EBooks/Machine-Learning-For-Finance/6.3 MNIST DCGAN.ipynb

{
  "cells": [
    {
      "metadata": {
        "collapsed": true,
        "_cell_guid": "21830c4b-3f47-4a7f-9697-95c05419871d",
        "_uuid": "6d170584ce2dcc8ddc7d555c52e00c637810bd42",
        "trusted": true
      },
      "cell_type": "code",
      "source": "import numpy as np\nimport matplotlib.pyplot as plt",
      "execution_count": 1,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true,
        "collapsed": true,
        "_uuid": "af8bd5b75a3e4d5530789479f988d566e7b85c76"
      },
      "cell_type": "code",
      "source": "from tqdm import tqdm, tnrange",
      "execution_count": 2,
      "outputs": []
    },
    {
      "metadata": {
        "_cell_guid": "0aa7d1cd-9c1e-494d-a5a1-56e7d8f6ffca",
        "_uuid": "dbfd497e8ca31e01cb32a8e395be7568f2c8b64b",
        "trusted": true
      },
      "cell_type": "code",
      "source": "# Ensure results are reproducable\nfrom numpy.random import seed\nseed(1)\nfrom tensorflow import set_random_seed\nset_random_seed(2)",
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": "/opt/conda/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n  from ._conv import register_converters as _register_converters\n",
          "name": "stderr"
        }
      ]
    },
    {
      "metadata": {
        "collapsed": true,
        "_cell_guid": "5d30be58-4dde-4da9-9cc5-4b2290c48cb4",
        "_uuid": "1655872712ea6447b0423a3b80b0fedd8f528bee",
        "trusted": true
      },
      "cell_type": "code",
      "source": "def mnist_load_data(path='mnist.npz'):\n    with np.load(path) as f:\n        x_train, y_train = f['x_train'], f['y_train']\n        x_test, y_test = f['x_test'], f['y_test']\n    return (x_train, y_train), (x_test, y_test)\n        \n\n(X_train, y_train), (X_test, y_test) = mnist_load_data(path='../input/mnist.npz')",
      "execution_count": 4,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true,
        "collapsed": true,
        "_uuid": "f94f9e7fec7fb5d166b23d4fc26b4cae7d8eb252"
      },
      "cell_type": "code",
      "source": "X_train = np.expand_dims(X_train,1)\nX_test = np.expand_dims(X_test,1)",
      "execution_count": 5,
      "outputs": []
    },
    {
      "metadata": {
        "collapsed": true,
        "_uuid": "af80a06b1d4b96ae07ed566b4f12fa78e9da09ab",
        "trusted": true
      },
      "cell_type": "code",
      "source": "from sklearn.utils import resample",
      "execution_count": 6,
      "outputs": []
    },
    {
      "metadata": {
        "collapsed": true,
        "_uuid": "ea321c0d595a3bad2a6cf2c57d92192e56ab1769",
        "trusted": true
      },
      "cell_type": "code",
      "source": "X_train, y_train = resample(X_train,y_train,n_samples=50000)",
      "execution_count": 7,
      "outputs": []
    },
    {
      "metadata": {
        "_uuid": "9531958425ae5845c7915cf9d05d57c3ac9430ef",
        "trusted": true
      },
      "cell_type": "code",
      "source": "X_train.shape",
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 8,
          "data": {
            "text/plain": "(50000, 1, 28, 28)"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "trusted": true,
        "_uuid": "05c41bcd93b0141d38e7c95ca3ae90d9f27baa53"
      },
      "cell_type": "code",
      "source": "X_train = X_train/255\nX_test = X_test/255",
      "execution_count": 23,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true,
        "_uuid": "d57d4f9fe81c6e7ed13979a7e4b2e3dac8f4666d"
      },
      "cell_type": "code",
      "source": "from keras.models import Model, Sequential\nfrom keras.layers import Input, Dense, Dropout, Flatten\nfrom keras.layers import LeakyReLU, Reshape\nfrom keras.layers import Conv2D, UpSampling2D\nfrom keras.optimizers import Adam\n\nfrom keras.initializers import RandomNormal",
      "execution_count": 24,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true,
        "collapsed": true,
        "_uuid": "b92a416a2c2d0a79ae745edfb830c052874bfaff"
      },
      "cell_type": "code",
      "source": "import keras.backend as K\nK.set_image_data_format('channels_first')",
      "execution_count": 25,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true,
        "collapsed": true,
        "_uuid": "12d24ca183711b35cc87d5d7922d26177e9e4b60"
      },
      "cell_type": "code",
      "source": "latent_dim = 100",
      "execution_count": 26,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true,
        "_uuid": "0b3bf51b9365d356a5021c2fc2bf5df9578b2d97",
        "collapsed": true
      },
      "cell_type": "code",
      "source": "generator = Sequential() #1 \n\ngenerator.add(Dense(128*7*7, \n                    input_dim=latent_dim, \n                    kernel_initializer=RandomNormal(stddev=0.02))) #2\n\ngenerator.add(LeakyReLU(0.2)) #3\ngenerator.add(Reshape((128, 7, 7))) #4\ngenerator.add(UpSampling2D(size=(2, 2))) #5\n\ngenerator.add(Conv2D(64,kernel_size=(5, 5),padding='same')) #6\n\ngenerator.add(LeakyReLU(0.2)) #7\ngenerator.add(UpSampling2D(size=(2, 2))) #8\n\ngenerator.add(Conv2D(1, kernel_size=(5, 5),\n                        padding='same', \n                        activation='tanh')) #9\n  \nadam = Adam(lr=0.0002, beta_1=0.5)                      \ngenerator.compile(loss='binary_crossentropy', optimizer=adam) #10",
      "execution_count": 27,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true,
        "_uuid": "58047ba162c42550af417713630f699f6530ceeb"
      },
      "cell_type": "code",
      "source": "generator.summary()",
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "stream",
          "text": "_________________________________________________________________\nLayer (type)                 Output Shape              Param #   \n=================================================================\ndense_3 (Dense)              (None, 6272)              633472    \n_________________________________________________________________\nleaky_re_lu_5 (LeakyReLU)    (None, 6272)              0         \n_________________________________________________________________\nreshape_2 (Reshape)          (None, 128, 7, 7)         0         \n_________________________________________________________________\nup_sampling2d_3 (UpSampling2 (None, 128, 14, 14)       0         \n_________________________________________________________________\nconv2d_5 (Conv2D)            (None, 64, 14, 14)        204864    \n_________________________________________________________________\nleaky_re_lu_6 (LeakyReLU)    (None, 64, 14, 14)        0         \n_________________________________________________________________\nup_sampling2d_4 (UpSampling2 (None, 64, 28, 28)        0         \n_________________________________________________________________\nconv2d_6 (Conv2D)            (None, 1, 28, 28)         1601      \n=================================================================\nTotal params: 839,937\nTrainable params: 839,937\nNon-trainable params: 0\n_________________________________________________________________\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "trusted": true,
        "collapsed": true,
        "_uuid": "3d901e7c56345597e4e00d29f891bf60c7d47912"
      },
      "cell_type": "code",
      "source": "# Discriminator\ndiscriminator = Sequential()\ndiscriminator.add(Conv2D(64, kernel_size=(5, 5), \n                         strides=(2, 2), \n                         padding='same', \n                         input_shape=(1, 28, 28),\n                         kernel_initializer=RandomNormal(stddev=0.02))) #1\n\ndiscriminator.add(LeakyReLU(0.2))\ndiscriminator.add(Dropout(0.3))\ndiscriminator.add(Conv2D(128, kernel_size=(5, 5), \n                         strides=(2, 2), \n                         padding='same'))\ndiscriminator.add(LeakyReLU(0.2))\ndiscriminator.add(Dropout(0.3)) #2\ndiscriminator.add(Flatten())\ndiscriminator.add(Dense(1, activation='sigmoid'))\ndiscriminator.compile(loss='binary_crossentropy', optimizer=adam)",
      "execution_count": 29,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true,
        "_uuid": "63e44f4b620c90311cb4b533052b984804b55415"
      },
      "cell_type": "code",
      "source": "discriminator.summary()",
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "stream",
          "text": "_________________________________________________________________\nLayer (type)                 Output Shape              Param #   \n=================================================================\nconv2d_7 (Conv2D)            (None, 64, 14, 14)        1664      \n_________________________________________________________________\nleaky_re_lu_7 (LeakyReLU)    (None, 64, 14, 14)        0         \n_________________________________________________________________\ndropout_3 (Dropout)          (None, 64, 14, 14)        0         \n_________________________________________________________________\nconv2d_8 (Conv2D)            (None, 128, 7, 7)         204928    \n_________________________________________________________________\nleaky_re_lu_8 (LeakyReLU)    (None, 128, 7, 7)         0         \n_________________________________________________________________\ndropout_4 (Dropout)          (None, 128, 7, 7)         0         \n_________________________________________________________________\nflatten_2 (Flatten)          (None, 6272)              0         \n_________________________________________________________________\ndense_4 (Dense)              (None, 1)                 6273      \n=================================================================\nTotal params: 212,865\nTrainable params: 212,865\nNon-trainable params: 0\n_________________________________________________________________\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "trusted": true,
        "_uuid": "0ec9b02889c0e09508ede2cf6528fbf793c340ab",
        "collapsed": true
      },
      "cell_type": "code",
      "source": "discriminator.trainable = False #1\nganInput = Input(shape=(latent_dim,)) #2\nx = generator(ganInput) #3\nganOutput = discriminator(x) #4\ngan = Model(inputs=ganInput, outputs=ganOutput) #5\ngan.compile(loss='binary_crossentropy', optimizer=adam) #6",
      "execution_count": 31,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true,
        "_uuid": "1a5c24f23149ef0cbcf7597790fa85fc3f30a01c"
      },
      "cell_type": "code",
      "source": "X_train.shape[0]",
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 32,
          "data": {
            "text/plain": "50000"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "trusted": true,
        "collapsed": true,
        "_uuid": "b1e4bd889178d1c553ca78ccfd96655933879acf"
      },
      "cell_type": "code",
