GAN_step1_ch7.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "In /opt/conda/lib/python3.7/site-packages/matplotlib/mpl-data/stylelib/_classic_test.mplstyle: \n",
      "The text.latex.preview rcparam was deprecated in Matplotlib 3.3 and will be removed two minor releases later.\n",
      "In /opt/conda/lib/python3.7/site-packages/matplotlib/mpl-data/stylelib/_classic_test.mplstyle: \n",
      "The mathtext.fallback_to_cm rcparam was deprecated in Matplotlib 3.3 and will be removed two minor releases later.\n",
      "In /opt/conda/lib/python3.7/site-packages/matplotlib/mpl-data/stylelib/_classic_test.mplstyle: Support for setting the 'mathtext.fallback_to_cm' rcParam is deprecated since 3.3 and will be removed two minor releases later; use 'mathtext.fallback : 'cm' instead.\n",
      "In /opt/conda/lib/python3.7/site-packages/matplotlib/mpl-data/stylelib/_classic_test.mplstyle: \n",
      "The validate_bool_maybe_none function was deprecated in Matplotlib 3.3 and will be removed two minor releases later.\n",
      "In /opt/conda/lib/python3.7/site-packages/matplotlib/mpl-data/stylelib/_classic_test.mplstyle: \n",
      "The savefig.jpeg_quality rcparam was deprecated in Matplotlib 3.3 and will be removed two minor releases later.\n",
      "In /opt/conda/lib/python3.7/site-packages/matplotlib/mpl-data/stylelib/_classic_test.mplstyle: \n",
      "The keymap.all_axes rcparam was deprecated in Matplotlib 3.3 and will be removed two minor releases later.\n",
      "In /opt/conda/lib/python3.7/site-packages/matplotlib/mpl-data/stylelib/_classic_test.mplstyle: \n",
      "The animation.avconv_path rcparam was deprecated in Matplotlib 3.3 and will be removed two minor releases later.\n",
      "In /opt/conda/lib/python3.7/site-packages/matplotlib/mpl-data/stylelib/_classic_test.mplstyle: \n",
      "The animation.avconv_args rcparam was deprecated in Matplotlib 3.3 and will be removed two minor releases later.\n"
     ]
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import torch\n",
    "import torch.nn as nn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from torch.utils.data import Dataset\n",
    "import random"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "using cuda: Tesla V100-PCIE-32GB\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "device(type='cuda')"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# GPU사용 설정\n",
    "\n",
    "if torch.cuda.is_available():\n",
    "    torch.set_default_tensor_type(torch.cuda.FloatTensor)\n",
    "    print(\"using cuda:\", torch.cuda.get_device_name(0))\n",
    "    pass\n",
    "\n",
    "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
    "\n",
    "device"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Current cuda device  1\n",
      "Tesla V100-PCIE-32GB\n",
      "Memory Usage:\n",
      "Allocated: 0.0 GB\n",
      "Cached:    0.0 GB\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.7/site-packages/torch/cuda/memory.py:346: FutureWarning: torch.cuda.memory_cached has been renamed to torch.cuda.memory_reserved\n",
      "  FutureWarning)\n"
     ]
    }
   ],
   "source": [
    "# GPU 할당 변경하기\n",
    "GPU_NUM = 1 # 원하는 GPU 번호 입력\n",
    "device = torch.device(f'cuda:{GPU_NUM}' if torch.cuda.is_available() else 'cpu')\n",
    "torch.cuda.set_device(device) # change allocation of current GPU\n",
    "\n",
    "print ('Current cuda device ', torch.cuda.current_device()) # check\n",
    "\n",
    "# Additional Infos\n",
    "if device.type == 'cuda':\n",
    "    print(torch.cuda.get_device_name(GPU_NUM))\n",
    "    print('Memory Usage:')\n",
    "    print('Allocated:', round(torch.cuda.memory_allocated(GPU_NUM)/1024**3,1), 'GB')\n",
    "    print('Cached:   ', round(torch.cuda.memory_cached(GPU_NUM)/1024**3,1), 'GB')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "class MnistDataset(Dataset):\n",
    "    def __init__(self, csv_file):\n",
    "        self.data_df = pd.read_csv(csv_file, header=None)\n",
    "        \n",
    "    def __len__(self):\n",
    "        return len(self.data_df)\n",
    "    \n",
    "    def __getitem__(self, index):\n",
    "        label = self.data_df.iloc[index, 0]\n",
    "        target = torch.zeros((10))\n",
    "        target[label] = 1.0\n",
    "        \n",
    "        image_values = torch.Tensor(self.data_df.iloc[index, 1:].values)/255.0\n",
    "        \n",
    "        return label, image_values, target\n",
    "    \n",
    "    def plot_image(self, index):\n",
    "        img = self.data_df.iloc[index, 1:].values.reshape(28, 28)\n",
    "        plt.title(f\"label= {self.data_df.iloc[index, 0]}\")\n",
    "        plt.imshow(img, interpolation=\"none\", cmap=\"Blues\")\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "mnist_dataset = MnistDataset(\"./myo_gan/mnist_train.csv\")\n",
    "mnist_dataset.plot_image(17)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Discriminator(nn.Module):\n",
    "    \n",
    "    def __init__(self):\n",
    "        super().__init__()\n",
    "        self.model = nn.Sequential(nn.Linear(784, 200),\n",
    "                                   nn.Sigmoid(),\n",
    "                                   nn.Linear(200, 1),\n",
    "                                   nn.Sigmoid()\n",
    "                                  )\n",
    "        self.model = self.model.cuda()\n",
    "        self.loss_function = nn.MSELoss()\n",
    "        self.optimizer = torch.optim.SGD(self.parameters(), lr=0.01)\n",
    "        \n",
    "        self.counter = 0\n",
