gen_pic.ipynb

{
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    {
     "ename": "ModuleNotFoundError",
     "evalue": "No module named 'models'",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-3-f92040c6d9c9>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     10\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mmath\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     11\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0msys\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 12\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mmodels\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     13\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     14\u001b[0m \u001b[0mmodel_path\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'netG.pth'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'models'"
     ],
     "output_type": "error"
    }
   ],
   "source": [
    "from __future__ import print_function\n",
    "from PIL import Image\n",
    "import random\n",
    "import torch\n",
    "import numpy\n",
    "import torchvision.utils as vutils\n",
    "from torch.autograd import Variable\n",
    "import torchvision.transforms\n",
    "import hashlib\n",
    "import math\n",
    "import sys\n",
    "import models\n",
    "\n",
    "model_path = 'netG.pth'\n",
    "netG = models._netG_1(2, 100, 3, 64, 1) # ngpu, nz, nc, ngf, n_extra_layers\n",
    "netG.load_state_dict(torch.load(model_path, map_location=lambda storage, loc: storage))\n",
    "print(netG)\n",
    "\n",
    "sqrt2pi = 2.5066282746310002 # sqrt(pi * 2)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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