      "source": "def show_gen():\n    r, c = 2, 2\n    noise = np.random.normal(0, 1, (r * c, 100))\n    gen_imgs = generator.predict(noise)\n    print(gen_imgs.shape)\n    # Rescale images 0 - 1\n    gen_imgs = 0.5 * gen_imgs + 1\n\n    fig, axs = plt.subplots(r, c)\n    cnt = 0\n    for i in range(r):\n        for j in range(c):\n            axs[i,j].imshow(gen_imgs[cnt, 0,:,:], cmap='gray')\n            axs[i,j].axis('off')\n            cnt += 1\n    #fig.savefig(\"images/mnist_%d.png\" % epoch)\n    plt.show()\n    return gen_imgs",
      "execution_count": 33,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true,
        "_uuid": "8e79ad4e351cc2e0a4d4e1b14080cafde5373754"
      },
      "cell_type": "code",
      "source": "i = show_gen()",
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "stream",
          "text": "(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f13856b08d0>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "trusted": true,
        "_uuid": "3cc32d8d41db8a0b3348f584a63c2854203055bc",
        "scrolled": false
      },
      "cell_type": "code",
      "source": "dLosses = []\ngLosses = []\nepochs=50 \nbatchSize=128\nbatchCount = X_train.shape[0] // batchSize #1\n\nfor e in range(1, epochs+1): #2\n    print('-'*15, 'Epoch %d' % e, '-'*15)\n    dloss = 0\n    gloss = 0\n    for _ in range(batchCount): #3      \n        noise = np.random.normal(0, 1, size=[batchSize, latent_dim]) #4\n        imageBatch = X_train[np.random.randint(0, \n                                              X_train.shape[0],\n                                              size=batchSize)] #5\n\n        generatedImages = generator.predict(noise) #6\n        X = np.concatenate([imageBatch, generatedImages]) #7\n\n        yDis = np.zeros(2*batchSize) #8\n        yDis[:batchSize] = 0.9 \n        \n        labelNoise = np.random.random(yDis.shape) #9\n        yDis += 0.05 * labelNoise + 0.05\n\n        \n        discriminator.trainable = True #10\n        dloss += discriminator.train_on_batch(X, yDis) #11\n\n        \n        noise = np.random.normal(0, 1, size=[batchSize, latent_dim]) #12\n        yGen = np.ones(batchSize) #13\n        discriminator.trainable = False #14\n        gloss += gan.train_on_batch(noise, yGen) #15\n    \n    dloss /= batchCount\n    gloss /= batchCount\n    print('dLoss: {:.2f}'.format(dloss))\n    print('gLoss: {:.2f}'.format(gloss))\n    #16\n    dLosses.append(dloss)\n    gLosses.append(gloss)\n    show_gen()\n    ",
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "stream",
          "text": "--------------- Epoch 1 ---------------\ndLoss: 0.46\ngLoss: 1.11\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f13853e5550>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAOiO/wG+0TOG/mFm2wAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 2 ---------------\ndLoss: 0.35\ngLoss: 1.54\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f1384fee6a0>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nwcIHAM3xP9T7Ds1BJ4WKAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 3 ---------------\ndLoss: 0.34\ngLoss: 1.66\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f13a0e8b048>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nMPEBQHMw8QFAc/wfvFfY7BnUr1YAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 4 ---------------\ndLoss: 0.33\ngLoss: 1.74\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f13849c9898>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4wLCBo\ndHRwOi8vbWF0cGxvdGxpYi5vcmcvpW3flQAAHfxJREFUeJztndvPXVX1hkcVKC2HUkoLhUIp5VBE\nCmipRSlCg4ASKMZEQjwk4oV4SLzyQv0TvNHEO2PQmBiDJp5QDFI1lqII0iq1obSl5xbaQim0UA4e\nrn7Td77tHl17u7/v2/3N57maK2PttfZhrpk53j0Ok/79738HAEBLvGOi3wAAwHjDwgcAzcHCBwDN\nwcIHAM3BwgcAzcHCBwDNwcIHAM3BwgcAzcHCBwDNccJ43mzp0qUTmibyjnf8d53/17/+Vdne+c53\n9nzdpEmTjjqOiHjrrbeqY72u3i8i4oQT/vt1v/32253v/89//rOnbVBWrlw56dhnQRc++clPDjSv\nfS4pnlGVnatkc8XnWHbuiSee2PlcnedZJph/hkGzxvR1fs0f/OAHnb4odnwA0BwsfADQHCx8ANAc\n46rxjTeusXW19aN9OKo5uIahx5nekr03GD266m8Rua6VaVeZTfF5pceua+s8O5b+ptdxm+rVPnf1\nun7/fr63XgyqE/KEAUBzsPABQHOMrKubuXu6ZfatfeZqZmEper/M1c1cAL/O66+/3vP+7jJn9+/q\n+rorMcg1YPzox03L5rVy0kknVcc6lzyESuegh2X5HJwyZUrPe+oz4M+Vzkm3dQ3nyZ5jXF0AgI6w\n8AFAc7DwAUBzjKvG5zpTpkllqV+KaxFdU8/8dXo/TS2LiDh8+HBP2+TJk3uem70X11T8OkqmOWbf\n4SDnQf8MqjP1k8KlNteHVbvz31m1ufPOO6+ynXbaaWW8e/fuyvbSSy9Vx4cOHep5f30msnk2LK1u\nGA3S2PEBQHOw8AFAc4yrqzuscAt1IbtWjfBjd0N1u+5hKPo6Dwl48803q+OXX365jKdOnVrZZs+e\nXcbuWujrpk2bVtkyl8Bdb4WeyaNNPxVYdA66LKLP1RlnnFHZli1bVsaXXHJJZdu7d28Z//nPf65s\nKtlEHCnN9DrXw2kyN1ifpSwszcHVBQAYABY+AGgOFj4AaI6RTVnLwkvU/3fNTbUIf53aMv3Pbaoj\n+l/5Bw8erI5PPfXUMr7jjjsqm+ov69atq2zPPvtsGb/xxhs9r+n6Y9eqHTB2DFqdxedZ19/ylVde\nqY5V87v55psr24033ljGrqPp3HWt+vTTT6+Os5AZfT78OllI1zD06UHnPDs+AGgOFj4AaI4JdXW7\nFgp1d1a3wR4yose+ld66dWsZu4vqUe2Kurf+d71/hksvvbSM1c2IiFi4cGEZv/baa5Xtm9/8Zhk/\n8sgjlU0/x6DZLzAaDFqoVp8Bz6q46qqryvjKK6+sbOoGu4v861//uoyfe+65yuaSzosvvljGJ598\ncs/37c+qyjb+PGZhaVklpV737gd2fADQHCx8ANAcLHwA0BwTqvFllZQzvUOZNWtWdXz99deX8Zln\nnlnZnnrqqTJes2ZNZdMqFn4/1fU0tSziSB1t586dZbxt27bKtnjx4qPeLyLi/e9/fxn/9a9/jV64\npqEhOlk1aPS+4wv/nfX306oqERFLliwpY093fPXVV8v4vvvuq2w/+clPyvirX/1qZfO5pJr0nDlz\nKpuGvuj9IiK2bNly1GtE1M9VVp15LKqHs+MDgOZg4QOA5hiZzI2swY5vdTWTQd3HiIgPf/jDZXzK\nKadUtgULFpTxe97znsq2adOmMvbKKRoGMGPGjMrmf/s/+eSTZezZGVlYytVXX93zmhq+4Las0UtW\nuQYmhiw0Q22Z9ONz0KuuKCtXrizjP/7xj5XtrrvuKuN58+ZVNp+7F110URl/6EMfqmxnn312GW/e\nvLmyrV27tow1nCyifq48W0k/r1ejUdugEg47PgBoDhY+AGgOFj4AaI6R0fhc08j0qbPOOquMNQ0s\notY/XBvQY08902P/S15DRjKNLaIONXDdZNAUPf0uvGqGvjfXOwhnmRi6VlnJ0q2y3/Kyyy6rbDrn\nPZ3tV7/6VRnfdtttle3uu+8uYw31iqi16oiIL33pS2X83ve+t7Lps+MVoKdPn17GrkVu2LChjFVj\nj6irOg+rcnv1uoFeBQBwHMPCBwDNMTKublapwre66uq665cVN8yiwdVl9cYqGzduLOPzzz+/sunf\n9RF1FYvly5f3fC+OZoS4+zxz5swyzirVwGgwaL9Y/d39d9ZnQCsARdQSztNPP13Z9Pjyyy+vbOoW\nP/HEE5XNq7zceuutZexhYlnPX31WvaqLfkavHLNv374y9oyPYcg27PgAoDlY+ACgOVj4AKA5Rkbj\nc79ddQMPPdFzvfGxVlZ2m+odzz//fGVTvUE1vYg6Rc4rU7g28q1vfauMVd9wPFznRz/6URl7OE0W\nEqGaZlbRA8aPLJwla5SlNv/t9BlwHVvTvbZv317ZNJzEQ79U5/ZKRl/4wheqYw9TUbQB1vr163u+\nN/+8qutl4WxjoWOz4wOA5mDhA4DmGBlXN+tz62jIiEeYv/DCC2X8zDPPVDYt8Omupv7VvmfPnso2\nd+7cMvbqE/v376+Ob7jhhp7vW9Go9YiIFStW9DxXs0GyrI7sO8PtHT8yaSIrvpu5umrzkJFDhw6V\nsc95dRMPHDhQ2fRcL+jrMo1ex3vnalFfbWAUUYfMaBWXiPrze8iKzuWuFW36gR0fADQHCx8ANAcL\nHwA0x8hofI767p5Cpg19PPRDtbodO3ZUNv1r39NuVLeYPXt2ZVOdQivaRhyZMufHiobXaAPxiLr5\nkL83fZ3/td81PWosGrbA0cnCWfR3yNI0My1Xw0ci6mfAnwfVznzuqlZ+3XXXVTZvqqXz06szayjW\nrl27Kps+V64N6jxXnTKi/vxjoU/zNABAc7DwAUBzjKyrm/XV1a2+b5/VLdQsjoh6u+5ba3VB3F3V\naHh/L/fcc0/P63gDlfvvv7+Mf/azn1W2+fPnl3FWxcKj9vXzU4h0NBi0+GjWYEuPPfRD58tHP/rR\nyqbzysNZNBvkzjvvrGznnHNOdayZTg888EBl0+dD5aSI+jnz9+3HvaCvLgDAEGDhA4DmYOEDgOYY\nV43PfXXVnfrRoFRn82uqjjd16tSer/OKL/o3/GOPPVbZNETgM5/5TGXz46zKi1ZucQ1FU4Q07S6i\n/hyeatc1PQrGjizEyH+fLNRFbZkW6KEuOuevuOKKyqYVw13zVr34ggsu6GmLqLU616517noVF32v\n/qxmISv6rGbf06Cw4wOA5mDhA4DmYOEDgOYYV41vUB2vn7goPdfTd1Sb8GtqBVqvPnv77beX8aJF\niyqblwjSOMLVq1dXNo2jOvfccyubxiZqGaqI+jO6xpc1XidNbXwYNG4vs3m8qOJNw3UOeLqjzgGP\nXc2qQXssqT67npamXd78edB7qBYZUT8rnpaa6Z2DdrFTeDIAoDlY+ACgOSY0nEXJ3OB+qo7otl+3\n4BH1dt7/2r/rrrvK+N57761s06ZNK2N3Qfx9a1ULb+6sboC/Tt+bu69Zo+nMJepanRkmhsxFdrdQ\nz/XUM5VJPExr27ZtZezSiz4DHs7iaZs6z/y50rRJn7vqwnqKWhb2k81dwlkAAAaAhQ8AmoOFDwCa\nY2TCWTI/PktnycI5vFPU3r17y9hTe6699toydn1F8ftpU+SIiIceeqiMH3/88co2Y8aMntfNwln8\nr35lLJotw/AYNBQrq8Dsnf40vEX1aH9d9vz5/fx51HJTHoqlz1WmOWdz1b+n7DrDgB0fADQHCx8A\nNMfIVmDOGi9nbrCGjGgzlYg6ct231trg211SdRc0PCAiYu3atdWxNnTxarQaVe/ua1YtOXMR9Fwa\niv//weenhoL4fNCwFM2G8NdlslAWThJRP0ueuaH3dJlGyULPnK4SDg3FAQA6wsIHAM3BwgcAzTGh\nGl+ma2WNlxWvFKvnZtWZ3fboo4+W8f79+yubdpFyTc9ThLR6sldZ1s/or8uaSWd07aRGytro0U91\nFq2W4rrWvn37ynj27NmVbd68eWV84YUXVjYNoZo1a1Z6f50/M2fOrGx79uwp4yz0KtP0MgatfpPB\n0wAAzcHCBwDNMaGubhaK0fVv6iz6PXN1vUipVlXxYooa6qKNlSPqZi6Ou8xa1cJdXXUDxiJqnXCW\n8aNrhkImP/g1VNLRaigRtfzi80qzLLIKLN6Yy9H56VKM3jPLssrCWfx5HzRMpSvs+ACgOVj4AKA5\nWPgAoDlGJmWtHw2qa2iGaxGq3WkIQESt/3mjlWuuuaaM58+fX9m8UsX69evL+IknnqhsGuriGmPX\nZtIO2t3o0VWf8vMyzVs1Pv/Nt2zZUsbejF7TJhcuXFjZtCLR3LlzK5s/O1u3bi1jD0vpqlX6+x6G\njkfKGgBAR1j4AKA5RiZzYyzIGgN59PmSJUvK+Kabbqpsc+bMKWMvUuqhBXrPNWvW9HxvHjKTZW6M\ndVFGGD+69ot1d1Lnizf7yeaHVhPyfrzaZ/pY8srGjRvLWDM+IvJwlq7PeD/yjp6LqwsA0BEWPgBo\nDhY+AGiOkU1Z6/q6Qc/z+2kIi1ex1Qq33hR5586d1bHqet742SvJ9HqvWeMlt3X9jIS9TAyZjuf6\nVKZzadWTTNdy7Vj1QJ3HERFPPfVUGaveF3HkPNO0zaxas3+GTI/TOTnWKWoOOz4AaA4WPgBojpHN\n3MhcX7X53/66ZXbXUsNE3GXVLAtvKKR/17sbvHv37upYizI6+hmzz9uPC5SBezs+ZO7ssNBr+v30\nGfBCoJm8oq6vZhz5NSPq58UrwOhzNWgf4X4YxvfLjg8AmoOFDwCag4UPAJpjZDQ+p6s+lfn7rhOq\nNuGpZtok2StcKK6huG6h6UNZwxb/fFk4C1rd8UXXlKpM8xq0cVQ/FVD0/h7q0k+z765hU8PS/0hZ\nAwAYABY+AGiOkXV1B0W33VmVk3561+r23YuUOl2j2J2umSu4wccXw3Lh1Ja5oT4/9DirVuT38wyQ\nLGRGr9uP69n183a9Rj+w4wOA5mDhA4DmYOEDgOaYNKiPDABwvMKODwCag4UPAJqDhQ8AmoOFDwCa\ng4UPAJqDhQ8AmoOFDwCag4UPAJqDhQ8AmoOFDwCag4UPAJqDhQ8AmoOFDwCag4UPAJqDhQ8AmoOF\nDwCag4UPAJqDhQ8AmoOFDwCaY1z76t52220T2uBDe3d6r5GufW29p6m/LruH2rLrZH1QBu0/6vzm\nN7/p3gAVUm655ZbqRxiLPjb6u2dzoJ8+vsqx+jNr71w/t+t7G9bczXj44Yc7fWB2fADQHCx8ANAc\nLHwA0BzjqvENi0xH63VeP2QahmtzfnziiSd2ukc/Wkiv8/xceiSPBoPOz+zcrjqeX7OrrnysZ0Xv\n6br2sfTB/+Ott96qjk844b/LTz9zdxhznh0fADQHCx8ANMdx6eoq2da+q+twrGvqVv7UU0+tbO4+\nHDp0qOd1TzrppDJ2d0GP3XXIXIlBXWQYH/qRWwYNWel1nh9rSMqxbM6bb75ZxpMnT65s+tq33367\nsum89nvovM6+p0FloQx2fADQHCx8ANAcLHwA0BzHpcbXVa/KtDoPO8n0htNOO62Mp0+f3tMWEbFz\n584yfuGFFypbptOoNtKPVtc11Q3Gj7HQXbuem+l4Ga5VO/q8+LnZPVQb9PeWpcF1vT7hLAAAHWHh\nA4DmGBlXd9BshX6uo5HijrqaU6ZMqWyLFy8u40WLFlU2P3fdunVl/Pvf/76yvfTSS0e9X0QeGa8u\nQRauAKNB1wo9/YRiZOEmWWWhzNXMngd3PfUehw8f7vm6bH66LKQus2d1DCpndYUdHwA0BwsfADQH\nCx8ANMfIaHxO17+w+6kUoTY/74033ijjCy64oLK9733vK+NLLrmksrnGoLrF7t27K9uGDRvKWPU+\nv3+mr/Sjd6L/jQ/96HhdKxL7vFZbVj0oSxnTlMmIOr1S51/EkSErqmVneqPf49VXXy3jPXv2VLZT\nTjmljD28LAuvGca8ZscHAM3BwgcAzTGyrm6Gbu0zt9C3z/qXuW+X9W//qVOnVjbd2h84cKCyeTWW\nTZs2lfHBgwd73uP111+vbPpeB20mg2s7MQwaiuWvyySNrs2wfF6pO7lv377KpuElN910U2Xzea1V\niTQ7KSJi165dZbxgwYLKpu97+/btlU2fFQ+t8WewF2RuAAB0hIUPAJqDhQ8AmmNCNb5hNA3KtA//\niz5D9Q5Pn9myZUsZ7927t7KpbhcRcd5555WxV3J57bXXel4n0/EGrWLbtcItTAz9pB9mYTB6fPrp\np1c2DQs544wzKtvXv/71Mta0zIgjtfMdO3aU8YMPPljZNNTlyiuvrGyzZs0qY5+7f/rTn8p41apV\n0Qt/L1RgBgAYABY+AGiOkQlnGTQkIMvccJtGlfs1NZPCXd0XX3yx53u77LLLquNzzjmnjD18QEMC\nTj755Mqmn8ldAo3GzzJTMhcIV3fs6EemyeSdrkVlM9dPw1ciIl5++eUyXrZsWWXTjCQP/XIJR49V\nzomIWL16dRnPnTu3sl1zzTVl7CErKi89/vjjlU0zPjwbhL66AAADwMIHAM3BwgcAzTGhGt8w/pZ2\n9O9719EU1/HOPffcMr744osrm1ZrmTlzZk9bRJ1qo/pKRMT+/fvLWDWMiFqbcW0yq1RBytrE08/c\n7fobZedlDYU2b95c2fQZ+PjHP17ZXNdTNNQkIuK3v/1tGS9cuLCyaVMtDdmKqENdfF7rMzdnzpzK\ntn79+jL2ijOq+R2rSVIv2PEBQHOw8AFAc4yrq9tPxYmuDVv66cepISve+ET/ond3Vl2CadOmVTYP\nH1A3xMNgnnvuuaOe52SNV7LwiOy7gPFjUMlBfz8P/VCXzjOS9FyvavLFL36xjC+66KKe93ZZ5tOf\n/nR1fOaZZ5bxu971rsqmBXbVJY6IuPnmm8vY565mmXiIjD4rzjAyktjxAUBzsPABQHOw8AFAc4yr\nxtdPI/Cs8Uqv8yJq7cy1MtXqPH3nlltuKWPX7fTvek07OxqqlaxYsaKyaYWLefPmVbasAov+ne9/\n3w9a1QbGjixVMEupzPRaPfYqy6pJL126tLJpZWV/LzpXly9fXtm2bdtWHX/qU58qY686pA24Lrzw\nwuiFz1Wdy/5c6Xt1TVOfY1LWAAA6wsIHAM0xMpkbWa/QftwFdRM9O0LdgE984hOVbcaMGT3fp4a+\neLiAV47Q9+NZHWeffXYZe1bJK6+8UsYeMqMuAa7t6DGs6iwuzXTlrLPOKuNLL720smlzLL/+d77z\nnTL+29/+Vtk+//nP97zfmjVrqmO/p6IyjWeK6Of3Iqn6DOizEVE/D4SzAAB0hIUPAJqDhQ8AmmNk\nmg0N6qtnjcG10UlExN13313GrumpbujVIPbs2dPzda5bPProo2XsFS60wZA3hdG/7L1pueuIvd63\n07UJNfxv9FM9PEs/1N/ZG3pryti1115b2TScxKujfP/73y9jT0vTxuD33HNPZXMt+8c//nEZe3qZ\n6uo+Vw8fPlzGPh9Vc/QQHbVlOumg8GQAQHOw8AFAcxwXzYacrr10r7jiisqm23d3J7Ux0JNPPlnZ\ntm7dWsbaoCXiSFdTr+M9RrURkVduUZfZG73oe83CZyhEOjFk1YMysgo9Pq907i5YsKCyqcv6j3/8\no7KtXbu2jL3iiYZbZSEjERHXXXddGav7GlE/H/5c6XvzbCV1Z921V5tLT1kP6q6w4wOA5mDhA4Dm\nYOEDgOaY0OosmX+eVWfRirOuKWhamDf7fuaZZ8r4gQceqGza3GT27NmVTZsi63kRdQOhiLrKhDZT\niajTcjQ8IaLW7rZs2VLZtKqLp+Fl6XsK+t/YkWl6XfXoiHruuD584403lrFXD3r44YfL2KuqaNVl\nb/adzR3XmXft2nXU9xlRa3D6XiIi7rjjjjL2FE69p99P56vr2v69DQI7PgBoDhY+AGgOFj4AaI4J\n7bI2aOqJxhGpphcRMX/+/DLWrmoREQ899NBRxxERixYtKuODBw9Wtl/84hdl7DFFngb0gQ98oIw9\nnU1L/3iM4eLFi8vY9RaN+fOUJAUdb/TweDiN3XOtTuM8P/KRj1Q21cdcZ1bNy3W8j33sY2W8atWq\nyqYplUuWLKlsv/zlL6tjbfh9++23VzZ9PjzGz59PRWMHd+/eXdmylDX9DmkoDgDQERY+AGiOkQln\nyf7297+6NZzl6quvrmzqsj799NOVTdN31LWMqMMFtMJKRMSmTZvK+N3vfndl++xnP1sdX3/99WX8\n2GOPVbaVK1eW8cUXX1zZtGGMpyRpiIC7ulrJeVhSAgyPrKGQV/rRdMirrrqq5+u8AvLf//73Mr7z\nzjsr2+bNm8v429/+dmXTNLjLL7+8snnIirq3Hpai4Vce3uXuvKKurr8ua66eVbjpCjs+AGgOFj4A\naA4WPgBojpEJZ/EyPOrXux9//vnnl/Gtt95a2VQr0xJRfg8tpePnalhBRMTkyZPLWKvdRtThMxF1\nas+DDz5Y2bRbm4cEaFcprfgcUX8XWaeqflICYXhkOpPb9PfzUA9NjfQ5qL+lV+/W0k+u/6k+fe+9\n91a2z33uc2Xsz8O6deuqY0239JQx1Z218XhE/ax6lzed565da5hKpvFRlgoAoCMsfADQHCNTgdnR\nbbG6iBH19tkbCunf8O6WaiiKV5FYsWJFGftf67rt9iq23/3ud6vj559/vow1tCYi4v777y9jrxyj\nW32vzqLZIR4eoO8ta8qO2zt2dK0yFFGHZnmFHv1ts/Auz/rR0BeXQrRC0Fe+8pXKplke+kxFHBnO\nos+jZ0ssX768jL/85S9XNv1Mnkml1aK9ArN+jn4atneFHR8ANAcLHwA0BwsfADTHhKasKa5PqV/v\nKWtZRzJNw/H0sm984xtl7A2Uf/7zn5exaxgaoqKhAxF1CEJExNKlS8vY/9rXRsyuW2gFFg/DyfSV\nYaTvwP9GFkaUNRT3TnvZ76xz/oMf/GBlU63QQ000ZMZTzbTKiYfIfO1rX6uO9Rlwre6+++4rYw17\niairtXiIjOrlrl3r67wi0jBgxwcAzcHCBwDNMaGZG4q7C/p3vm91t2/fftRxRF3xwrfPmtWxbNmy\nyqYuqt9Pjz2KXDMu/H1neMHGRx55pIzdJdBwHr9+VoiREJbRQ+e5NwbSakI6VyNqF9Kb72h4iz9H\nKv14A3OVl9xF9oKm2byePn16GXsGxrPPPlvGHkKmLnM/Es4w5jU7PgBoDhY+AGgOFj4AaI6RSVlz\nDSELCdiwYUMZf+9736ts2uznhhtuqGz6175rdaqbaDUWf2/+un7QcIXVq1dXNtX4/LtwbUbJtBBS\n1sYH/96zRt2qZXlq5E9/+tMy9oZCWjFcdbuIek56VRdNPfPQLw2n8RAV/0yairl3796e1/GG93/5\ny1/KeMeOHZVN5+SgTYMGhR0fADQHCx8ANMfIuLqeuZH1ztRjbaYSUW+nf/e731U2DRHwAqJaycWj\nz/V17kq4S6Buh/fc/eEPf1jG6q5H1L18PVxBvxsPtVFXCnd2Yhi0wK7b1E38wx/+UNlUGnFX98CB\nA2Xsc1ers3jVnylTppSxV0DKXF+36XXctdewLf+evJLMeMKODwCag4UPAJqDhQ8AmmNCNT7VDbK0\nFA/n0GNPS1OdZPfu3ZVt48aNZbxq1arKpo25/b2oTuIhAarNRdThA3rNiLqBsl9Hz3XtJ6tO0U/1\nXxgbssrXrnnpuVmYks8d1dWyasUadhJx5DOg6Lxyvc3DtvS5cj1QnwFvKKR6pM9HTZPLvqexmMfs\n+ACgOVj4AKA5RqYQ6aBFND3URV1fdyW0koq/TrfWXjlF3VKvPuFujkaxu7uimSMaghBRb/X9mgqu\n7eiRyTSZLQtN8tephJJlingolF7T3dmsApK7rFqBxdHXZs2wMvy8sS6qy44PAJqDhQ8AmoOFDwCa\nY0IrMGepPV31QNciVNdz3SLTXvQ6rs2p/uC2rDKt6xaawpbdH63u+KIf3TWb13puPymc2f313H6e\nBz/W62SfqZ/3lt1vrJ8BdnwA0BwsfADQHCNTncXpGhLgf9Hrdj5rYNS1KVBEHWHuW3CPcM8i89UN\nyKL2+9n24xaPHl3d2X6uoXMnc0t9XmXucz+FajN7Fn6V3UOPs0LE/VyzK+z4AKA5WPgAoDlY+ACg\nOSahEQFAa7DjA4DmYOEDgOZg4QOA5mDhA4DmYOEDgOZg4QOA5mDhA4DmYOEDgOZg4QOA5mDhA4Dm\nYOEDgOZg4QOA5mDhA4DmYOEDgOZg4QOA5mDhA4DmYOEDgOZg4QOA5mDhA4DmYOEDgOZg4QOA5mDh\nA4DmYOEDgOb4D0SJbshKsQcXAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 5 ---------------\ndLoss: 0.33\ngLoss: 1.78\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f1384835390>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nyI7/A65FdqkVATcbAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 6 ---------------\ndLoss: 0.32\ngLoss: 1.83\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f13847a5438>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nrkJggg==\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 7 ---------------\ndLoss: 0.32\ngLoss: 1.89\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f1384665c18>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAFAdbHwAUB3/B21adRUCojxBAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 8 ---------------\ndLoss: 0.31\ngLoss: 1.93\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f13844898d0>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 9 ---------------\ndLoss: 0.31\ngLoss: 1.95\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f138438f6a0>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 10 ---------------\ndLoss: 0.31\ngLoss: 1.99\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f13a0d72160>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4wLCBo\ndHRwOi8vbWF0cGxvdGxpYi5vcmcvpW3flQAAG1JJREFUeJztnVusXVX1xidCKRRaKC2lLRfLpVK5\nF2gpUtHUUkCEIIqI+kCM0aAJCYnxwURfTNREnzQxeAkaSIyBqA9qWgNWuTcUChRKmwoN0oJQSoUW\nWigo/4d/MvONz+7RvbfnnO595u/3NFbG3mutfc5cI3N8a8wxD3jvvfcKAEBLvG9/3wAAwFhD4AOA\n5iDwAUBzEPgAoDkIfADQHAQ+AGgOAh8ANAeBDwCag8AHAM1x0Fhe7LLLLuu4TOSAAw4Ix/2uKNHz\n+Dn8Gv3cy77OsWfPnmofeOCBwafH//nPfzqeo5f77vY3+TlXrFjR3Rdhn1x77bVjuvypl/Gpx+97\nX5znvPvuu9WeMGFC8Pn41M/6ebq9V7+3Xp6Bbrnzzju7GtfM+ACgOQh8ANAcBD4AaI4x1fgyRqpL\nTKZ3dKvVZdrDvnSKgw8+uNqu8f373/+utuskep5eNBSlX00Thovs/+y+TFfW773zzjsdffu6hvqy\nazg6zse6SxQzPgBoDgIfADTHwKS6zkiUpWTTZ/fptDtLkfW1fimlHH744eF4165de7X9Gp4GH3bY\nYV19738ptYHhod+SlYMO6vxI+5jPSlR8fCoq2Tj+vew51vP0UrI1EmkxMz4AaA4CHwA0B4EPAJpj\nYDW+frWrkcj/s1fyqsWVUsrOnTs7Xv+UU04JvtmzZ1f7yCOPDL4tW7ZUe8OGDR3vp5ffx0ZS45Os\n3MmXnmVanY5l1+106WUpcZxnGp+TXT8rZ8m0wZGAGR8ANAeBDwCaY2BT3X4rxbPSj2x1ROabNGlS\ntXfs2BF8nhLcdNNN1b744ouD75BDDqm2l6w8+OCD1d6+fXvwvfTSS9XO0v6xThdg9Ojl/6Xp7cyZ\nM4PvtNNOq/bJJ58cfJrqrlmzJvjuueeecKwrOyZPnhx8+uzs3r07+PTZ8d+k3/Mysex51PP0O66Z\n8QFAcxD4AKA5CHwA0BwDo/H1siyl2w4srv/pq/Velui8/fbbHb/3ta99LRxfddVV1fblQ5k2oRqH\n+/Q40yZHolMzDCZZ6YeO3aOPPjr4VNc7/fTTg2/ixInV9jKt9evXh+PVq1dX+5hjjgm+GTNmVFuf\nlVKiru06nurjPq6zztEjsUyTGR8ANAeBDwCaY2BS3ZHYXOh/OY+mC95xRavWv/GNbwTfRz7ykY7n\n8Xt57rnnqv2Xv/wl+JYvX15tL5nRkgAvn8mghGW46LfrkI6JF198Mfg2btxY7Tlz5gSflqX4KqNv\nf/vb4VhT2Pvvvz/4NBX1FUlaiuVykqbhPq5fe+21anuKnMlS3cKMDwCag8AHAM1B4AOA5tivGl+/\nmka3G5j4a3BddpPpX1u3bg3Hl1xySbUvuuii4Mv0BtU3Sinlu9/9brXXrVsXfKor6oZFpeSbH3UL\n5SyDTzYmdQxkm317Zx/t+jN37tzgmzVrVrX9WZkyZUo4/uEPf1jthx9+OPieeOKJantZjC6F81Kb\ns846q9ovv/xy8D3++OMdfdkGSt3CjA8AmoPABwDNMaapbr+dRTKy7/lrcE0hvcPE5s2bq+3p67Jl\ny6rtqzG8KeMDDzxQ7dtvvz34tCRg6tSpwXfUUUdV+6233gq+N998s3Si29UalLYMF9m41tUQjssk\nOj5dwukFTYW9ZObQQw+t9vTp04NP01sv/dLOMc8//3zw6fOopS2lRMmKlRsAAF1C4AOA5iDwAUBz\nDMySNadbTSpbspZ1dfBlYboR0Ne//vXgUy3CeeaZZ8LxzTff3PH6xx9/fLVdG9y2bVu1ffmOdtHo\nRSeF4aJbvcq1a9WdfVypPrx27drgu/TSS6vtyzR9LGmZjJa2lFLKhz/84Wr//e9/Dz7t5HzFFVcE\nn5a+ePmM4n+XbLOlbmHGBwDNQeADgOYY01S335KV7DxZqpu99veU4Mwzz6z2qaee2vF7//znP8Px\nrbfeGo417bjgggs63ptXo//rX/+qtqa2peSV6qS3w8VIlBh5qqvHPna0bMvLULRbkEo9pcQVH6WU\n8utf/7rjZ7Wzyy9/+cvg09TX702fwddffz34dDMu/ztpqtvLHr/hHH19CwBgiCHwAUBzEPgAoDn2\n65K1kei67OfUnN99uhRs2rRpwacan78u1y4rP/rRj4JPtY9Soo7iGzjr79VlN37NXjYp6ha6swwG\n/W6Uo99zrUzHi49d1bld89YSFe8WdNddd4Vj1QO9W/Orr76618+VEpes+TJR/f2qcZcSl6llujZL\n1gAAuoTABwDNMbDlLN2WrDjeCFHZvXt3tRcsWBB8H/rQh6o9YcKE4NNUwtMFX2WhnSq8il1Xbvh5\n9Df6K/qsGwXlLMNL9r9zuSPrOqQSjn9PS6F8rOqmQd5VxVdSHHfccdX2DYU0TfXz3HTTTdX2/Xj1\nd3gHFvV5+p7JWd3CjA8AmoPABwDNQeADgOYY2O4s/XYW1i7HXjLygQ98oNpXX3118Kmm4R2YVTfU\njhalxA1bSinltttuq7a+5i8laoz+av+II46odtZFt5fNlOnAPNhkY9x13myjei1v8Q2FVCt78skn\ng0+Xpbnm7N1adu7cWW3V+0op5YQTTqi2loWVUspll11W7WwTLe8yrvc9GmOXGR8ANAeBDwCaY2BT\n3QxNEfz1vU6ZPV245pprqu0dJvw8iqbBvq/uwoULw/FnPvOZaj/44IPBd8cdd1TbK9w1RfeUQI89\nfe/2dT4rNwaDbNWR4iUcvgGVoqVYixcvDj7tAuSrlXTzIV8d8fTTT4dj3fzn2GOPDb5NmzZV27us\nqITjv1evuX379uDLyllGYiUTMz4AaA4CHwA0B4EPAJpjKLqzZFqIvwafOXNmtZcsWRJ8ukwt0w0y\nsm6wpURNw6+vS3a8c/PGjRur7TqeglY3XGTjKvtf+rK0efPmVds7e59zzjnVdn1YN8PyTbt1nPn1\nfHmb6oP+zP31r3+t9qRJk4IvK8PRZWreHXq0YcYHAM1B4AOA5iDwAUBzDEUdn2sDWp+nHV5LiUtk\nPvrRjwafaipeN6Rdll955ZXg0/ZSrm9ceOGF4ViXt/nSHl0yt3Tp0uDTmiq/htYY+t+i2/ZdaIOD\nR9amzZeeffrTn6626n2O1tSVEjuEe+unc889t+N5vOZvxowZ1fbWbzo+veu41uq5dr1+/fpq+/JO\n/dt4Pe5ILMVkxgcAzUHgA4DmGJhUt5dUTLsc+5IxLSHxDhO6GfgDDzwQfPqqf8eOHcGnabBvKL5i\nxYpwPH/+/Gpfd911wacpyqJFi4Jv5cqV1fZ0RfGyg6xcAPY/Xu6k49w7fWuXE01tS4ldT3x5pS53\n1NKSUuKyySuvvDL4NPV86qmngi/b/Ofyyy8PPh3nWlrj11A5p5RSVq1aVe033ngj+DS99b/TSIxz\nZnwA0BwEPgBoDgIfADTHwGh8+1oKpujrdNcU9DW864baRda1uW3btlXbN0x+//vfX21dklbKf7fv\neeSRR6p9/fXXB5/+Jr+37BW9lgR4B2bKVAabXnZS01IQ1fv8s/4/Vw0sa/3km4Rr2ZS3k/rSl74U\njm+88cZqa2mLo12dS4k63tq1a4NPn51MC/WWWZ0+1wvM+ACgOQh8ANAc+3VD8W7xym3FX3Xr1NfT\nQu3c4p2UdSWHbvxdStxQyFMC73irnTM0RXa8ZEVLZrJu0NnKjQxS4sFA/19emqRyi48z3cTbx4em\niTfccEPwLVu2rNpeoqIbDM2ZMyf4fEPxLPXU8q8XXngh+H7729/u9XOlxE4yvtmR/m2yscvKDQCA\nLiHwAUBzEPgAoDkGpgNz5vM8Xl/Db9iwIfh0aY8vWZs+fXq1r7322o7ndH1Dl8h5h1vXW1Rz9PvW\nJTu+tEi7U3gXW4VlaYNPNq71WJealVLKunXrqu0dkHVZmGvHOia9c4p3eel0L73gO77pWL7nnns6\nftb1eH12XMfvNjb0CzM+AGgOAh8ANMfArtxQvCxl165d1b733nuDTyvezz///I7n8VICTREmTpwY\nfJrq+nTd0Vf9Xj6wfPnyaq9evTr4/HW+0m+z0ZHYeBl6J0sh1edjUMs97rvvvuDT8paPfexjwXfe\needVW8teSslXdWT4eNFyr29961vBp52NXCbSUht/dvRZ8RKZkWg2msGMDwCag8AHAM1B4AOA5hiY\nJWu9aFeqwflGxL/4xS+qvWbNmuDTMhEvJVAtwjuwnHHGGdWeOnVqet/aneKPf/xj8Omm4f763nVM\npd/NzrP7hNFD/w/edUS1rGy5paOlLtoBqJTYTcg3sdcO5bqhvV9fOxeVEjuCl1LKn/70p2r7Zlza\nEcl1Sy1ZcZ/+3tEoWclgxgcAzUHgA4Dm2K/lLN2+ss58XnqiKzB8dYSml1mJjK/G0BQ5m8qXElNo\nT2e1ZKaXjhOkqcNFt+PaSzg0LfYVQlom4jKNjsnf//73wXf77bdXW8uySoklVL5SxFdnTJ48udou\nBen1MwnHn7lu984dDZjxAUBzEPgAoDkIfADQHAOzZK2XnF61kex7Xi6QLQtT/S3T2FyncJ0m0wM7\nnXNv1xxpWLI2GKiO52NHj70MRjVo/56Oc9fx1Ofn1PHp3/Nxrpqf+7JlaXqNQSq3YsYHAM1B4AOA\n5hiYVLeXEg79bLbnZjbtdvR1ftYpwssMHL1GtjdwL6kuaer4od9OOzqWvPRD02AnS62zczrddnnJ\nzjMamwb1CzM+AGgOAh8ANAeBDwCaY2A2G3K6ffWdbebSSzeIfpfWZPSrW2R6Z7/nZNnb/qHfsiUf\nu6rHZRuKO3q9bFz/L92Z++0Cvj/HJDM+AGgOAh8ANMfANCLt9zz9ps9ZyUr2PU8r+k1LR6OcZZDK\nBeD/6eX/2m3K6nQrv/j5s7Ha73jJnqtBkluY8QFAcxD4AKA5CHwA0BwHoP0AQGsw4wOA5iDwAUBz\nEPgAoDkIfADQHAQ+AGgOAh8ANAeBDwCag8AHAM1B4AOA5iDwAUBzEPgAoDkIfADQHAQ+AGgOAh8A\nNAeBDwCag8AHAM1B4AOA5iDwAUBzEPgAoDnGdF/dr371qwOzwUe2H65z4IEHdvxcto9oL3vu+nlG\nm5/85CeDs8npkLNkyZKBGde+d66OqwkTJgTfnj17qq1j3L/nHHRQDBvZPtfvvvtux2t0ux9wL6xc\nubKrcc2MDwCag8AHAM1B4AOA5hhTjW+QyDQ9R3WKfWl8iustqmm43pHpJADdko3Ht99+OxyrVqdj\n3H1+XtUGS4naoZ9HnwHXtdU31ho3Mz4AaA4CHwA0R7Oprk+7FZ/ma1rqU3kvEdDz+mcnTpzY8fp6\nPNbTfhg/ZKUmWfqa+UqJ4zwbu/48vPPOO9XOpJ+xlneY8QFAcxD4AKA5CHwA0BzNanwHH3xwOM40\nBtUwfJmN6xb6WddCXPNTVEcci6U9MD7xkpWsZMTHbrfn9WdFj32sZvr4/izbYsYHAM1B4AOA5hjX\nqW6WMr711lsdfbt27Qq+ww8/vNonnnhi8J199tnhOEsJDjvssGo/9thjwbd58+a93gtAKTEt9RQ1\nS2e1TGXnzp3BN3ny5I7fc5lGz7Njx46O9+lj99BDD622lnOVEp8PLXvZ2/2MNMz4AKA5CHwA0BwE\nPgBojqHX+FyLcF1PUd3AP7do0aJqz507N/jmzJlT7SOPPDL4XLfIrq+axoIFC4LvV7/6VbU3bdoU\nfFk5DbRBtrzMu6V08u3evTv4dFy5xubnnD59erVVqy4lX86m5/Wxq1q6l5eNdrciZnwA0BwEPgBo\njqFPdX3ar3jJyrx586p99dVXB9/s2bOr7eUC2XTdr6HT8kmTJnX0ecqs9/bss892/B60iaa6b7zx\nRvBpmjhz5szgU9lGJZtS/nt8Ki+99FI4vvXWW6vtY/7YY4+ttqfMulrDy8S0FExT6VJiederr77a\n8T77hRkfADQHgQ8AmoPABwDNMfQaX4braEuXLq32cccd1/F7q1atCsd//vOfq+0lAWvWrAnH9957\nb7