complete\n",
      "Episode 7\n",
      "Saved\n",
      "Complete\n",
      "Episode 8\n",
      "Saved\n",
      "Complete\n",
      "Episode 9\n",
      "Saved\n",
      "Complete\n",
      "Episode 10\n",
      "Saved\n",
      "Complete\n",
      "Episode 11\n",
      "Saved\n",
      "Complete\n",
      "Episode 12\n",
      "Saved\n",
      "Complete\n",
      "Episode 13\n",
      "Saved\n",
      "Complete\n",
      "Episode 14\n",
      "Saved\n",
      "Complete\n"
     ]
    },
    {
     "ename": "TypeError",
     "evalue": "unsupported operand type(s) for -: 'builtin_function_or_method' and 'float'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-6-9d62e6090bd1>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      8\u001b[0m     \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcuda\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mempty_cache\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      9\u001b[0m \u001b[0mend\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 10\u001b[0;31m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mend\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0mstart\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m: unsupported operand type(s) for -: 'builtin_function_or_method' and 'float'"
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   "source": [
    "start = time.time()\n",
    "for i in tq.tqdm(range(len(classes))):\n",
    "    classe = classes[i]\n",
    "    print(\"Classe \"+str(classe)+\"...\")\n",
    "    agent = Agent(classe, alpha=0.2, num_episodes=15, load=False, model_name='vgg16')\n",
    "    agent.train(datasets_per_class[classe])\n",
    "    del agent\n",
    "    torch.cuda.empty_cache()\n",
    "end = time.time\n",
    "print(end-start)"
   ]
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