exercise_810.ipynb

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    "# Pulling Down MNIST Training Data\n",
    "\n",
    "This program pulls down MNIST data and stores it in the **data/mnist** folder under the current directory.\n",
    "\n",
    "Please make sure that you have a **data/mnist** directory present."
   ]
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      "Label = tensor(5)\n",
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      "00 00 00 00 00 00 00 00 00 02 03 03 05 11 17 20 25 25 20 12 06 03 00 00 00 00 00 00 00 00 00 00\n",
      "00 00 00 00 00 00 00 00 01 12 17 18 21 25 25 25 25 25 25 25 22 13 01 00 00 00 00 00 00 00 00 00\n",
      "00 00 00 00 00 00 00 00 05 21 24 24 25 25 25 25 25 25 25 25 25 20 07 00 00 00 00 00 00 00 00 00\n",
      "00 00 00 00 00 00 00 00 06 22 25 25 25 25 25 24 20 22 20 17 17 17 08 00 00 00 00 00 00 00 00 00\n",
      "00 00 00 00 00 00 00 00 03 21 25 25 25 22 15 10 06 06 06 04 04 05 02 00 00 00 00 00 00 00 00 00\n",
      "00 00 00 00 00 00 00 00 01 17 24 25 25 21 09 02 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00\n",
      "00 00 00 00 00 00 00 00 00 09 20 24 25 22 14 03 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00\n",
      "00 00 00 00 00 00 00 00 00 02 12 20 24 25 22 13 08 02 00 00 00 00 00 00 00 00 00 00 00 00 00 00\n",
      "00 00 00 00 00 00 00 00 00 00 02 11 21 24 25 25 23 11 05 02 00 00 00 00 00 00 00 00 00 00 00 00\n",
      "00 00 00 00 00 00 00 00 00 00 00 02 09 20 25 25 25 25 19 09 03 00 00 00 00 00 00 00 00 00 00 00\n",
      "00 00 00 00 00 00 00 00 00 00 00 00 00 07 21 25 25 25 24 23 17 08 00 00 00 00 00 00 00 00 00 00\n",
      "00 00 00 00 00 00 00 00 00 00 00 00 00 01 05 13 22 25 25 25 23 15 03 00 00 00 00 00 00 00 00 00\n",
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      "00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 02 15 24 25 23 12 00 00 00 00 00 00 00 00\n",
      "00 00 00 00 00 00 00 00 00 00 00 00 00 00 01 00 00 04 10 19 25 25 23 12 00 00 00 00 00 00 00 00\n",
      "00 00 00 00 00 00 00 00 00 00 00 00 01 05 08 02 03 18 24 25 25 25 22 11 00 00 00 00 00 00 00 00\n",
      "00 00 00 00 00 00 00 00 00 00 00 00 08 20 23 17 22 24 25 25 25 25 20 03 00 00 00 00 00 00 00 00\n",
      "00 00 00 00 00 00 00 00 00 00 00 00 11 24 25 24 25 25 25 25 25 20 09 00 00 00 00 00 00 00 00 00\n",
      "00 00 00 00 00 00 00 00 00 00 00 00 10 23 25 25 25 25 25 20 14 08 02 00 00 00 00 00 00 00 00 00\n",
      "00 00 00 00 00 00 00 00 00 00 00 00 05 14 22 25 25 21 16 09 04 01 00 00 00 00 00 00 00 00 00 00\n",
      "00 00 00 00 00 00 00 00 00 00 00 00 00 04 11 14 14 10 05 01 00 00 00 00 00 00 00 00 00 00 00 00\n",
      "00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00\n",
      "00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00\n",
      "00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00\n"
     ]
    }
   ],
   "source": [
    "# Code adapted from https://github.com/activatedgeek/LeNet-5/\n",
    "\n",
    "from collections import OrderedDict\n",
    "import torch\n",
    "import torch.nn as nn\n",
    "import torch.optim as optim\n",
    "from torch.autograd import Variable\n",
    "from torchvision.datasets.mnist import MNIST\n",
    "import torchvision.transforms as transforms\n",
    "from torch.utils.data import DataLoader\n",
    "import matplotlib\n",
    "import matplotlib.pyplot\n",
    "\n",
    "data_train = MNIST('data/mnist',\n",
    "                   download=True,\n",
    "                   transform=transforms.Compose([\n",
    "                       transforms.Resize((32, 32)),\n",
    "                       transforms.ToTensor()]))\n",
    "data_train_loader = DataLoader(data_train, batch_size=1, shuffle=True, num_workers=8)\n",
    "\n",
    "def main():\n",
    "    for i,(image, label) in enumerate(data_train_loader):\n",
    "        #matplotlib.pyplot.imshow(image.squeeze())\n",
    "        print(\"Label = \"+str(label[0]))\n",
    "        for j in range(0,image.size(2)):\n",
    "            row = []\n",
    "            for k in range(0,image.size(3)):\n",
    "                pixel = round(256*image[0,0,j,k].item(),0)\n",
    "                if pixel == 0:\n",
    "                    row.append('00')\n",
    "                elif pixel >= 0 and pixel/10 < 10:\n",
    "                    row.append('0'+str(int(pixel/10)))\n",
    "                elif pixel/10 >= 10:\n",
    "                    row.append(str(int(pixel/10)))\n",
    "            print(' '.join(row))\n",
    "        break\n",
    "\n",
    "\n",
    "if __name__ == '__main__':\n",
    "    main()"
   ]
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   "source": [
    "Once it downloads the dataset, this script prints out the first image."
   ]
  },
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   "source": []
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