W/8pWvBN8tt9zS8Zq6LM6voRpOLxuhw3Ch/1svi1Idbf78+cG3bNmyavu41iVjrofr2NnXOPrC\nF75Q7Ycffjj4fve731X7+eefD77XX3+92rNmzQq+hQsXVvuII44IPtUR0fgAAEYAAh8ANMfQp7pe\nXqLHPrXW9OHFF18MvtWrV1f7e9/7XvBpGvqDH/wg+K666qpw/M1vfrPal1xyScf7zjY70uuVEn8T\nKzfGD1n3oClTpgTfddddV+2LL744+LTLymhJH9OmTav2kiVLgu+oo46q9ooVK4Jvw4YN1fZU+7XX\nXqu2d3xRnzMS+/Ey4wOA5iDwAUBzEPgAoDmGXuNzVCfZunVr8D300EPVfuGFF4Lv6aefrvYJJ5wQ\nfGeddVa1XRvcsmVLOP7yl79c7SuuuKLjfXrJimohrtOg641Psv/r6aefHo7PPffcaqumV0ocL64d\na1mIj6us648vZ1NdzbU6XQq3ePHi4Hvuueeq7c+Klqn4ffumSYrqeplWnsGMDwCag8AHAM0x7lLd\nbFOU9evXV9s3XjnllFOqvW3btuD729/+Vm1dmVHKf6ck3//+96vtTUq1c8X9998ffJpqe4cL/U3Z\n3rww3Gh5S9bs00s4NE392c9+Fnw//elP93r+Uko544wzqq0rLEqJKzVKKeXKK6+stndZefnll6u9\nbt26jj7vKqNj+ZBDDgk+/b0Z/ZbvMOMDgOYg8AFAcxD4AKA5hl7j827JiusGqp15x9eTTjqp2p/4\nxCeCb8aMGdX27hd+jQzVUZYvXx58qn94KYG+2s9+LwwX/r/U0gzvwq3ametav/nNb6r985//PPg+\n//nPV9uXgWlZzJNPPtnxeqWU8vGPf7zaWqJSStSrH3nkkeDTchrtFFNKfHZc11bdcjQ6EvEUAUBz\nEPgAoDmGPtV19JW9T4m1LMRfl59//vnVPvPMMzuesxf8tb9u2OJ75x5//PHV9mk/zUaHlyxNyzqL\n6GY7pcSx46Unmk5ef/31waclK/fdd1/waQNR7zr02c9+Nhzrs+MrR7Qxqa/q0GfH/xbZyhH21QUA\nGGEIfADQHAQ+AGiOodf4Mp0k2xg8WxbWS8cH1yZUf/FNi3RZ2jHHHNPx+t6ZAo1veOn3f+c6nnbz\n8U20dDMqLzXRJZa+EdDdd99dbe+qnHVy8c5Guvm43kspeQca/U1+vdEe88z4AKA5CHwA0BxDn+p6\nWqqvz7MuFp5K/OEPf6i275Wrm/9s3749+ObNmxeOtSmjlhKUEtOAO+64I/h02u9dXejI0h6eMuq4\n9jKpo48+utraZaiUUhYsWFBt77iizU33hY77H//4x8GnnY581VG2J7T+prFutsuMDwCag8AHAM1B\n4AOA5hh6jS97De4an3a19e7MuomQLxfauHFjtb3DxJ49e8LxqaeeWm0vO1DtbuXKlcGnnTPowDJ+\nyZZi6Xj1JZWqgXkplo5l7yx+0UUXVVuXRe4Lv8YNN9xQbV/6duGFF1bbf5Pejz87+nt9zGcbCtGd\nBQCgDwh8ANAcBD4AaI6B0fj6zeO9DY4u98qWpU2bNq3jOb2mSGv1tKavlLgpsl/f21mpxqi1V6XE\nnd3Q+MYv2bjW/7uPXR1LrpVpTaovWdOx7N3CP/e5z1Xb6+/Wrl0bjnXcu1Y4c+bManuXZ605zJ7x\nrI6PtlQAACMAgQ8AmmNgUt1eprOasvomxZoSnHjiicGnpSe+JEhfu/t0XVML3SC5lLxEwJea6b16\nGYy+vs86zkAbeDmLjgntuFxK7Ih82mmnBZ+Os1tuuSX4Hn300Wp/5zvfCb6TTz45HM+dO7faW7Zs\nCb4333yz2v48uhSldPvMU84CADACEPgAoDkIfADQHAOj8fWCameuhZxzzjnV9s2/tQOydo0tJWqD\nrkuopjFr1qzgO++888KxvpZ3PVA3W9bylVKi5ujlLHpOujGPHzLtyvVhHZOuAavm52NXtTp/HubP\nn19tL+/y8yxcuLDauoF4KbEjs5ZslZKP1247nVPOAgAwAhD4AKA5hiLV9Wm3VrXPnj07+C699NJq\n+6Y92mXZz6kprKeaU6ZMqfYHP/jB4NPX/H5NLRcopZSHHnqo471lnaNJb8cn/n/NVuzoZ7NSFx87\nunLCv6cdifxe/LM6Xr0LuXYd8nGtq0V8dcb+LNtixgcAzUHgA4DmIPABQHMMhcaXaVwnnXRSOFbN\nzzWTT37yk9W+6667gk81Ni9ZOfvssztezzuwqG7iu7VpFw3vzqzaCN1Z2sDLObKuw6qPuU9LobwD\n8+OPP15t7zp+4403Vts7t/g11q9fX23fBVCfF9+9UPV4f1Z0nI+13scTBgDNQeADgOYYilTXX4Nr\n6qsbeJcSX8P71Hrp0qXV9pRAV3UsXrw4+LTjhTci9U4uzz77bLV1k/BSYlmM/ybS2/FJtjqjl1UN\nWn7l41pXeWinllJiWqoNQ0sp5Ytf/GLHc3qXFU2ZHb2+n0cZ603DM3jaAKA5CHwA0BwEPgBojqHQ\n+PxVd9apIkP1v0996lPBd/nll3c8p+oWugSolFI2bNgQjp955pmO11fdhi7LbeA6XtaRRD+bdehx\nrUyfBy+T2rRpU7V9gyvXAxXX+P7xj39U20tfvCP0MMCMDwCag8AHAM0xFKmuo+mCVpSXEhsvzpgx\nI/iyDijKK6+8Eo61REWn/Hu7vk77/dV+VplPB5bxSfZ/dl8mhehY8jRYy0m8vErH4wUXXBB8Kv34\nvfg419UhvnIj6w6Trc7YnyVczPgAoDkIfADQHAQ+AGiOodD4XAtQnWTjxo3Bd9ttt1Xbl5dNnTq1\n2t5FVnU9L1lR3cRf5WfdkjMdEU2vDbJyll58mY6WlXfphveLFi0KPtUGvSTl7rvvDsf6DGZjN9Pt\n3Jf93tGGGR8ANAeBDwCaYyhSXZ++67HvP6p72W7evDn4tOI928DIfZMmTerxjgH2TlbO0m/nlux5\n0Aa3K1euDD4tS/F9np944omO1x+pLiv7U+5hxgcAzUHgA4DmIPABQHMMhcbXC6rVuYagmobrJLp8\nJ+uMQRkKjBS96Hj62WwppKO+VatWBZ92EvJuLN6hXMu4XEfUex2WTuLDcZcAACMIgQ8AmmMoU91u\nK7572Zs064zRb3pLBxbol2xVR7b5lqehmhZ7irx169aO11Ppp5QoIWXp7LCMeWZ8ANAcBD4AaA4C\nHwA0xwHZ5icAAOMRZnwA0BwEPgBoDgIfADQHgQ8AmoPABwDNQeADgOYg8AFAcxD4AKA5CHwA0BwE\nPgBoDgIfADQHgQ8AmoPABwDNQeADgOYg8AFAcxD4AKA5CHwA0BwEPgBoDgIfADQHgQ8AmoPABwDN\nQeADgOYg8AFAc/wfP0PnAc0vpUYAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 11 ---------------\ndLoss: 0.30\ngLoss: 2.02\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f13843bd860>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nTkSuQmCC\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 12 ---------------\ndLoss: 0.30\ngLoss: 2.05\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f13848cb5c0>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4wLCBo\ndHRwOi8vbWF0cGxvdGxpYi5vcmcvpW3flQAAGndJREFUeJztnVnsXVX1xzcytmUopS2FjpSZlsog\nUMQKpVZkSBhCCIPRoMEQNFFR33wx0Sd9UUlQSBrEmBhDGoKGoNHSALVAmUsZ2tJSaAuUDnSAMur/\n6b/zXV97d++9uffXe37783laJ+vec87tb5/VvdZZw37//e9/EwBATXxuX98AAMBQg+EDgOrA8AFA\ndWD4AKA6MHwAUB0YPgCoDgwfAFQHhg8AqgPDBwDVccBQXux73/vewJSJ7LfffuH4s88+a/nZ/fff\nvy/XVP7zn/+09Tm/z899rrv/u+64447WF4GOuPjiiwdmXQ8aWhlWWte9YtGiRW1dhB0fAFQHhg8A\nqgPDBwDVMaQxvkGm3ViZd7PR2Jyfx3Xtxjv8XvQ83cb0YPjS7rry9aif9e+V1nUn19djf3aGIubX\nCp4iAKgODB8AVMewdnV9K61bbU8LOeCAA/b4Of+sfm5PqIvgaTD6Xb+3Tz/9tHjePZ3fr0FT2Trp\nJGzSCl+r/r1OUqxasS9dW4cdHwBUB4YPAKoDwwcA1TGsY3ylmJfHMPSz/r1SyZrHNw466KCW59E4\n3scffxx0GrsbOXJkSx3pLOD0Ip3E13En6SxNXJ/NuEsAgB6C4QOA6hjWrm7p9bmnpezcuTPLo0aN\nCrpTTjklyyNGjAi61atXh+OPPvqo5fXXrVuX5WOPPTboZsyYkeUPP/ww6NasWZPl3bt3B5264Z24\nJ9Bc/O+qa+CTTz4JOl1LHkLR9Vmq6kgppQ8++KDl/ej1S1VHVG4AAOxDMHwAUB0YPgCojmEd4/OY\ngsYfPGYxZsyYLH/rW98KuilTpmR58+bNQefxwLFjx2bZ4y0aY9GYXkoxdrh169agW7hwYZZfeuml\noGtiKgH0Fl1nhx12WNDNnj07y8cdd1zQvfPOO1l+7bXXgs5LKHft2pXl7du3B52mcHkMWr9XiumV\nUs/6EQvkSQGA6sDwAUB1NMLV7VWahroERxxxRND98Ic/zPIxxxzT8vrbtm0LOj9WV+Opp54KunPP\nPTfLhx9+eNBpSsCRRx4ZdAcffHCWDzzwwKBrtzMGNItS9ZA/D7omvv71rwfdl7/85Syra5tSSo88\n8kiWly1bFnS+BvWa7uqefvrpWfbnStO9Oklnade97bYjETs+AKgODB8AVAeGDwCqoxExvlJMr9Rl\n2XVapnbZZZcF3dFHH93yGu+//36Wf/SjHwWdxwOnTZuW5Z///OdBN2nSpCy/8MILQaexwQ0bNgTd\nihUrsuxdXfQ39WrYOAweGmPzGN8ZZ5yR5blz5wadxpL/8Y9/BN2dd96Z5Xnz5gWdpmWllNIzzzyT\nZY9rT548OcsTJ04MOk3h8lQXpZPnuBfwZABAdWD4AKA6GuHqlii9znadZphPnz496EpNGe++++4s\ne0b7/Pnzw/Ghhx7aUnf++edneceOHUGn7u39998fdPrZQw45JMHwp5NUj6985StZ9nQSXa+PPvpo\n0M2aNSvLmmqVUkrLly8Px/q8eCqWVoR45Yim0GgHpJT+NzVL6XfnFnZ8AFAdGD4AqA4MHwBUR+Nj\nfCX8tb++TnedxgPXr18fdAsWLMjyOeecU7zmqlWrsnz11VcH3Zw5c7KsnZpTSumxxx7Lsnd1Hj16\ndMvraXoL6SvDB/9baqxOOwmllNKJJ56YZY9rb9y4McveneWoo47KsndnWbp0aTjWbkJXXnll0J1w\nwglZ9vi4PnPedUh/U2n4Vy9K2xyeFACoDgwfAFRH413d0hzRUucSbZCYUtx2+2v3s88+u+X3Hn74\n4XB84YUXZlm7VqQUUw3cnV25cmWWS0NhPJ1GXYRS9js0C5/lrKGZ8ePHB52mkHhlj6ZJaYVFStHV\nvfzyy4PuqquuCsfqXmsaTEoxxUqrnFJKadOmTVl+4okngk7XsqaapUQ6CwBAz8HwAUB1YPgAoDoa\nH+MrxbF8+Ld2YPbX9T5gXLnllluy7LE5L30766yzsuxxGi3fWbJkSdDp4Gcv+/GYo6IxPmJ6wwcf\nVKXH2uUnpXKH7nHjxmXZB2XpmvMB9zNnzgzHEyZMyLKXrOmz4/Fp/Z7H8UrdWvoNOz4AqA4MHwBU\nRyNdXX3VXRpg4tngqnv66aeDTrfdnuGu2353AXyurrq3mjWfUkp33XVXlt97772g05QAn/nbbcoK\nM3ebi/9d1YU977zzgk7/tt71RzuyuGup6SSehuLrWj976qmntry+u7PHH398lr3iRIcW+fr0yqpe\nw9MAANWB4QOA6sDwAUB1NDLGV+rcoLpSrMxjClqK5ufU2IS/yvfPapncPffcE3SawuJdXjSmUSrD\n6yRlhbhes9C/l8fcdIjP1KlTg07jylu2bAm6xYsXZ1lTW1KK6V5vvvlm0GmqS0pxqJanzJx22ml7\n/A0pxY7kHjdsl04GkbcLTwYAVAeGDwCqY2BcXX993a2bpttgr8bQY6+qWLt2bZa94uNrX/vaHs+/\nJ/R3+BZdu7WUGqH6Nfr9ah8Gg9LaUlfTqyzU9fTnZt26dVnWTikpxaoKrxTx5+PFF1/Msq/Hn/70\npy2vr/e2t2u0grm6AAA9AMMHANWB4QOA6hiYGF8/8G7F2sXC4wbaucJf+5fijR7H0zKck08+uaXO\nhw1pGoynC6iOFJXhi/6dPT79hS98Icseg9Y14QPFNYVk27ZtQaddXrxzs6dt6Xp95plnWt63r11N\nKfMUGX12hjqOzVMEANWB4QOA6sDwAUB1DEyMrxd5e3vDW0EpOkntmmuuCbrSvXlp0Zo1a7LsJXMa\nb/EJcBqP9HwnjfeQ0zd80ZiXx8qmTJmS5dKa9+9pzM/jhm+88UaWdeJaSv9b+qadxz3/TuN/fn0t\nhfNO4u3m8fUDdnwAUB0YPgCojoFxdTuhNGBbt9reDVZf2XuHi9tuuy3LPjBF8TSUxx57rOU1tKty\nSnEwkd+buhJvvfVW0OHe1kGpC4+uCV+DupbefvvtoNNQjK8rDf34WnU39Etf+lKWv/Od7wSdPnPe\n5XnZsmVZdvfZn4GhhB0fAFQHhg8AqgPDBwDVMaQxvl61ntL4h59DU0E8/jd27Ngsf/Ob3ww6nwDV\n6np///vfg27hwoXhWO/H44hnnnlmlk866aSg0yHiXlqkpT6UrA1f9G/r8bBHHnkky5raklJK06ZN\ny/KGDRuCTltPvfvuu0Gn6VbegVnPmVJKN998c5Znz54ddPpcv/zyy0G3aNGiLHuqi/5eStYAAPoM\nhg8AqmNIXd2hcNM0O92z0W+66aYsT548ue1zaufaBx54IOguueSScKyDypcuXRp08+bNy7K71qNH\nj86y/ztpakEnw4ZgsPG/pbp7nl7y2muvZflPf/pT0M2YMSPL3p1Fh1rpGkspVm7oOVJKadasWeFY\n3VvvDqOpWPfee2/Q6RAvT5EpdSvvR9dlhR0fAFQHhg8AqgPDBwDV0YiStZK/X4p5+TQqTS8pndNf\nrf/lL3/J8vjx44POY4WvvPJKlmfOnBl02tXWO95q+ZBfnw7Mw5PSGtRB3CnFNbB8+fKg0wloc+bM\nCbobbrghyxpjTinG3Lx8zO9Nu5drB6KUUlqwYEGWn3zyyaDTjkS+dkuTBfsNTxEAVAeGDwCqoxGu\nbrevur3xqGbDuxus5/TvrVq1Ksvu6q5cubLlZ7VSI6X4at+7aOh5vBEpgLqlnuqi60WHZqUUXWat\n4kgpVlJ4lZOmuqSU0qOPPprl+++/P+g03Utd25RieplfY6jdW4UdHwBUB4YPAKoDwwcA1dGIGJ9T\nGkSscQONPaQUO6n4a389z+LFi4NOB4F7bNAHCmkHGO9Gu2TJkixv3bo16HwQi0LJWnPpNj5dioeV\nhvTs2LEjHK9YsSLLnk6i8T9/Vv785z+H4+effz7L3jmmNERL07YGKRVrcO4EAGCIwPABQHU00tUt\noa6FuwtaVaFy6RwppTRu3Lgse8XFxo0bw7G6IZ4Wo40g3SXQ1/5+fSo3mku3KRv+vVKVg1ZVrFu3\nLuh+85vfZNm7Fen3fICRr2vFu7Pod/3eBnW9DuZdAQD0EQwfAFQHhg8AqqPxMT5/tV+KhWiJjsfY\ntOzHv6cpKzr4Z0/XLw1N0fOWOlV4jG9Q4yQwdOja8di14iVjuq7Xr18fdLpWfRCQxv/8s4NUetYt\nPFEAUB0YPgCojsa7uqVKBnc7S26obvV96+5ucemcpfspueHtVmT0ajYxDA1DMUSntHZ0XXuzUV1L\nvsbdnd2XTUP7AU8NAFQHhg8AqgPDBwDV0fgYXyeUulq0m06ytxhbKY6on+22ywoxvWbRbTysk9ig\n6jxWV4pPl9agr7N2B341Jf7HUwQA1YHhA4DqGHaurrqapeqI0vdK7M3VLOlL9wag9KqrSz+u0a/z\nDCU8fQBQHRg+AKgODB8AVMd+DK8BgNpgxwcA1YHhA4DqwPABQHVg+ACgOjB8AFAdGD4AqA4MHwBU\nB4YPAKoDwwcA1YHhA4DqwPABQHVg+ACgOjB8AFAdGD4AqA4MHwBUB4YPAKoDwwcA1YHhA4DqwPAB\nQHUM6Vzdiy++uO8DPnRerc/KbVd3wAHxn+XTTz9tqfPz6Gd9du5nn31WvPf/pzSn1M/Z7jxgZ9Gi\nRc0bhjqgXH311ft0cE23c21Lz4PP4tl///1bfrYftDsLyH/7woUL2/rHYMcHANWB4QOA6sDwAUB1\nDGmMbygoxR/ajU18/PHHbes85qbHGhdxncYCXdeL3wD1oPGwTuJ9pbXk5ynFp9u9fif3pp/1eF9J\n1y7s+ACgOjB8AFAdw87VVUpbZE9L0c+67qCDDsryBx98EHQll9Xdg4MPPniPn4N66IWbVqK05kvu\nqruhvj5L6SwHHnhgy/Pq81H6vX790md78e/G0wcA1YHhA4DqwPABQHUM6xhfKW7hcTyNU+zevTvo\nNKahcbo9XUM/6zEVvX6p9KwU/yOdpdn0I67XLp5epfh9+TrT45LOnwc99uvr9zr5d+m2RE9hxwcA\n1YHhA4DqaLyrW3ILfWv90Ucf7VFOKVZkjBo1KugOP/zwluccOXJkOH7qqaeyfMghhwTd2LFjs7xj\nx47ieZSSiwLNott0ll50YPHQi6aaeErKhAkTwrHqfV3r71i7dm3QafqXpoX5vXXy+7qtVAnX7upb\nAAANBsMHANWB4QOA6mh8jM9frWuayocffhh006dPz/L8+fODbu7cuVnWWFxKnZWXaUxj/fr1Qffc\nc89l+a9//WvQvffee1n+5JNP2r4eNJdSmVa3MS9H43p+zhkzZmT5xBNPDLpTTz01HGvMz2N1+syt\nXr066O67774s+/Og7K0DdCvozgIA0CYYPgCojka6uu2+Bp88eXI4/uUvf5lld2d7xWGHHZZldx+O\nP/74LF9wwQVB99vf/jbLjz/+eNCVmptCcyl1UinRSdWPhk3UtU0ppeuvvz7LY8aMCTpfZ3oer3o6\n6qijsnzkkUcG3a5du7L8+9//Puj09/t9l/4t6M4CANAFGD4AqA4MHwBURyNjfIr7+xpj+8EPfhB0\n3cb1NCXAS838+q+//nqWR4wYEXQnn3xylidNmhR01113XZY9JWD79u1Z7tVAcdg39CI+Vfqbe0dw\njdVddNFFQXfcccdl+d133w26F154IRyvWbMmy/4M/PjHP86yl15qXNvjhlom6uu6311s2PEBQHVg\n+ACgOhrp6uqrbq9y0M4RU6dO7er8ixcvDsda1fGTn/wk6Hxr//TTT2dZU1RSKleAaOrNuHHjgk5d\nXWg27XZncV1p2I/qSgOupk2bFnTaoehvf/tb0G3atCkca9XF6NGjg047t3gain5WuxylFN3rfszO\nLcGODwCqA8MHANWB4QOA6mhkjK80/Pv999/P8quvvhp0WlrjcYN//vOfWf7+978fdPfee2+Wp0yZ\nEnTacTmllG6//fYsexdbxWMxb775Zpa1U0tKMaZDyVqzabcDS2mIVemzHkc+7bTTsuyxY72XzZs3\nB53HA/X68+bNCzrt1uL3retcn8093Wure+tVF5tw7a6+BQDQYDB8AFAdjXR1FXcBdu7cmWVv9qlD\nhDQTPaWUtmzZkuVf/OIXQbdu3bosP/nkk0F3ww03hONzzjkny+6G67b/jTfeCLqHHnooy+7qaoqO\nZ+bDYNOtK1ZK7/Bwh64Jb757ySWXZPmII44IOk1n8VQTd0PPPPPMLJ9//vkt781DOBoK0mfTr6lV\nHClRuQEA0HMwfABQHRg+AKiOxsf4St1K/vWvfwWdln5pLC6llM4444wsH3rooUGnXVW8q7KWBO0N\nfZ1/zz33BN2zzz6bZY8LefwDhj8ex9N17etDB1x5B+STTjqp5fe03NMHimuXo5RSOu+887LsA8X1\n3lauXBl0OmzIhxSV1jUlawAAPQbDBwDVMbCurrqwpax1dwl0y+7pJNo5xdNCtCnjrFmzgs639u3i\nc0R/97vfZdlTbbSqpBP3GQaPkpvWbXqL4ufUNX/66acHnbqXnmpSSmfxjkDq+qprnVJKS5YsyfId\nd9wRdPrsuDvt99MNzNUFAGgTDB8AVAeGDwCqY2BjfKUhyYrHCdTnP/bYY4NO43rLly8Puq1bt2bZ\nYxElNE6SUkp33313ln