    "        self.progress = []\n",
    "        \n",
    "        self.outputs = 0\n",
    "        \n",
    "    def forward(self, inputs):\n",
    "        return self.model(inputs)\n",
    "    \n",
    "    def train(self, inputs, targets):\n",
    "        self.outputs = self.forward(inputs)\n",
    "        \n",
    "        loss = self.loss_function(self.outputs, targets)\n",
    "        \n",
    "        self.counter += 1\n",
    "        if (self.counter % 10 == 0):\n",
    "            self.progress.append(loss.item())\n",
    "        \n",
    "        if (self.counter % 10000 == 0):\n",
    "            print(f\"counter = {self.counter}\")\n",
    "            \n",
    "        self.optimizer.zero_grad()\n",
    "        loss.backward()\n",
    "        self.optimizer.step()\n",
    "        \n",
    "    def plot_progress(self):\n",
    "        df = pd.DataFrame(self.progress, columns=[\"loss\"])\n",
    "        df.plot(ylim=(0, 1.0), figsize=(16, 8), alpha=0.1, marker=\".\", \n",
    "                grid=True, yticks=(0, 0.25, 0.5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def generate_random(size):\n",
    "    return torch.rand(size)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n"
     ]
    }
   ],
   "source": [
    "D = Discriminator()\n",
    "\n",
    "for label, image_data_tensor, target_tensor in mnist_dataset:\n",
    "    # 숫자 이미지는 1\n",
    "    D.train(image_data_tensor, torch.Tensor([1.0]))\n",
    "        \n",
    "    # 랜덤 이미지는 0\n",
    "    D.train(generate_random(784), torch.Tensor([0.0]))\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "D.plot_progress()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.9872260689735413\n",
      "0.9968051910400391\n",
      "0.9970766305923462\n",
      "0.9952917098999023\n"
     ]
    }
   ],
   "source": [
    "for i in range(4):\n",
    "    image_data_tensor = mnist_dataset[random.randint(0, 60000)][1]\n",
    "    print(D.forward(image_data_tensor).item())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.005652696825563908\n",
      "0.005639504641294479\n",
      "0.004952243994921446\n",
      "0.006592056713998318\n"
     ]
    }
   ],
   "source": [
    "for i in range(4):\n",
    "    print(D.forward(generate_random(784)).item())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Generator(nn.Module):\n",
    "    def __init__(self):\n",
    "        super().__init__()\n",
    "        \n",
    "        self.model = nn.Sequential(nn.Linear(1, 200), \n",
    "                                   nn.Sigmoid(),\n",
    "                                   nn.Linear(200, 784),\n",
    "                                   nn.Sigmoid()\n",
    "                                  )\n",
    "        \n",
    "        self.optimizer = torch.optim.SGD(self.parameters(), lr=0.01)\n",
    "        \n",
    "        self.counter = 0\n",
    "        self.progress = []\n",
    "        \n",
    "    def forward(self, inputs):\n",
    "        return self.model(inputs)\n",
    "    \n",
    "    def train(self, D, inputs, targets):\n",
    "        g_output = self.forward(inputs)\n",
    "        \n",
    "        d_output = D.forward(g_output)\n",
    "        \n",
    "        loss = D.loss_function(d_output, targets)\n",
    "        \n",
    "        self.counter += 1\n",
    "        if (self.counter % 10 == 0):\n",
    "            self.progress.append(loss.item())\n",
    "            \n",
    "        self.optimizer.zero_grad()\n",
    "        loss.backward()\n",
    "        self.optimizer.step()\n",
    "        \n",
    "    def plot_progress(self):\n",
    "        df = pd.DataFrame(self.progress, columns=[\"loss\"])\n",
    "        df.plot(ylim=(0, 1.0), figsize=(16, 8), alpha=0.1, marker=\".\", \n",
    "                grid=True, yticks=[0, 0.25, 0.5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fe5c96c04d0>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "G = Generator()\n",
    "output = G.forward(generate_random(1))\n",
    "img = output.detach().cpu().numpy().reshape(28, 28)\n",
    "plt.imshow(img, cmap=\"Blues\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n",
      "counter = 10000\n",
      "counter = 20000\n",
      "counter = 30000\n",
      "counter = 40000\n",
      "counter = 50000\n",
      "counter = 60000\n",
      "counter = 70000\n",
      "counter = 80000\n",
      "counter = 90000\n",
      "counter = 100000\n",
      "counter = 110000\n",
      "counter = 120000\n"
     ]
    }
   ],
   "source": [
    "for i in range(100):\n",
    "    D = Discriminator()\n",
    "    G = Generator()\n",
    "\n",
    "    for label, image_data_tensor, target_tensor in mnist_dataset:\n",
    "\n",
    "        # 참에 대해 판별기 훈련\n",
    "        D.train(image_data_tensor, torch.Tensor([1.0]))\n",
    "\n",
    "        # 거짓에 대해 판별기 훈련\n",
    "        D.train(G.forward(generate_random(1)).detach(), torch.Tensor([0.0]))\n",
    "\n",
    "        # 생성기 훈련\n",
    "        G.train(D, generate_random(1), torch.Tensor([1.0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "D.plot_progress()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "G.plot_progress()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, axes = plt.subplots(2, 3, figsize=(16, 8))\n",
    "axs = axes.ravel()\n",
    "\n",
    "for ax in axs:\n",
    "    output = G.forward(generate_random(1))\n",
    "    img = output.detach().cpu().numpy().reshape(28, 28)\n",
    "    ax.imshow(img, cmap=\"Blues\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}