/2s58FnabM6BCWlGKZmsdQSnEaGDzajTuV4n8e1y51JNI498aNG4NOOxT5\nsC3tCOTX07WaUkw9eeKJJ4JOSzz9N2ns3LuzdNtlpRdxUnZ8AFAdGD4AqI6BdXVL6Fa31LDRZ4Vq\ndwrPGl+xYkWWdbhQSvFV/ssvvxx0OlM0pZR2796dZW0CmVJKRx99dJbdJVH3uvTan7m6w4dSg81S\nw1kPd+iaePHFF4PurrvuyrJ3Z9Fwy1e/+tWgmzhxYstr6uzolGKDU6960m4xvnY19NRJs9FeVHKw\n4wOA6sDwAUB1YPgAoDoaEeMrDVAuxfhKaTCeEqAdmZcuXRp0q1evzvLjjz8edF7ONmnSpCx7Nwrt\n3uwxnPHjx2fZYzjt/ibYN5TSKzqJR5XSWUqxXF2DxxxzTNBpmpaXpWnMWddtSv+7PnXdeQrXtm3b\nsuzDxjWW7v9Oek4GigMA9BkMHwBUB4YPAKqjETE+R31+z8fTlk6lvKELLrgg6K699tose2mP5gP6\nUGbP1dMyOY9NaMzP8wG1TM3bUhHXG2z6EoMq/M1LnYx97ei6mj17dtBdeumlWd7boHqNMXq7NX2u\nfEJgr6bM9RqeKACoDgwfAFRHI1xd3/aXXvvrZ/U1e0px8IqXmumrfR3CklLcvm/atCnofLjLKaec\nkuXJkycHnXbH9U61OrS839t8GHy8Q7i6sJ5OMmrUqCxPmDAh6M4999wsX3HFFUHXSReit99+u+X3\nNLzjz6Peq6eQKf0oSyvBjg8AqgPDBwDVgeEDgOpoRIzP/X8t6fKSMY3reZxE43renVljExrPSCnG\n9bTNTkopvfXWW+FYBy/r5DS/by8f0nQCv28YPrTbddjjaNrubOfOnUGnQ+49jvf5z3++5TkVj2tv\n2LAhHOuEQI+d6+/w50Nj7n6N0v30e1IdOz4AqA4MHwBURyNc3dKrbdeNGDEiy7feemvQzZgxI8ue\nIqMdkX/1q18F3Re/+MUs+yAgHxo0ZsyYLHvagXZ5XrlyZdBpNj6u7vCl3a4j3qFHU0HUfU0ppe9+\n97tZ9u4sus491WTLli1Z/vWvfx10nhYzffr0LP/73/8OOh1oNHXq1KDT58GrOvR+Su5rL1xbhx0f\nAFQHhg8AqgPDBwDV0YgYXycdmDU2MWfOnKArdbzQDhfPPvts0Gmc4uyzzw46TV9JKU6yWrt2bdD9\n4Q9/yLIPV/YJWNAcOim3KqWzlOJxWrLmw751zXuKiKaQeFeVm2++OcubN28Oum9/+9vh+KWXXsqy\ndiRPKXZvvvDCC4NOY5XPP/980G3fvj3LpXK2Et2WtrHjA4DqwPABQHUMrKtb2vaXurOoy6iDwPeG\nVnLccsstQacVGN7AdOTIkeFYs+offPDBoNOGpj54mY4sw4du0y90LXs6i+LVSvpZ/54OG9Lh4inF\n4VeXX3550Gm3oJRSuvPOO7PsKVyaNuY6TXUppeiUoHIDAKAHYPgAoDowfABQHQMb4ysN0VafX7tW\npBTLYjop/dK4ib7m9/N4TNE7Vdx3331Zfvjhh4NO03D8N2nagetKw6Rh8Gi3A0sJ/56WP3r8TY99\noLfqPB49f/78LPtA8R07doTjuXPnZvnGG28MOi2h8zJN7WzUyTruxb9hCXZ8AFAdGD4AqI6BdXUV\n3yLra3CfMapNRLVSIqWUvvGNb2TZG4GWUmR27dqV5VWrVgXdggULwrFmp3vKimbVl9IVcG2bRSfd\ng9p12zzVQ0Mhy5YtC7rXX389yz78SsM0uo5Tih1XvIGoH8+cOTPLnk7zzjvvZNmrOvS4tOYdGpEC\nAPQYDB8AVAeGDwCqoxExPkfjFh5v0FjIH//4x6DTVJNx48YF3cSJE7Ps8Q0tNfP0Ge3qklIc7uyx\nCY1xlAahE+MbvpTSNFRX6kjkQ3s0ZcWHBOln/Xoag/YUKl/Xmt7inVw0du3Pjt+r0m3KSi/KO9nx\nAUB1YPgAoDoa6eoqvpXWLfvYsWNbfs9nkz733HMtP1tKQ9EGkSlFF6XkzlKdMXwouWmduGXtDiLy\nZqPqBnt6V6nqSCmtVb8ff3ZUp/eyp+NWDHV3InZ8AFAdGD4AqA4MHwBUR+NjfB5zazclwOMkGtPw\neIMee+yj1AGGOF4ddBvH6+RzpXWtOk8nUfx7+uyUBh+lVI5ztxvHK9HJwKZewI4PAKoDwwcA1dF4\nV9cpNTDVLbq7qLrV9hQZ7ZThW3Lf5pcGv/SjoSI0i5IL1246SyffK6VQlVzdUkeU0nk6cXv35fPA\njg8AqgPDBwDVgeEDgOrYj0HWAFAb7PgAoDowfABQHRg+AKgODB8AVAeGDwCqA8MHANWB4QOA6sDw\nAUB1YPgAoDowfABQHRg+AKgODB8AVAeGDwCqA8MHANWB4QOA6sDwAUB1YPgAoDowfABQHRg+AKgO\nDB8AVAeGDwCqA8MHANWB4QOA6vg/apuebIrqT0MAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 13 ---------------\ndLoss: 0.29\ngLoss: 2.09\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f1384421ac8>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSUVORK5CYII=\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 14 ---------------\ndLoss: 0.29\ngLoss: 2.12\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f1384551c88>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n/wBAvVFbWkueXgAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 15 ---------------\ndLoss: 0.29\ngLoss: 2.12\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f138467ef60>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nfQAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 16 ---------------\ndLoss: 0.28\ngLoss: 2.15\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f13845dccf8>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 17 ---------------\ndLoss: 0.28\ngLoss: 2.19\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f1384625518>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRN4CmDlEYgAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 18 ---------------\ndLoss: 0.28\ngLoss: 2.20\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f1384e8f470>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 19 ---------------\ndLoss: 0.28\ngLoss: 2.21\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f13848f0470>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nA5MqGQAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 20 ---------------\ndLoss: 0.28\ngLoss: 2.23\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f1384108160>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRK5CYII=\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 21 ---------------\ndLoss: 0.28\ngLoss: 2.25\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f13633994a8>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 22 ---------------\ndLoss: 0.27\ngLoss: 2.28\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f1363274a20>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nPgAojv8Bfc1iDaUUg4MAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 23 ---------------\ndLoss: 0.27\ngLoss: 2.27\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f138d58a7f0>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n4APgDgMfAHcY+AC4w8AHwB0GPgDu/B++THKchojEmAAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 24 ---------------\ndLoss: 0.27\ngLoss: 2.29\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f13631726d8>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nOEh8ABCO/wE5TSI2ET8mqgAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 25 ---------------\ndLoss: 0.27\ngLoss: 2.29\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f13a0644080>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nHwCEg8AHAOH4Pz8SK9gGX8LVAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 26 ---------------\ndLoss: 0.27\ngLoss: 2.29\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f1384720630>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nHwBkB4EPALKDwAcA2fF/fXxqtA096TAAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 27 ---------------\ndLoss: 0.27\ngLoss: 2.33\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f1384007630>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nHwC4g8AHAO4g8AGAOwh8AOAOAh8AuOP/iMjAG6xqWkQAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 28 ---------------\ndLoss: 0.27\ngLoss: 2.32\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f1384890b00>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 29 ---------------\ndLoss: 0.27\ngLoss: 2.31\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f138404de80>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nB4EPAIqDwAcAxUHgA4DiIPABQHH8D67KP4yCYN2nAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 30 ---------------\ndLoss: 0.27\ngLoss: 2.35\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f136329ba58>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4wLCBo\ndHRwOi8vbWF0cGxvdGxpYi5vcmcvpW3flQAAF29JREFUeJzt3WeMlNX3wPGLSGfpZQFpgoBg1wWR\nZkEDbxQLRBMLGjBG3/iC+EbFBKMmGjWGECNRjEZFxRY1umgsNEGREjEoIEivrpRl6ej/jb/7P+fA\n3J1d2GFmzvfz6jw5zDOz4c7Nc8/cUu/ff/8NAODJWWf6AwBArtHxAXCHjg+AO3R8ANyh4wPgDh0f\nAHfo+AC4Q8cHwB06PgDunJ3LNxs7dmzBLxOpV6+eurYrX2xe+ueff7K+b6bc6VppM2vWrMxviBoZ\nMmRIQbTrVNutrl3Ltnv22Zm7jVT7zMUqsQULFmTVrnniA+AOHR8Ad+j4ALiT0xpfMUjV6UJI101S\ndbxs7wnUVqoeXV2tWtb17Heguu/E/5x1Vv48Z+XPJwGAHKHjA+AOQ92TqMnP/jWRGrKeyn2BTFLt\nqiZlmWPHjsXYTmdp2LDhSf+dle2QOBd44gPgDh0fAHfo+AC4Q43vP7KmYX92l7UJW6ez/zZVx6tf\nv/5J72nf38qn2ggKS6qOJ9uubbf2ukmTJjE+evSoyu3fvz/Gtv4n23zqu5LrKVs88QFwh44PgDtu\nh7qpn++PHDmicvLneuvAgQPqumnTpjG2j/1ySGDJf2uHBHK4cPz48Yz3gA/ZTlGxbNuR7cqSQ9sQ\nQqisrIxxVVWVyt1xxx0xbtWqlcp98cUXMd67d6/K1cWuQ9niiQ+AO3R8ANyh4wPgDjW+/8if6Pv3\n769yN954Y4xLSkpUbteuXepa1j9s7vfff4+xrSPu2bMnxn/99ZfKyRpjdTvlwh9ZH7Z1vNRSM9kG\nbV350KFD6lq2u6lTp6rc0KFDY2ynuuzYsSPGs2fPzvi5rbqu//HEB8AdOj4A7hT1UDc1LLSPz23b\nto3xvffeq3LdunWLsf1JfvXq1epaDhHWrl2rcn/++WeMR48erXLt27eP8WeffaZymzdvjnGjRo1U\n7kxOCUDupKawyCGjbQMy16xZM5Vr0KBBjGX7C+HEYaks8QwbNkzlUqsz5Kqj1BQyprMAQB2j4wPg\nDh0fAHeKrsaXbd3g8OHD6vqcc86JcZcuXVRO1i3efvttlXv44YfV9ciRI2O8atUqlZN1khdeeEHl\n5FIfOyXg3XffzZijrgfZ5u0yNDm9Zdu2bSon27ndAcjWsufOnZvxPSS7hFO+zk5fOZOHj/PEB8Ad\nOj4A7hTdUFc+Ituf1lMbL3bs2DHGqVUddvg6YMAAdV1aWhpjuwJD/ls5fSYEPbXg/PPPV7nGjRuf\n9LOgeNmhpxxe2vYpV2DYFUGyzduhpmxLFRUVKvfBBx+o64suuiibjx1mzJihruWKpBYtWqhcapNU\nhroAcJrR8QFwh44PgDsFX+Or7W601u7du2O8c+dOlZO7z1p9+vRR11u2bIlxr169VO6BBx6IsZ0S\nID+r/CwhhLBv376M789B5MXJ1qdTudQOLPLf2hrbwYMHY2xr1WPGjMn6s8ppMi+99JLKderUKev7\n5BJPfADcoeMD4E7BD3XtcDa1ckNe2yHBypUrY/zRRx+pnJwiYIe9dmPSgQMHxnjixIkq17p16xP/\ngP/I6QSffvqpysnZ96nNG+GD3WxUTn1JnWsrh7Yh6B1ZpkyZkvF1lv1evfbaazHu0KGDyqVKManp\nZXWNJz4A7tDxAXCHjg+AOwVfMErVEFI5e0i4POxb1vtC0DvX2h2Qx40bp64HDx4c4+bNm6ucrGPI\n3ZhDCOHll1+O8bp161RO1ltSNU0Uj5r8v6Z2QJa7EMlpLyGEUFZWFmNbm0spLy9X19OnT49xv379\nVE7WxPOpPs0THwB36PgAuJM/z561ZId+8lHf7nCRIoe+9jxceR+5YWkIIQwaNEhdN23aNMZ2M8fv\nvvsuxtOmTVM5OQyxB7+kdrFAcbJTVrIdJtppKLI0Yw+4uv3227P+PHKnoVdeeUXl5IamdspMahhu\n/0aJc3UB4DSj4wPgDh0fAHcKvsZnpXZgluxP+6l/27179xjfc889Kmd3vJDL2x577DGVW7FiRYzt\n8jW5y7KtadSkVonikNq9x9b7ZK3M1tiuueaaGE+YMEHl5C7g1e2AvHHjxhhv2LBB5eR3wLZVed/U\ndy61vLQu8MQHwB06PgDuFPxQN/WInsrZR+kmTZrE2D6ujx8/PsZ2Oou9z9atW08ah6A3JrWHwsiD\nX+zP/ExhgZTanWXEiBEq9+CDD8a4Xbt2KifbVXXlFNnuR40apXJLly6NsT1XNzWcle+Z6zbOEx8A\nd+j4ALhDxwfAnYKv8aV2K7F1g9RyNrkjym233aZyckmOZestcjdaOUUlBH1okH1/eaA4NT3UZBce\nWZ+WB1qFoA/7sfeQbVfu4hLCidNpZFseO3asyslpKvPnz1c5uRTUflfYgRkAcoiOD4A7dHwA3Cn4\nGp8l6xip+XC2xibnP91///0ZX2fZ3ZJXrVoV41TdQtb07HucrkPSUVhSbTe1LZXc9btz584Z75l6\nP7mcMgS9vVoIehfyVq1aqdzQoUNjvHjxYpWTtUP7N6Tm1dY1nvgAuEPHB8Cdgh/q2kf51OHK8mf3\n3r17q9ykSZNibA8ikuzP/vKglRD0kMAuS7O7U0jswILUcC91wPdVV10V45oc6CN3VX788cdVrmPH\njur66quvjvG1116rcnIppv1e2SG0dCbLNjzxAXCHjg+AO3R8ANwp+Bpfiq3/yTqJrIuEEEJJSUlW\n97Sno82bN09d9+/fP+NrZY0vVbMBUjsw21rxueeem9U97RSZyZMnx7hNmzYqJ09nCyGE999/P8aX\nXXaZysktq2QtMARd48unOjZPfADcoeMD4E5RD3XlrsYh6OHDpZdeWqv7lJeXq5zcGSMEPZ2gqqpK\n5eRqjdShLBarNXxIHaIt24udJpXtFJb169er69WrV8e4a9euKjd79mx1Lae3lJaWqlzLli1jbIfd\n8rPZNi+/j6zcAIA6RscHwB06PgDuFF2NL7UDi9zx1f5cn+09hw8frnJLlixR19u3b4+x3YFZvn91\nBzjDn9QJgZKt6cnaXc+ePVVO3mf//v0qJ2vOa9euVbmKigp1/fTTT8e4ffv2KienydjdilJt/kzi\niQ+AO3R8ANwpyKFu6md/ST5m2+uVK1eq3JAhQ2JsZ83L6Sx21vyhQ4fUtZzekto5BkhJHTZkp2l9\n/PHHMbbTtOSGonLnoBD08HXv3r0q16FDB3Xdt2/fk36WEELYuXNnjL/99luVk98X+308k0NfnvgA\nuEPHB8AdOj4A7hRkjS/1s7/M2ZrCgQMHYjxr1iyV27hxY4xtnUT+1L98+XKVs3WT2tbxsq1bwodU\nu7ZTseQOQa+++qrKjRw5Msbdu3dXuR49emT9eeT7b9myReVef/31GK9Zs0bl7Hcw0z1zjSc+AO7Q\n8QFwpyCHuimplRtymsqOHTtUbu7cuTH+7bffVK6ysjLGqdUYIehZ7OzAAqu2Uzjk6+yZzM2bN4/x\nhx9+qHJyJdG4ceNUrlu3bhk/l13lMX/+/Bh/8sknGd/Dfh/kKhM7FSw1DK5rPPEBcIeOD4A7dHwA\n3CmIGt/p2skkVV/ZvXt3jO3OFKnpM6ldXqjpwcp2BxbbPuS1XbIma2W2Bv3DDz/EeNmyZSona96H\nDx9WObsUU17b92jYsOGJf8B/ZJ37TNb0rPz5JACQI3R8ANwpiKFuTYaFtR1Cysfw1CO5HZ7Ys0oZ\nwiJbqbaSGgandv1JTeGyw9fU+9vhqx3eZvv++TS8lfLzUwFAHaLjA+AOHR8AdwqixpdSF1NbUrvf\npqYZAHVFtjPb5mQdLdU+7c7iMmdrc9VdZ3r/fK3pWYXxKQHgNKLjA+BOwQ91U1IrPnIxRQaorZq0\nudOxOqImryuGM6F54gPgDh0fAHfo+AC4U68Qx+cAcCp44gPgDh0fAHfo+AC4Q8cHwB06PgDu0PEB\ncIeOD4A7dHwA3KHjA+AOHR8Ad+j4ALhDxwfAHTo+AO7Q8QFwh44PgDt0fADcoeMD4A4dHwB36PgA\nuJPTc3XLysoK4oAPew6JPUc0RZ5PKs87zTeLFy/O/o9C0iWXXHLa2/WptMG6fr9cf7aaWL58eVYf\nhic+AO7Q8QFwh44PgDs5rfEVCluzkHU76/jx4+r62LFjWb0OSKmLupmtzckadHVtVb62UOt/Et9M\nAO7Q8QFwx9VQt379+jFODVFTGjVqpK4bNGigru2jvmTfE8glO5xt2LBhjO3UqyNHjmR9n5SaDItz\niSc+AO7Q8QFwh44PgDtFXeOztYizz/7/P9fWHpo3bx7jo0ePqlxVVVWMDx06pHK2biffQ9ZQbC7b\nmiJQE7KOHYJu54cPH1Y52c7t62zblTVAWw88HUszazvtpbZ1Qp74ALhDxwfAnaIb6qZ2R5GP7717\n91a56667LsZ9+vRRudatW8fYDm1/+eUXdT1z5swYL126VOVKSkpiLIe9lh2i5/MuL6gbqRUQdlgo\n24cdzsohbNu2bVVO/ttNmzapXOPGjdV1s2bNTvp+IdR+hVLqu5rt0Le2Q2Se+AC4Q8cHwB06PgDu\nFF2NT7JTRg4cOBBjW1No0aJFjDt37qxyssZna3M9e/ZU18OHD4/xU089pXJz5syJsa3hyKVv9nMX\nyq7OOH1qu9TrvPPOU9ePPPJIjC+//HKVk/W/nTt3qtzUqVPV9U8//RTjLVu2qJys/9nPLZe+pXY9\nqu20FKazAECW6PgAuFPUQ107LD148GCMFy1apHI//vhjjO2s9TFjxsT45ptvVrkBAwao6zZt2sT4\nvvvuUzl5XznsDUE/sjOdBanpLKmdhW644QaVGzRoUIxT005KS0vV9a233qqu5Xdn//79KldRURHj\nyspKlZNTuDp06KBysl3be9qVJJkwnQUAskTHB8AdOj4A7hRdjU/WDWyNT17bHWZlnULGIYTw5JNP\nxnjy5Mkqt2/fPnUtd3np0aOHysn64MKFCzPex9YY4U+qdmXrX7LNN23aVOWyne5ha2yWnCazd+9e\nldu8eXOMu3TponKyxminiS1evDjGX375pcrJnWPq4sAinvgAuEPHB8CdohvqSnYFhNxxwg6D5U/t\ndoj6xx9/xNgeNmTvkxpayEd2+9kY3iJbqRUQ69evV7lly5bF2O64smTJkhgvX75c5eS0rBBCWLdu\nXYztDjDy+2Knew0dOjTG9rsh7/P999+rXLYb9bJyAwCyRMcHwB06PgDuFHWNzy7Rkctu7IFC8tru\nVLF69eoYv/feeypna36y5rBx40aV++abb2JsaxhydxZbQ5FYzoZUfdguZysvL4+xXJYZQghbt26N\nsa1V25rzhg0bYjx48GCVu+CCC2Jsp6zIeqTcHSmEEFauXBlje4hXtrvTsGQNALJExwfAnaIe6tph\noJzxLoeWIeif+u1w4fnnn4/x6NGjVc4+asth6jvvvKNycjPH1A4bqV00GNr6JNuZXbnRsmXLGNuD\nsuQGu7/++qvK7dixI8Zys90QTlyBIa8nTZqkcn379o2xXdUhp8nYKStytYYtPcm/t7YHEaXwxAfA\nHTo+AO7Q8QFwp+BrfLYelu3By3Yaivy3N910k8pNmDAh4z0tORXm888/VzlZ/5O7uISQXnrDYUPF\nI9upGKn2YHNyRxY71UQuxZTTuULQU7PsFC65q0oIIdx5550x7t+/v8rJv2PFihUq9+KLL8Z427Zt\nKifr2nY53emYspLCEx8Ad+j4ALhTEEPd1GoF+xgsp4nYn/3lfexMdflz/vXXX598f8kOO+TwwX62\nVq1axTi1csNOdWF4W5yy3cnHspvoyvbRsWNHlZMllXHjxqnchRdeGOOlS5eq3LBhw9S1vK+devLV\nV1/FeMqUKSonp8y0a9dO5ezwNpd44gPgDh0fAHfo+AC4UxA1vlSNy9bDpFQdzd5T7hTx9ddfq1xZ\nWVmMbb3PHtIid7yw7yHrinY3ilQdEcWjtlMz5OtsW9m1a1eM//77b5WTNT773v369Ytxr169VM7W\nwOX37Oeff1a55557Lsa2/tipU6cY2+9DqlZf1/i2AXCHjg+AOwUx1LVSKxnkI7qdLiCnt9hZ7HL2\n+xtvvKFyd911V4xLS0tVTh5EZNnPJoe39qd8+W/tNJzUcB7FybZdORSU06JC0GcyP/PMMyr3xBNP\nxFiu4rD3tLsVWXIIPW3aNJXbvXt3jOVuMCGcOPUl0/vnGk98ANyh4wPgDh0fAHcKosaXWrJm62Ep\nslZm7ylrd7b+J3eusDU+Ow1A7o5hp8XIup6dapNaaofiZGtc2R6ObWu+csrKwoULVW7y5MkxfvTR\nR1Wubdu2MbbTV2x9Wu6eLA8iD0HvAJ06CPxM1vQsnvgAuEPHB8AdOj4A7uRtjU8eaGzrBnLekpx/\nF4JeImOXhcnaXWrekq21yK11bG3Qvn/Xrl1jbOskcnmbvU9qWyoUp2xrelZVVZW6Tn1X5s2bF2Nb\nY5N1PXvYt/yOhaAPI08tZ7M5Wa/Op3bNEx8Ad+j4ALiTN0NdO/STP5HbYalcslNRUaFycncUOewM\nQT9224NP5PDBvt/cuXNjPGLECJWTwwx7H7vjrFz2k9p9NjV9Bz6kduuxw0k5hLXL0iZOnBjjzp07\nZ3yPPXv2qNyaNWvUtczLaTAh6EO0bFut7XC+rvHEB8AdOj4A7tDxAXAnb2p8tm4h62NyW6gQQujW\nrVuMy8vLVe7ZZ5+Nsf35/uKLL46x3SlW1ubklJgQdN3E3tMuL5OnUZWUlKicrPHZv1fWQqjpFY/U\n9lLV/dtMr7P1P1ljGz58uMrdcsstMU5NQ5FL0kIIYebMmep6/fr1MbZTZuR97WejxgcAeYKOD4A7\neTPUtY/PzZo1i/GAAQNUTg4n7777bpWbP39+jOfMmaNyffr0iXGXLl1Ubt26dTG2Q4Irrrgixo0a\nNTr5H/Af+WgvhyAWw1mkpIbEtu3IXY7Hjx+vctW11/9ZtGiRurbTxOQOMHaVh/w8qaFtTYb9dY0n\nPgDu0PEBcIeOD4A7eVPjs9NLZH0sNYWkdevWKjd9+vQYP/TQQyond5wYOHCgyskpMldeeaXKDRky\nJMZ2OZuttzRp0iTGdsmaXPZDjc+HmtSxalvzkjVvu0N4ivzOLViwQOVsHU+2a1sDT52kJrEDMwCc\nQXR8ANzJm6GunfG9efPmGNudVOSjvX2dHPrOmDFD5eSGonYDUbnLinysDyG9aakdssqDieznTu24\nwdAXUk2mfsi2k2pjllytVFlZqXL2Wn5fiqGt8sQHwB06PgDu0PEBcCdvany2jiZ3MnnrrbdUTtbx\n5DSUEPRUF7s7stw51k6fkdepHZDt6+zhym+++WaMbZ2kJvUXFI5cL8Wyyztl+6zJgT5yF/Du3bur\nnNzJPAR9cFeqHefTlJUUvokA3KHjA+BO3gx1LfnIbGeVyykjo0aNUjm5A4sdlm7fvj3G9jCVTZs2\nxdj+XC9XfMh7hHDiGae1nVqAwlXb4V1tX2dXTshVFsuWLVO5srKyGNv2uGvXrhjbIbIdvstSlB1q\nF2I7L7xPDACniI4PgDt0fADcyZsaX01+hl+1alWMba1O1thsLcTWJjLlbM1CXtv6n52GI6fT1ORv\ngj/ZHi5k/61t17LObHckkkvNWrZsmfH9ZL0vhBOXbcp2bw/YKkQ88QFwh44PgDt5M9S1sv2J3A49\n5ZDATmdJ3d8OHzLd075fahpAocxix6mpi5UbqWGw3fhTrsCw5Ry5AkpOy7KqKwvl6/m4tcUTHwB3\n6PgAuEPHB8CdvK3x1XaX19NRXzmV3Seo6/mT6/9z+36pqSZyhyL7nZJ1vGKr4VWHJz4A7tDxAXAn\nb4e6KdlOGUnlOPgH+aYupkLJ4WyqXadWipzsOtNrc70pa23xxAfAHTo+AO7Q8QFwp563n7EBgCc+\nAO7Q8QFwh44PgDt0fADcoeMD4A4dHwB36PgAuEPHB8AdOj4A7tDxAXCHjg+AO3R8ANyh4wPgDh0f\nAHfo+AC4Q8cHwB06PgDu0PEBcIeOD4A7dHwA3KHjA+AOHR8Ad+j4ALjzfyLVzZk9YAH4AAAAAElF\nTkSuQmCC\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 31 ---------------\ndLoss: 0.27\ngLoss: 2.35\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f1384e6f128>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 32 ---------------\ndLoss: 0.27\ngLoss: 2.35\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f138433ab38>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nrj42TaeupQAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 33 ---------------\ndLoss: 0.26\ngLoss: 2.35\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f13847ce320>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 34 ---------------\ndLoss: 0.26\ngLoss: 2.35\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f1384565358>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4wLCBo\ndHRwOi8vbWF0cGxvdGxpYi5vcmcvpW3flQAAGMxJREFUeJzt3VmMlEXXwPFCZN8Z9l1ACGsAHXaB\niEQBNRIVjFciJMSYaFCICfFKA0REBSSa4AUaYuRCUDCsxpggyiqLyr4qIoM4su+L78X3pr5zDk7x\ndL/dPd1T/9/VeXKGfnrG6vKp07VU+ueffxwAxOSu8n4DAJBrdHwAokPHByA6dHwAokPHByA6dHwA\nokPHByA6dHwAokPHByA6d+fyZsXFxRlfJmJXnlSqVCnTt1Duukv/v+LWrVuJf1a6efNm4ntm4ney\nf6etW7dm9w8VkUGDBlW45U+hNpfPq72+//77RO2aJz4A0aHjAxAdOj4A0clpjS8bUqlFpFsrk68T\nquk5p+t6to4n75/KewnVVJK+TrZrn6hYQjXoUO26UBT+bwAAKaLjAxCdgh/qhqQ7vKtcubK6lo/9\nd/oq/8aNGz6uUqVKWq9jhxlVq1b18Z2G2kBZUvk83H132V2DbYNJXzefpsHwxAcgOnR8AKJDxwcg\nOjmt8eV6eVkq5Ff0sk7nnK532Pdsf1bW9a5du6Zy8rpWrVoqV61aNR/bGsqVK1d8nM9/Q+S3VNpO\n6GdD9b/QNBh7v/Ks+fHEByA6dHwAopPToW6uh2WpzDCXw0s57HTOuRo1avj44sWLwXvI4azNTZo0\nyccDBw4s8x47d+5UuQULFvj4/Pnz//4LIBqZ+hzJoaYdvtoyTZ06dXzcs2fPMn/2l19+UbnLly/7\n2H4e5O+R62EvT3wAokPHByA6dHwAohPVkjVZR7D1Brks7K+//lK5mjVrlvmaHTp0UNd9+vTxcf/+\n/VVu0KBBPrY1FfnemjRponJr1qzx8Z49e1QulZ2cUTGkMi0laa569eoqd+nSJXXdsWNHH48dO1bl\nTpw44ePDhw+X+TqpvM9s1/x44gMQHTo+ANGpcEPd0EagcteV69evq5x8JB8zZozKTZ482cd169ZV\nudAsdvu4HvpZ+ahvp9PIVR652HgV5S809LM52a7tNJSyfs45Pby1r3nmzBl1PWrUKB937dpV5ZK2\n61D7ZDoLAGQZHR+A6NDxAYhOhavxyaVnoZ2UO3XqpHLz5s3zcaNGjTJy/z///FPlGjZs6GNbF7l6\n9aqPd+zYoXK7d+9OdG9qehVHqB5m/zvLNtegQQOVKyoq8vHx48dVTtbD7W7hTz31lLoeNmyYj+Xy\nSvt+Tp8+rXJJa+BMZwGALKPjAxCdgh/q2o1A7Qx0qUePHj7+6KOPVM4Oi5MqKSlR10ePHvXxnDlz\nVE5OA7BTVlavXu1jOzw4e/asjyvCmaZInRwK2rYqh7dPPvmkysnpV7KNOadXAdmhZtOmTdW1HHra\nKTPr1q3zsdw01zm96onpLABQjuj4AESHjg9AdAq+xheqeTVr1kxdz58/38ep1PQuXLjg4ylTpqjc\n9u3b1fV9993n48aNG6ucXCa3ZcsWlTt06JCPW7ZsqXJy5xi71C7pkiAUNln3tW3g6aef9rFcWuac\nbrsnT55UObmbuN1ZfO/ever64MGDPrZLQb/++msf2yWdsgZv/11oqku28cQHIDp0fACiU5Dn6oaG\nt/LResaMGSonv1oP2bZtm7qWQ+RTp06p3N9//62uf/jhBx/LTUmd08MJ+9gvD3CR01ec00ObdDed\nRGGTbcAOEYcMGeJjeSiQc3qou3//fpWTbde2azssXrp0qY/t589OKZPke7X/rjw30eWJD0B06PgA\nRIeOD0B0Cv5AcVvv6N69u4+7dOmS+HVk/fGtt95SubZt2/pYHvzj3O07VbRq1crHcudk5/SuK/Z9\nyxqOnVpgl7ehYkjlMCxZR3vwwQdVTk6bsnX0zZs3+9ge9v3bb7/52O7qYqd7yZ1d7r//fpWTS0Ht\nNK3S0lIfy51iyhtPfACiQ8cHIDoFuXJDbrxovxKfMGFCWq8pD1eRO6w459z58+d93KJFi+D9mjdv\n7uMVK1aonDyv1z72y6Fv6MzdEFZuFJZUdiuRZRN7rq0cFtvNRletWuVjO/VK3s+2R7s6RK6CkuUk\n5/RqEXvu8zvvvONj+TlyTu+kZD/H2d65hSc+ANGh4wMQHTo+ANEpyCVr8qt2uwOLPew4KbnU58sv\nv1S5+vXr+9ju8Bz6HUaOHKmup0+f7uO1a9eW+Tq2xidrmiHU9Aqb/O93+fJllevfv7+PO3ToUOZr\nLFu2TF3LKSvdunVTOVnLPnfunMp17NhRXQ8cONDHcvqKc/rz0aZNG5WTn6vXX39d5UJL1jhsCAAy\njI4PQHQKcuWGfAy2Z+CmexiPHF7KKSn/C7mBqHP6Ud8OZ5csWeJju+Ij6VAXhSWVs2SfeOIJH9vV\nQvLfffrppyr3008/+fiRRx5ROXmWs1yd5Nztw2K5OW7oc2w/f3379vVxu3btVE6uJAkdEpYNPPEB\niA4dH4Do0PEBiE65LlmTtYlU6gbyZ+XX9c7pJTN2F4nynu5RpUoVH0+cOFHl5A63tjZoD3BGxWDb\no6zlyrbiXHgKi3ydMWPGqJzcnUXuDuScc/Xq1fOxXeq2ceNGdS2n1xw7dkzlZs2a5ePatWurnPw9\n7FK3I0eO+NjWsZnOAgAZRscHIDp0fACiU641vqQ1Nzv+lzU/u9RG7p4sl/k4p5fayGU2zoUPbJb1\nD3tSld0NV85/svUOyR42Ln8ne3+5RM+eaFXedUukL1THsnP1knr55ZfVdcOGDX1sT06T9Tf7ObI1\nP9kmv/nmG5UrKSnxsV3qJn9He8phebZdnvgARIeOD0B0Cn4HZuvgwYM+3rlzp8rJaSF2Fwk5LcZO\nJ5HLdeyUgLlz56rrfv36+djulCHZJWt169b1sTwE2jk91GVoW9hCOwvLcoedwnTgwAEfh5ZU2oOp\nnn32WR/boa58zQ0bNqic3a1Z7p586dIllQu1SfmzmzZtUjl5qJb9zGUbT3wAokPHByA6dHwAolOQ\nNb4QuaWTnbIit76xO9zKuqHd6kou0bFbRtl7yBpfKuQ0ALmVkHPU9SqSpMs0bfv84osvfNylSxeV\nk1NW7FSo06dP+/jEiRMqt3fvXh+fOnVK5Ww7l/eYNGmSysmpN7b+99VXX/nYTgWT9chsL1GzeOID\nEB06PgDRKfihbmjnFvl1uf1Zebi3c3qoaaeayJ0q7E61ffr0UdeDBg1K8rZv06BBg399n87dvloD\nhSs0nUVe2x2J5W7Fb7/9tsqNGzfOx3aIKncrsjsZyWlTDz30kMq1aNFCXcv2aYfo8rP03XffqdzC\nhQtdWbJ9aHgIT3wAokPHByA6dHwAolPwNT5L1gpsvaNVq1Y+tjUMWaeQX90759z48eN9PGLECJX7\n4IMP1PWAAQNSfMf/Ry5LszVGOUWBqS2FLTSdReZsnffKlSs+tofRy/YyatQolZO7BfXs2VPl5DI0\nW2OTSyid09NrZL3ROee2bt3q4127dpV5D9uuy/P0QJ74AESHjg9AdAp+qGsfl2/evOljO9SVm4bK\nYa9zzv38888+Xrx4scp17tzZxytXrlQ5ufGpc8l3mbAz3OVOMnJY45weBsvfzzmGvhVJ6L+lHCba\nTUq3b9/uY7vr0OjRo31sNwKVO8DYqS52J5Xdu3f72K7AKC0t9bGdhiPftx1OM50FAHKIjg9AdOj4\nAESn4Gt8lqyBya/SndP1t06dOqmcPPxn6NChKldUVOTjJk2aqFy6h8LYWqHdHUOSvxM1vTjYmpdc\ntminhcipWD/++KPKFRcX+9i21dWrV/t4/fr1Kmd3cpG1dFvHltehWl2u63ghPPEBiA4dH4DoVLih\nbujAFjnj3X7t36tXLx+HzsP9X8iDkBYsWKBycrhgd2MpzxnuyJ5Upncknepy9OhRlVu0aJGP7WoQ\nOYXLHnBlh9OhYWq677s88cQHIDp0fACiQ8cHIDoFX+OTy7ks+/W93Dni448/VrkpU6b4WO7G7Nzt\n9Y6kZE3POeemTp3qY7s7tKzjUdOLU6iOJtuErdXJ+rBd7iint4R28rZTVEJ1Znv/kHyawiLxxAcg\nOnR8AKKT06Fupr6+l+xuJfIx3ObkkHXfvn0q98wzz/jY7jBRpUoVH9sdLuy5unLDxnPnzpWZ40Ah\nhIQ2KU2lFCJ/1paF5D3sa9r2Ka8rQimGJz4A0aHjAxAdOj4A0cmb6SyZWtoSmhYSOtBHLlOTh/s4\np3dLtgeRl5SUqGtZC7H3kNfU9BCSyjSQUM0t9LmS/+5On798nZaSLp74AESHjg9AdHI61M31Tg32\n63s5hL169Wri15HTW+x0FjvMkNd2yCxn1ae7GgRIRdIhakUbyt4JT3wAokPHByA6dHwAolMptrE9\nAPDEByA6dHwAokPHByA6dHwAokPHByA6dHwAokPHByA6dHwAokPHByA6dHwAokPHByA6dHwAokPH\nByA6dHwAokPHByA6dHwAokPHByA6dHwAokPHByA6OT3ctbi4OG8P+JBnj+T6/N/ysGXLlor/S+ZI\nUVGRateZaD/2LJxst0n7+vb+mfh8ZON3sq9ZWlqa6EV54gMQHTo+ANGh4wMQnZzW+PJZpmooSWsh\nua7hIHty/d8u1HZSaVepnKktX+dO9cCk908qG58VnvgARIeOD0B0GOr+V6amsyT9twxtYSVtg+nm\nrLvuysxzT6aG0+m8frp44gMQHTo+ANGh4wMQHWp8/0XNDfkklSkc2ZjOYnOyHpjKZyX03kI1zaS1\nwXQ/tzzxAYgOHR+A6EQ71LVf5ScdSty4cSPxPezjepUqVXx869Ytlbt582ai94I4pDtlpXLlyupa\ntrNU2mMq01Dkv7WfK/l+QvewuWzjiQ9AdOj4AESHjg9AdKKt8dmaQtLlOw0aNFDXzZs3V9dnz571\n8e+//65yofogdT2kPTVDtN3Lly+rXNWqVX1s63ZXrlzxcbVq1VRO1v/se7t27ZrKdenSxcetW7dW\nuX379vn48OHDZd4j3eks6eKJD0B06PgARKdCD3VDU1bso7X8WTsMvvvu//8zvfrqqyonH/Odc27V\nqlU+Xrx4scrJx/erV6+WmZNTWwDnwsNgWUKpUaOGyj388MM+7tChg8rJtlq3bl2VGzBggLrevXu3\njxs3bqxyM2fOLPP+K1as8PGECRNUTrbzdHeKSXdIzBMfgOjQ8QGIDh0fgOhU6BqfrYuE6iTyq3VZ\n03POuYkTJ/p4+PDhKmdrEz169PCxrfHJWky2v65HPGrXru3jqVOnqtxzzz3nY7ucbciQIT7euHGj\nytnpLb179/bxqFGjVK5evXplvrehQ4f6uHr16ionp97Yz1EmdqMO4YkPQHTo+ABEp+CHuvYRObTL\ngxzChlZRXLx4UV2PHDnyX1/j3+63YcMGH1+4cEHl5D3tv7PDACk01QblL9dnJNv7tWnTxsejR49W\nuZo1a/rYtvnr16/7+NixYypXUlKirgcPHuzjzp07p/Ve7VDbXkvZ/hvyxAcgOnR8AKJDxwcgOgVf\n47NkPczuMBFa2nPp0iUfN2vWTOXq1KlT5v3kDhfO6SksdqcMeX87BaBWrVo+Pn/+vMpR18tvud5Z\nJ7S8S+4O5JxzZ86c8fG6detU7sMPP/Rx27ZtVU5OQ3HOuXHjxvnYfnZC9uzZ42O7q0vSmns28MQH\nIDp0fACiU/BD3dBOKvZrf7kpY8iMGTPUdWhosXbtWnUtNyqVj/n2vU6bNk3l5FB3+fLlKieHvmxY\nmn9yMZ1FvqZt83KDzyVLlqicLKnMnTtX5eTuKMOGDVO5xx9/XF3b8k9Z5BQZ55ybPXu2j+37ltNZ\n2IgUALKMjg9AdOj4AESn4Gt8ofqbrTfIZWH2ICC5i0XXrl3LfE07fWXevHnqun379j4+ceKEyr30\n0ks+Hjt2rMrJOs3q1atVjrpefst2Tc+yyyblNJGVK1eqXMOGDX3cqFEjlZPX7dq1Uzk7vSUpOUXG\nOeeWLVvmY7tzs5zCkvMpQTm9GwDkATo+ANEp+KFu6HxcOyQ4efKkj++55x6Ve+211xLd74033lDX\n9mAgOZ3FPvYPHDjQx/br+lOnTvnYzr5ndxZIdkWSbBPHjx9XuY4dO/p4/PjxKldUVOTjfv36qVwq\nh/8cPHjQx/bz0aJFCx/b1RmZGN5y2BAAJETHByA6dHwAolOQNb5Q/UGO+e3PdevWzceLFi1SuVC9\nQdbx5AHJzt1+wPjp06d93KdPH5WT76e0tFTl5s+f72M7DcfWKlHxJW2Pzun2YWvAcsla3759VU7W\n31LZccXuLP7YY4/52L5vuSzN7s4SWoaXFIcNAUBCdHwAopM3Y6hUdriQj8Whf1e3bl2Ve/fdd31s\npwSEyF0t5OEtzjm3bds2dd20aVMf2yHq1atXffzmm2+qnNzJpX79+irHFJY4hNq8LJPYNi9zcuNR\n5/SuP3aHFTm8vdOQUQ6vly5dqnJyNVPo7FwrdHZu0mkqTGcBgITo+ABEh44PQHTKtcYXGuPLuoVd\n6iLrc7Ju5pyuMUyaNEnlZP0t9F7ef/99lZs+fbqP5RQA55zbsWOHup45c6aP7e909OhRH69fv17l\n5PIhW7egxlcxhepqNhea+iGnjNiDsXr37u3j0JSVO7W5I0eO+NjuACPbtVyy6ZyuidvPauj+oVwm\nlrrxxAcgOnR8AKJDxwcgOnkzjy/EjullHcHOeZPL0uxWO3Iukj20+5VXXvHxwoULVa5z584+7t69\nu8rZ06h69erlY1sn+fzzz31s6x2y/mKXrKFwZaM+ZV9D1sDtTsqyfcpaoGXbnG2fcj7evffeq3Jy\nKZzcSdy5cH066Ry8VGqhSfHEByA6dHwAopPToW4qX1nL6Sx2t+QXX3zRx3Jo65xztWvX9rF9DN61\na5ePJ0+erHJyF9nBgwernFySY19T7kzhnB6y2mk4W7Zs+df36ZweamRjp1qUj9B/u1CbD/1s1apV\nVU4OQ59//nmVs6Wgstih7qVLl8q8Li4uVjk5LP71119VTn52QkPtkFC5gCVrAJAQHR+A6NDxAYhO\n3kxnseN/Wcd49NFHVU6eVhaqG9jxv9yip1WrViona3MtW7ZUObmdzwsvvKBytlYn2ZqNnIbzxx9/\nqJz82t/+TixZq5hS2YpJtiXbrmQdb9y4cYnvL9vVrFmzVM7W6uTJf3YKl93+TZJTyFI5uU1iOgsA\nZAAdH4Do5HSoG3q0tweoyK/B7c6xSb8Wt/eTQ1g7JJCP4R06dFC51q1b+9juwBxipwTYw57Luj9D\n28KSjdUZlnxN266aNGni46TTV5xz7uTJkz6eM2eOyg0bNkxdy6GubZ/yM2F/d7kLebq7LIcwnQUA\nEqLjAxAdOj4A0SnX6SyyrmdPJJPLtuxOKumStYjhw4ernLy/fS+p1GxkzcEePi4PEbenvNllaohP\n0qVYtsb2wAMP+DiVKSN79+71sd11yO6kLA8DtyepyeWe9tBwWY/Pp9o1T3wAokPHByA65TrUDc1G\nl7Zv366u5Y4odliaVOjglVTYIYl8r7Nnzy7zZ0ObjbIbS5xSGd5KduiZVNu2bX3cvn17lTtw4IC6\nlrsg2YOy1qxZk+h+uZj2kxRPfACiQ8cHIDp0fACiU641vtAhybIe8O2336rcoEGDfDxixAiVS3cH\nCHk/+17kDrMXLlxQua1bt6rrTz75xMe2/hhaoofCle0las7ptmOnjMi6sm27oc+D3Nl82rRpKrd6\n9Wp1vXz5ch/v379f5eRnwrZ5+X7yqXbNEx+A6NDxAYhO3gx1LTnjWx6m4pxz7733no9LSkpUbuTI\nkT62s8/lcEGuonDOuc2bN/t406ZNKrdx40Yfy10qnLv94Be5AsMOM+TwNp8e+5F/QgcRVatWTeXk\nCox9+/apXJcuXRLdw36O1q1bp67l8FbunOScXoVkh9rZbudsRAoACdHxAYgOHR+A6FTKxC6oSRUX\nF6d1M1srk3UEW2OT1/Zr/4sXL/q4Tp06Kid/1v47eUiRnYaSyq4q8m9d3jW+LVu2UGTMkEaNGmX8\nQ2TbvGw7tsYn68724J9Ro0b5uH///ip36NAhH3/22WcqZ6dtyZp7PrV523+VlpYmuglPfACiQ8cH\nIDoFOdSVj8x26CmHwakMkSX7db18zC/vIWqmMNTNnKKiItWuQxuKJm0/9udCrylXS9gyjSRLNs7p\ndm7bvP3shA74ysRnIpW/U6jPYqgLAGWg4wMQHTo+ANEp1yVrSaVySEloNwpZCwl9JW/rf7KOmE+7\nyKLwhOpTSQ8bskLLJOW1reNJoTZv31sqQtNZQr9j0mkwLFkDgITo+ABEpyCGupkihwT2XFv5yGwP\nAmI4i1RkY4pY0iGjvbcsE4VKRnYD0dCGolbSz0cqf5ekw9t0/9Y88QGIDh0fgOjQ8QGITk6XrAFA\nPuCJD0B06PgARIeOD0B06PgARIeOD0B06PgARIeOD0B06PgARIeOD0B06PgARIeOD0B06PgARIeO\nD0B06PgARIeOD0B06PgARIeOD0B06PgARIeOD0B06PgARIeOD0B06PgARIeOD0B0/gN4IwOaN9wa\nYwAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 35 ---------------\ndLoss: 0.26\ngLoss: 2.37\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f1384971a20>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 36 ---------------\ndLoss: 0.26\ngLoss: 2.35\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f13842cf908>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAESHjg9AdOj4AESHjg9AdP4P2oMxxXDuozEAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 37 ---------------\ndLoss: 0.26\ngLoss: 2.38\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f1384415c88>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nfADC+T/7JdJb7VWd5gAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 38 ---------------\ndLoss: 0.26\ngLoss: 2.37\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f13a0baafd0>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nDgMfgHAY+ACEw8AHIBwGPgDhMPABCOe/Rjk0H00iFYkAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 39 ---------------\ndLoss: 0.26\ngLoss: 2.37\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f138495d5c0>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 40 ---------------\ndLoss: 0.26\ngLoss: 2.38\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f13848f3400>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 41 ---------------\ndLoss: 0.26\ngLoss: 2.40\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f13844e4cc0>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nfADcoeED4M7/AbU4zRv9zqP3AAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 42 ---------------\ndLoss: 0.26\ngLoss: 2.38\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f1384251a20>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 43 ---------------\ndLoss: 0.26\ngLoss: 2.40\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f13845fdc88>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYII=\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 44 ---------------\ndLoss: 0.26\ngLoss: 2.39\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f13632dcdd8>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSUVORK5CYII=\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 45 ---------------\ndLoss: 0.26\ngLoss: 2.39\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f1363181630>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nBwDJgeEDgOTA8AFAcmD4ACA5/gcMzyEvbb/4OwAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 46 ---------------\ndLoss: 0.26\ngLoss: 2.41\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f13847be080>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4wLCBo\ndHRwOi8vbWF0cGxvdGxpYi5vcmcvpW3flQAAFv9JREFUeJzt3WmMVEXXwPFChGHfBgFZFEUEWQSJ\no1EUwQQNEdAgoglR0BiicQsuqCQmopFEMCaSuJAYo99UIhglgoIkYoICiogYZJFhmWEfgRn2zedb\nvacOdnFvv90z3X3+v0/n5kz3bXxu11N1upZG//77rwMASy5q6A8AAPWNhg+AOTR8AMyh4QNgDg0f\nAHNo+ACYQ8MHwBwaPgDm0PABMOfi+rxZt27d6nWZiF6V0qhRo8R/m/R1xaq6urr0/lENpKKiInh4\nLrro//oT586dc9nkspXt/S70WWS+cePGGe8f+87FvmNpPlvM6tWrEz3X9PgAmEPDB8AcGj4A5tRr\nja++panpJf3bC9X7ktY0st0VpxTrjaUmTU0q3/eTuVjdLs17nj17NrjOth4Xk+3nTooeHwBzaPgA\nmFPSQ918DWeTvmcasSEyw9vSkXSYlmaqSy6Gmvr99bV8Jps0aZLxfc6cORNcy8+T7WfLR+mAHh8A\nc2j4AJhDwwfAnJKu8aURq6PJ3IXqbbF6RNKpLtT0ikuupltkOy0lRi4v08+cfB/9nrpWJ99H5zL9\n3YX+Nh/TYJKixwfAHBo+AOaU9FBXDxmTrqTQr5Pd97KysiB38cXhf8ITJ074+Pjx4xnvp4cW+Zhq\ng4YRG4rmY0gnnwk91JTPTmyKzOnTpzO+p3POTZ482cf33XdfkGvVqpWP9+zZE+Rmzpzp4zVr1vzn\n528I9PgAmEPDB8AcGj4A5pR0jU+LTSeR9Q5dJ5G1keuvvz7IDR48OLhesWKFj1euXBnkZD1Q73Ah\nP0+a+h8aXq52WY7V/2Lvme2UFXl96tSpIKenofTv39/H5eXlGT/nZZddFlzfcsstPl61alWQ0/Xx\nTJ9NY3cWAMgCDR8Ac0puqJt0g089fGzWrJmPa2trg9yoUaN8PHv27CAnf8p3zrlu3br5eNmyZUGu\nffv2Ge8vhxZpNillGFxccjJMy/JQIl3CkVNYevToEeR+/PHH4PrZZ5/1sS7hxD7PyZMnfayHtrHh\ne75XctDjA2AODR8Ac2j4AJhTcjW+pDup6LrE0aNHfXzHHXcEOVnX69SpU/T+w4cP93GHDh2CXF1d\nnY/btGkT5Op7dwrkT9JpKdm+Z9LdmC+kadOmPtbPqp6mJWvXse+V/B4559zy5csz/m3S+jSHDQFA\nDtDwATCn5Ia6ciqI/vleXsuf2Z1zbsqUKT6eOnVqkGvbtm3i+8uh8MsvvxzkXnnllYz3j82+R+nI\ndnVG7D3k62Jn3sY2Ba2srAyuBw0aFFy/9NJLPo4NUZcuXRpcb9q0ycdyaK0/T7bD2WxLB/T4AJhD\nwwfAHBo+AOYUfY0vVm/QOyDL+tu7774b5EaOHOljfWCyrLnpOom+v1yWo6fFfPLJJz7evn17xs/N\ngeKlK9uaVNL30HVt+ezIZZnOhXW0zZs3B7mJEycG1126dMl4z2PHjvl4zpw5QU7WHPVzne3h6rlA\njw+AOTR8AMwp+qFubOqH/vl87ty5Ph46dGiQi21SWlNT4+OvvvoqyI0YMSK4lrtc6NnwN9xwg4/1\nUJfhLGKSbm6qn1051IwdjKVXajzwwAOJ7/H999/7WJeX5NA7NtVGS7pSJdthMD0+AObQ8AEwh4YP\ngDklV+OTU1Gee+65ICfrerGa2pYtW4LrF1980cfffvttkHvjjTeC68cff9zHuv4gd67Q94/VGKn/\nFZdcLD2LLeGK5XQdT9a59XMlp7foqVdlZWUZ77Fu3bogN336dB+3bNkyyOm6XlIcNgQAOUbDB8Cc\noh/q6q59z549fXz//fcHudiQUXbJn3/++SAnN1Ns3rx5kNOHDcnzSaurq4Pcr7/+6mM91UafayrJ\nIQrD3sKX7c4i2U7hkN8B/TpZ+tHn4cqhrtwk17lwCpdz4XMnh7bOObdr1y4f9+vXL8jJ71UuVq3k\nSuF8EgCoJzR8AMyh4QNgTtHX+DT5c3qaetju3bt9rH/K79Onj4/3798f5OQhLM6F9bidO3cGuX37\n9vlY1/gkvcMGOzIXtnwchpNmGozcMUjXvPWzLMlnXi+91IdhyXvoOp78TqQ5NLwha370+ACYQ8MH\nwJyiH+rqmeFyePnxxx8HuTFjxvhYH/azbNkyH+uzc+VP/d27dw9yffv2Da7l9AF9xqj82V/u4pKG\nHr4zDC48+dhsVA4TYxvlauvXr/dxVVVVkHvsscd8fNdddwU5PU1L0tO95OfRhw3Jso0eBst/U30P\ng+nxATCHhg+AOTR8AMwp+hqfdvjwYR/PmjUryL399ts+7ty5c5CTNQ29fKy2ttbHM2fODHL6EBZZ\nm9C1mNatW2f83ElrddT0SkeaKSuSnu4kD7zX01Lk9C5dj5Y7gutdVWJ0DXzKlCk+1tO9Nm7c6GO5\n4/OF5OOAIYkeHwBzaPgAmEPDB8Ccoq/xxQ4p1ltIyZw8BFnnDh06FOTk8rIBAwYEOV3Hk0t79OHj\n8m/TnDhFXa94palVxZ4BOX9TP9dy+7UJEyYEOblkLfYc6bq2fj5Pnz7tY73cUt5DLu/Uf7t69eog\nJ2uV2R42nu18P3p8AMyh4QNgTtEPdfUSLjm81N1g+bf6p3X5Or2c7cCBAz4+ePBgkNNdcjlk2LNn\nT8Z76NfFuv2wIekUFjnsdC4sv+hhsKSHr1u3bvXx+++/H+TkIeHOhUPWp59+OsgNGjTIx+PHjw9y\ncrmn/u5s27Yt42eV8rH7DT0+AObQ8AEwh4YPgDlFWeOL1cBitTJZ44vtzixPn3LOuUsvvdTHuk6h\npwHIraj+/PPPICfrL2wvVTpytaVSbLdi+bzoqVjbt2/38ZAhQzK+TteulyxZ8p+xc+dPxZLvo08P\nHDt2rI/1zs3y+6CXd27ZssXH9b0bMz0+AObQ8AEwpyiHurLbnWaIGDuwWeb0AS2yi65z+v5y1ccv\nv/yS+LOheOViaKvpHVgkvZPKwoULfax3YJHP7t69ezPeQ6/G0PcfPXq0j5955pkgF5tCI3dd1iWk\n2NA+3+jxATCHhg+AOTR8AMwpyhpfTKzmF5vCIqel6B1XevXq5ePy8vIgp5cPVVZW+ljvRhu7v/zc\naQ5CR2HLdrmVfo7lcjNdf5PTph566KEgJ3dZHjhwYJDbsWNHxtfpU9YmTpzoY12ri5E7otfU1AS5\nhnzO6fEBMIeGD4A5RT/UTTp81H8bm5muDw2fNGmSj/VB4HrTUjmF5fjx40EuNkUBxSu2ciMfqzpi\nm9jq+8lh8KpVq4LcTTfd5ONhw4YFud69ewfXSYe3+v5yRciGDRuCnP53SEn/O2U7DYYeHwBzaPgA\nmEPDB8Ccoq/xxej6n6wb6JysacyYMSPIyR1mdU1B7jDhXLhzbazGGMuhuCVdGpltvS821UWTu6Xo\n3Vlqa2t9LA/+di585tNYt25dcP3FF1/4WO96HqtN5uK/Uww9PgDm0PABMKekh7qanMKid5R45JFH\nfCxnuzsXruSQwwPnnPvmm2+Cazn01StAJIa2NuRq15GkOxLJ3VCcC6dbtWvXLsjJ6S2ff/55kBsx\nYkRw3alTJx/rofVvv/3m4zfffDPIVVVV+TgvQ1bO1QWAZGj4AJhDwwfAHFM1Plkn0bUXWYuQsXPh\nrsv6oOXFixcH17FdNGBD0p2Fs13qpuvD8jnTNT45hUTvJNSxY0cf6yWc06ZNC67lIUZ//fVXkJNT\nWI4cORLk5M7Ouap35qJWSI8PgDk0fADMaVSf57l269atQQ+PjQ11ZfdZT0ORQwQ9XNDD2aRnozb0\nyo3q6mrm0+RIRUVF3p/r2FBXij1XehqKfHb1ebh6ZyF5rb8fsVUWegidSZoNW2ND3ZUrVyZ6runx\nATCHhg+AOTR8AMwp+uksaQ4Xkn+ra3MyJw8e0vTrYveIYckashV7xmK1sdizW1dXF72nrOslrdtp\nsTpemppeLnZuoccHwBwaPgDmFP1QNyb2036aWeTyfWJTVP7rGpCSrurQsj5UJ3JIkaRXfOjvTrbT\n3pIORXM1nSUpenwAzKHhA2AODR8Ac+p1yRoAFAJ6fADMoeEDYA4NHwBzaPgAmEPDB8AcGj4A5tDw\nATCHhg+AOTR8AMyh4QNgDg0fAHNo+ACYQ8MHwBwaPgDm0PABMIeGD4A5NHwAzKHhA2AODR8Ac+r1\nXN3y8vKCOeAjzVkjac7Kle8be13szN/6UFNTwwHAOTJu3LiCea6tmz9/fqLnmh4fAHNo+ACYQ8MH\nwJx6rfEVknzV1OT76nskrSs2dP0PSCNpXbuQ0OMDYA4NHwBzSnqom2bIGOuup5n6kvR1+ZgiA+Sq\nTJKP9ymkZ5ceHwBzaPgAmEPDB8CckqvxJa0ppKk3NG7cOGPu3LlzGXMXXRT+/0qs5hd7n9h7FFLd\nBPWjPp6BNO8p/zbbenh9o8cHwBwaPgDmlNxQNyk9tJTd9VhOD18vvjj8T3j69GkfHz9+PMjJ1+qh\nRCwHxMSGl7FcrIQTk7Qs41zhPsv0+ACYQ8MHwBwaPgDmFH2NL/bTfrb1DV23k06dOpXxfs45d+21\n1/p47NixGV/76aefBrm///7bx02bNg1yhbrsB4UhVp+WteMmTZoEOflc6edafwfk++rvlXzfM2fO\nJP3YDYoeHwBzaPgAmFP0Q11Ndu3Pnj2bOCe7+i1btgxybdq08bHuym/bti24vvzyy308ZcqUIFdW\nVubja665Jsg9+OCDPi7kQ4pQeOQzoYez8jnfu3dvkJPP6pgxY4LcddddF1yXl5f/53s659ymTZt8\nPG/evCC3Z88eH6fZ9SjfzzU9PgDm0PABMIeGD4A5RV/ji9UNZG3OOeeuvPJKHw8cODDIHT582Mcr\nV64McnV1dT4+ePBgkNP1wKlTp/q4VatWGT/3rbfemjFXLDtcoGHEljvKJZPOOde8eXMff/DBB0Gu\nd+/eWd1T379r164+lt8x55ybO3eujzdu3JjxPfUzn+8pXPT4AJhDwwfAnKIf6uqZ6h07dvTx66+/\nHuRGjx7tYz1ElTupfPjhh0Fuy5YtPt6xY0eQGzp0aHDdr1+/JB/7vGGwXEmiu/byWk8lgA1Jh36t\nW7cOrufMmePj9u3bZ3ydnqa1du3a4LqmpsbHw4cPD3JymlbPnj2D3BNPPOHjJ598MsjFdiTKd7mH\nHh8Ac2j4AJhDwwfAnKKo8cXG//KndOece/XVV3187733Bjm9e7LUokULHw8YMCDIHThwwMdy6Y5z\nzlVUVATXsZ1dpDS7yjC9xZ40SxNlfXjy5MlBLlbXk1OzXnjhhSD3+++/B9eyBv7aa68FuXHjxmW8\nR7du3XzcuXPnICeX0MW+m/lAjw+AOTR8AMwpiqGuJoeTeqg5atQoH6fpPsuhRVVVVZD77rvvfKyH\nwXJmfJp7ytUgzqXbkQW26akncgXGkCFDgpx8dnbv3h3kRo4c6WM5JHXu/CkrchqV3ig3Rj7XN954\nY5BbuHBhotflAz0+AObQ8AEwh4YPgDlFWeOTy9R0TU3vQJuU/Lm+srIyyP3xxx8+1rtPtG3bNqv7\n6XqLnJKgd9hgl2V7Yv+by6lXzjk3YcIEHzdr1izIbd682cd6ysptt93mY72EUu6crO+pp3QldezY\nscR/y+4sAJBjNHwAzKnXoW6a1Qqx7q38OV8OQ51zbufOnT6+6qqrMr6HPkf0yy+/9PEPP/wQ5OT7\n3HzzzUFOz0aPkVMCfvrpp4y52L+dYS8efvjh4Lp///4+PnToUJCbNGmSj9u1axfkunfv7uMNGzZE\n7ymfc3m/C5ElpBUrVgQ5WbKK7UiUD/T4AJhDwwfAHBo+AObUa40v29qV3mVZ/u3WrVuD3LRp03w8\na9asICd/6l+/fn2Qk8tn9HSB6dOn+3jw4MFBLs10ltraWh/resfJkyd9nGZJEEqTfuZlfS62A7J+\ndn7++WcfX3311RnfU9cG9a4u8sBxvcuzpGvny5cv97F8/vVnre9lmfT4AJhDwwfAnIKZzhKTZueS\nRYsW+Xj16tVBrkuXLj6+5JJLgpzcneLRRx8NcnLHC31Wb5odYPbv3+/jffv2BbnYuaXszmKPfq76\n9Onj41gppEOHDsG1XLkhp5Y4F5Zp9DOmV3Lo516SZZoFCxYEucWLF/tYr6rK9+qMGHp8AMyh4QNg\nDg0fAHMKZjpLtu+jayGyNqF3g5A7Ttx9991B7qmnnvKxrmdk+7n1LiufffaZj2Xtxbmw/sGyNBvS\nLOGUyzTT1Mrlcks9RUZe6/fU3yt5rQ+1X7JkiY/l0k/nwvpfIT3X9PgAmEPDB8AcGj4A5hTFDsyx\neWz6xCk5x0kf7i2X6Nxzzz1BLtudlGUNwznnTpw44WN5YLJzzs2ePdvHut4hP7euxaA0xeZr6pzc\nNkov07ziiiv+8z2cC59HXfOWW7jpOXYDBw7M+Fn1srT58+dnzBVSXU+ixwfAHBo+AOYUxVA31l3W\nP7vLn9r1jhNymoo+lCVGvqceLtTU1ATXcgrLpk2bgpwcFrds2TLIycOGGOraFJumdeTIER/rXYd6\n9OjhY/08bty40cd6OLt27Vofjx8/Psi99dZbGT/nmjVrgmu5/FJ/bl1uKhT0+ACYQ8MHwBwaPgDm\nFOYA/P9B1hj00jN5qpSuPci6mp6iIndrlrUW587/+V5ub6UPDddTbyS9vA226WVhsgasp0nJpZj6\neZTTpPSULfmsyh2WnTu/li2n07z33ntBTn7n9JZZhVqvpscHwBwaPgDmFOVQNzbDXXat9dBSDgO2\nbdsW5GR3Xe424VzYzdeHKVdUVATXXbt29bEeasspNIU6ox2FSQ519bQU+ew2b9484+t0OWXs2LE+\n1is19MFAH330kY/1MFjuiCRXihQyenwAzKHhA2AODR8Ac4qyxhfbqVbWNPSyNPlzvj5FSi71qaqq\nCnLyAGX9OrlcyLnw53z5WZwLd4c5evRokJN1Gup/SFO7lnT9T56s1rFjxyA3btw4H+tnddmyZcG1\n3BFGHzYua+exnZQK6bmmxwfAHBo+AOYU5VBX0l1rea0PUL7zzjt93Ldv3yAnV3LEDk/WBzbr3Sjk\nLPp58+YFOTkkSHMQOSDpZyd2aJAcFg8ZMiTIde7c2cf//PNPkPv666+D67KyMh/rVSXy/oU0nI3h\n2wfAHBo+AObQ8AEwp+hrfPpneFl/0DtDDBs2zMd6WorUq1ev4DpWN9y1a1dw/c477/h46dKlGe8B\nZCt2+Ld+5mXtOnaAkD7gXu/kLKdixabTUOMDgAJFwwfAnIIZ6uruey66zHKnFOec6927d1bvIz9L\ndXV1kJsxY0ZwLXd2iU1Z0VMCgKTSHL4lVy/pZ04exlVZWRnk5GqlC92zWIa3Ej0+AObQ8AEwh4YP\ngDkFU+PLlq4vyGud279/v49j01k0ecDQggULgtyiRYuCazmdQNdbYjtXAPkgl0nqncVXrVrlY7nL\nuHPnf3fkFJZirOlp9PgAmEPDB8CcghnqZtt91sNHOVN93759Qe7222/3cYsWLYJcXV2dj/XZpPKc\nXT0zXn/u2Cz6UhgioH5ku6Gnfubk86hXZ8R2ddH3iB3wVYzo8QEwh4YPgDk0fADMKZgaX7Z0TUPW\nIuTBP86FhyTrA5PlLi96aU9seVlsWVosx9QWxMRqbFrS+pv+rsTup5XajuGl9a8BgARo+ACYU/RD\n3dj5o3qTUtldjx1SpOn3id0/6XuWwpQA1J+ku6Nk+8zlY3ekQkaPD4A5NHwAzKHhA2BOI6ZVALCG\nHh8Ac2j4AJhDwwfAHBo+AObQ8AEwh4YPgDk0fADMoeEDYA4NHwBzaPgAmEPDB8AcGj4A5tDwATCH\nhg+AOTR8AMyh4QNgDg0fAHNo+ACYQ8MHwBwaPgDm0PABMIeGD4A5NHwAzPkf+qeGsgon9K0AAAAA\nSUVORK5CYII=\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 47 ---------------\ndLoss: 0.26\ngLoss: 2.40\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f13840a95f8>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4wLCBo\ndHRwOi8vbWF0cGxvdGxpYi5vcmcvpW3flQAAF3VJREFUeJzt3XmMlEXzwPFGhZXlcuUWgRVWEQQV\njYBEI5o1ShRRo5EgcgQ1Ip4xERPjFUk0JGo04hs1ATRGgxdEAUXxAEwAQQKIHCK4gqKinCssh8fv\nv/5VFU4zs7KzO1Pfz1/1pHZ3Bt9n+n26prq70T///BMAwJNj6vsNAEC+MfABcIeBD4A7DHwA3GHg\nA+AOAx8Adxj4ALjDwAfAHQY+AO4cl88Xq6ysZJlIAzFv3rxG9f0eikVZWVnB39d2BVejRplvj1x+\nNt927tyZ1ZvhiQ+AOwx8ANxh4APgTl5rfMWotvUNWyf5+++/Y3zMMfz/EepXbXdtStX/GlJtkE8Y\nAHcY+AC4w1Q3C6lH8ly+9pfXcmobAtNb1A15z9l7NZfprPzdY489VuXsvVwI+LQBcIeBD4A7DHwA\n3KHGlwVZf2vSpEnGXAghHDx4MMZ//fVX3b4x4AiyrU/b+9jeu7Ie+Oeff2bMFUqtujDeJQAcRQx8\nANxxNdXNtvXEPq7L68aNG2f9Gvb17BRBSrUEFMr0AQ2bvR/l9aFDh1SuVatW6rpbt24x3rt3r8r9\n8MMPMbb3eEPauUXiEwXAHQY+AO4w8AFwx1WNL7VER9YibJ3iuOP+/z/TCSecoHI1NTXqurq6+l9/\nL4TDl/rU5n0CtWXrbbJ2XFpaqnLDhg1T15dffnmMN23apHJTpkyJ8fr16zO+pq1jszsLAOQRAx8A\nd4puqpva0DPbLnY7fR06dGiM+/Tpo3JffPGFul61alWMf/31V5WTqzpsW4xcEVJSUqJy8t9k2w5S\naINB6p7fv39/jE888USVO/3009V1mzZtYizLOSGE0Llz5xhv3LhR5eQKkIbU2sInA4A7DHwA3GHg\nA+BO0dX4ZF0rteOsbTU5cOBAjCsrK1Vu7NixMba1uRYtWqjrjh07xnjXrl0ZX1++XgghfP/99zGu\nqqpSOdkGY+t2hbj7LY6ubA/0sfd8s2bNYnzjjTeqXP/+/dX18ccfH2Pb0iWXsy1dulTl9uzZk3zv\n9YUnPgDuMPABcKfoprry0d5upiinjHaHicGDB8f4vvvuUznZXmL/pmwJCCGE7t27x9i2BLRs2TLG\ndkPT7du3x/ipp55SueXLl8fYTleY6hanXM6gTR0oJO/5ffv2qdz1118f4/vvv1/lmjdvrq5lG5W9\nd0866aQYy7aXEHQLl/3M1eeZuzzxAXCHgQ+AOwx8ANwp+BpfqmUldYCKrEuEEMK9994bY7tkTFq7\ndq26fu2119R1z549M75Ghw4dMr432QbzwAMPqNyjjz4aY7skiBpfcTpaNS5ZY6uoqFC5Bx98MMa2\nRSXFtmLJ9iv7d2RdUb6XENKHcaXqlkcDT3wA3GHgA+BOwU91U+w0sLy8PMYTJ05UuaZNm2b8O999\n912Mx40bp3KdOnVS1/PmzYvx1q1bVe6xxx7L6vVat26trgcOHBjjzZs3q5zcNNVOHdidpTjlUt6R\nRowYoa5l6eVI5Gts2bJF5dasWRNj294lP4P2/ky1s9Q1PhkA3GHgA+AOAx8Adwq+xmdrA6kdmCdM\nmBBj2T5iyeVjIYRw6623xtjWRezOtTt37ozxwoULVe7111+PsdzxxbI1HLnDbaoWQk2veGR7MNaR\ncrKuduaZZ2b9d6w//vgjxnPmzFE5eaC43SFctrCklpDmG58UAO4w8AFwp+Cnupac7t18880qZzvX\nJdl6ctddd6mc3KnC7lphNw2VrSj20f6dd96J8ahRo1RO7rpipzm7d+/OmOMM3uKUallJ/W9uW7hk\n25TcHehI7N+R5+W+/fbbKid3XbHTV/l5adWqlcrJVR2pVpe6wBMfAHcY+AC4w8AHwJ2CrPGl5v9y\n1+OrrrpK5WT9wS6tkXU9+5W8rNvZZWj2Z2U7i82dfPLJMZZLzex7k38jhBA+//zzjL8n2boM7S3+\n2M+GvAdyqQfbmtu2bdtibJdbyoOIZD06BN3+Zd+bPGDL7g5d17VrPhkA3GHgA+BOQU51JTudu/TS\nS2NcWlqa8ffkjish6FaTiy66SOXklNVuwmi/opdTArs6ZPTo0TG209Lq6uoY281NV65cedj7/zdM\nbYtH6vCdVKnHlkLkyon/stnohg0bMr5GTU1NjO1BRAMGDIjxjh07VE7uNMTuLABQxxj4ALjDwAfA\nnYKs8aXqAV27ds3qb9j6n2x9adasmcr98ssvMZZf3Ydw+Nf30rXXXquuzznnnBjbdoFPPvkkxrNm\nzVK5uj54BQ1PasmavXdSyx3lDuHt27fP+Hr2by5btkxdz5w5M8a2lixrfoMGDVK5ysrKGH/99dcq\nt2jRohjL3V9CqPtDtHjiA+AOAx8Adxj4ALhTkDU+ydYb5HKvVC+U3V6qf//+MbbL0nbt2hVjWwux\nS98uvvjiGNt6h6zFbNq0SeVkH2Fq6RkHiMPW/+R9Ze9HuUO4/TzI/tTPPvtM5W655RZ1LWvitldP\n7uw8bNgwlZPLNJcvX65yqeWXdY0nPgDuMPABcKfgp7p2B5QFCxbEuFevXionpwRz585VudWrV8fY\nLq2RUwv7evbwofHjx8fYtg/8/PPPMX7ppZdUTh7S3LhxY5WTUwI7tU8droSGrbYHCqX+jlw+FkII\nZ511VoztMrRff/01xvfee6/K2TYtuXtznz59VG7MmDEx7tGjh8r99NNPMbaHb8nPGUvWAKCOMfAB\ncIeBD4A7BV/js+0dK1asiLGto8mf/fbbb1VOHiJu63hyd2TbzjJy5Eh1LWt+9r299957MV6zZo3K\nyRYB+xqp2h11vcJV25PULFkDtm1a/fr1y/g35WfF3keyLSsEfV/bUwjlMlFbH//oo49iLOvo9Y1P\nDQB3GPgAuFPwU13b+iEPLVm8eHHG37OHm5SUlMRYdpuHoL/2lys8Qghh8ODB6lpOi+WuLiGE8Omn\nn2Z833Z6mwkHChWvVAtLaoceeQ9069ZN5fr27Rtje6C4XFlkW1TatWunruXKDbtDkZxqy3s8hBDe\neuutGMtdxu37pp0FAOoYAx8Adxj4ALhT8DU+W/OStQJ5wpT9WVnTs+RBxyGE0KJFixjb9hX7d+Rr\nzpgxQ+X27NkTY1unkTU+lqUhxdaD5f0hTzULIYTu3bvH2O4sLq/t0stUq439XMmdlZ944gmVk3Vu\nWf8OQf878r2zOJ8iAO4w8AFwp+CnuvZrcPnYL3djsT9rp4xy5wrbanLPPffEuKKiQuXsxo+zZ8+O\n8Zw5c1ROPs7b983qDEi57Nwi71e5UiME3YZS2x1fQghh7969MX7//fdV7oUXXojxtm3bMr5XW5aq\nz4Oz+EQBcIeBD4A7DHwA3Cn4Gl9tD+axX98PHz48xueff77KyTqJbSWYP3++un711Vczvn6+l+Wg\ncKXaSWxbiCR38g5B7zSUauGy97U9DGvq1KkxfuONN1Qu1abVUA/H4okPgDsMfADcKfipbi6rHGTO\nPoKXlZXFOLVzyjfffKNykydPVteyqz3VYU+LCnKRaoWS95mdhrZp0ybG9pxn2cI1a9YslZs2bZq6\nlu0sqd1hst1lKIT0jjN1jU8fAHcY+AC4w8AHwJ1G+WyxqKysrPMXy7aOZmsRHTt2jLHdjVbuHCsP\naAnh8CVrcpmc3Jn2SPJd85s3b179rRcqMmVlZXntU7Kf2dRhWHK3ZLuEM3V/2sPHU/d1trU6+77r\noq63c+fOrP4oT3wA3GHgA+BOwbezWNmu3LCP/XLDRHtIkJxK2MfzXKYPmd4ncCSpklRqE1t5P6Za\nTezv2Wu5AsSuHMl2dUZ97sZi8ekD4A4DHwB3GPgAuFPwNb7U7iy5tLNkW3NLLRcC8iGXlpFs788j\ntbXJ17R/syHV7rLFEx8Adxj4ALhT8FPd1BQ1NQ0+0s/W5vX+y88C2cpltVW202J7r9rXSL1mfe6y\nUlt8MgG4w8AHwB0GPgDu5HV3FgBoCHjiA+AOAx8Adxj4ALjDwAfAHQY+AO4w8AFwh4EPgDsMfADc\nYeAD4A4DHwB3GPgAuMPAB8AdBj4A7jDwAXCHgQ+AOwx8ANxh4APgDgMfAHcY+AC4k9dzdXv27MkB\nHw3E2rVrC+MA1AJw2WWXFfx9bc/eSZ2Pm8qlzqfOx5m7c+fOzepFeOID4A4DHwB3GPgAuJPXGh+A\nupVLrU7+rP25Y47Rz0R//fVXxtc49thjs3q9hoQnPgDuMPABcIepbh6lphZAbWV7X2U77f03zZo1\ni/GhQ4dUbv/+/TGW094jvUZ9fgZ44gPgDgMfAHcY+AC4Q43vKJNtAHb5Tqqmkfo9ICXbWpmtscn7\nzLav9OzZU1137do1xuvXr1e5jRs3ZvX6DQlPfADcYeAD4I6rqa59nJdSj/2Zfi6Ew7++T7UFyJ9N\nfbVvX5+pL44Ge6/K+6xJkyYq16NHD3VdWloa4127dmV8jVxaZlKflbpudeGJD4A7DHwA3GHgA+CO\nqxpfqlaWquvJeoOtkxx3nP5PePzxx8e4efPmKieX+vz+++8Zc/a9yNeUu2TAp1R9OFVztveOvM/k\nkrQQDl+WVlVVFeMdO3aoXOPGjTO+hvzM/Zclc0cbT3wA3GHgA+COq6luajp78ODBGNsp8YUXXhjj\n3r17q9xJJ52krrt06RLj1q1bq5ycEmzfvl3l5syZE+N333034/uk1cWn1DSxpKQkxqmWkbKyMpWT\n9/KAAQNUrk2bNup6wYIFMbb3nCz32ClyaqrL7iwAkEcMfADcYeAD4I6rGp9k6wsXXHBBjB955BGV\nO/nkk2Ns6xt//PFHxmv71X779u1jXF5ernIVFRUx3rJli8otXLgwxrZ9BoUrl2WLkq3VDRo0KMa2\n5iyXotmas2y3OuGEE1ROtmWFEEKnTp1ivGfPHpVr2rRpjO2/Sf47clmyVtd44gPgDgMfAHfczpt6\n9eqlrp977rkYt2jRIuPv2a/rv/vuO3U9c+bMGC9evFjl7rnnnhhfeeWVKnfiiSfG+M4771S5L7/8\nMuP7YSVH4Uq1c9iSirw/5H0UQgjnnntujO3KDfl3ampqVE62VO3cuVPl7FS3uro6xnaqLae69n2n\n2sRS0/m6xhMfAHcY+AC4w8AHwJ2irvGlWj9GjhyprlN1Pfm1+/PPP69yr776asbfW7FihbqWNY0h\nQ4aonKz3yNaWEHRNJbX7LYpHu3bt1PXdd98dY1nTCyH7WuHmzZtVbsmSJRn/RseOHdX1b7/9FuOW\nLVuqXOqelPe8fY36XG7JEx8Adxj4ALhT1FNd+ygtv6K304WUlStXxnjKlCkqZzcbld3xtiXgtttu\ni3FqemJz9fm1P+pO6h7o37+/uj777LOz+j17z8+YMSPGb7/9tsrJUlD37t1Vzq6q2L17d4z37t2r\ncvL92PYq2eqyf/9+lavPs6T5RAFwh4EPgDsMfADccVXjS9Ui5LX92n/MmDExljushHD4Uh/5Gjfd\ndJPKXXHFFdm87bBt2zZ1LXfDqM8dLXB02f8t5XIzuVtQCNnvyvP000+r62nTpsXY1vH69u0b4+HD\nh6ucbe+Sh2PZ5Z5r1qyJsd25WX6WVq1apXLys5Lv3Zh54gPgDgMfAHeKbqqbav34888/Yzx37lyV\nk7tfTJo0SeVk17r9+3L3iRBCOO+882I8YsQIlZNf7Vtyqj19+nSVszvCoDjYUozc7NNOS7P17LPP\nqmu5ia5siQkhhNGjR8fYlnDs1FOeu2vbtC6//PIYy41PQwjh66+/jvG6detUrj7va574ALjDwAfA\nHQY+AO4UXY1P1k3sbrSyxiaXoYWga3WdO3dWOXkQiz1o5ZprrlHXo0aNinFqxxdb31m2bFmM33zz\nTZWjhaV4yNqZrZXJQ4NkTS0XdlmaPMS+W7duKid3WbE1PXvPyRq0rIeHcPiyTUm+pq3/UeMDgDxi\n4APgTtFNdWW7iX2U7tq1a4xPO+00ldu3b1+M7SO5bDPo16+fyg0YMEBdt23bNsZ2uiB3p7AHCP3v\nf//L+L5TK05QWOQ9YVdjnHHGGTGu7Y48sp0qBH2/2L8pc3JlRgghVFVVqWtZGrrhhhuyfj/ynGnZ\nThaCvq/zXc7hiQ+AOwx8ANxh4APgTtHV+GTdwh7YMn78+BjbGt9XX30VY9tmIFsC7NIeW5uQNQ3b\nsiLbVF555RWVk3U921pgayNoWFL1KVtXkz9rlzDanU1q8/qyVh2C3i3Z7py8YMGCGM+ePVvl5H0c\nQggffvhhjIcOHZr1e5O/l2pfsf8N63q3Fp74ALjDwAfAHQY+AO4UfI3PLkuT1xMmTFC5gQMHxtjW\nXnr37h1juaNsCCH88ssvMf7mm29U7pxzzlHXso/K7s788ccfx9j2TcmerpKSkoDCcaTlXpK87+yy\nNFkDS9V15TZpIeiDwe3WT1u3bv3XOAR9L9tT3Wyde9y4cTG2dW7J1gZnzpwZ49SStVz+Gx6N+h9P\nfADcYeAD4E5BTnXldMEu4SovL4/xJZdconJ2Wpzpb/70008qt2HDhhjbqe6QIUPU9SmnnBJjuyRJ\ntreUlpaqHMvSfJBT2O3bt6vcwoULY2zvwaVLl8b4008/VTk5LbU7gkv2fpT3qn0vtvXkhRdeiHFq\n6dvkyZNVTk59W7VqpXLy82Cnr7SzAMBRxsAHwB0GPgDuFGSNT7J1u4suuijGqVPNrFTLys8//xzj\n1q1bq5xskQlB1+5snWLHjh0xtnUSu7wNhSO13CqVs60fctmYvXdlDa66ulrl5GfA1vgOHDgQY7nj\ncgi6NmjbVx5//HF1ndpNfP78+TFOnV4ot2ULIf+HiEs88QFwh4EPgDsFOdWV00LbDS53Wc7lUVpO\nUeUhzCGE0KFDhxiPHTtW5VKHwsgDhEIIYffu3TG2UyD5b2IaXFhyuc/k/7b29+TuKXY6K9mVPXbX\nFUlONW07i3z9J598UuW6dOmS8W/++OOP6vrFF1+Msf08yFaXfLespPDEB8AdBj4A7jDwAXCnIGt8\nkv36fsWKFTG+7rrrVC51clVFRUWMH3roIZWTrQVlZWXJ9yPbDuzhznK5Umr5HDW94iVru6lWl9TO\nzbauLe+rVH3YtpNcffXVMe7YsWPG1wshhG3btsX44YcfVjl5z9f2veW73scTHwB3GPgAuFPwU137\n+PzRRx/FePTo0Sp36qmnxtg+WstH9M6dO2d8PTsNtV/tP/PMMzFev369yqWmt/AhtcFmqqUpNRWU\nOTvVlNPb7t27q5zdWUjasmWLun700UdjLFc5haBLQXZXF/nvsJ8d2lkAII8Y+AC4w8AHwJ2iq/HJ\n5TsTJ05Uudtvvz3G8nChEA7fnUKSdRJ7ENGkSZPU9erVq2MsDyIPgYPBkX2tzpK1QVsrSy2Dk20q\nd999t8rJnYZqampUburUqeraHnAkyR1gavvvyzee+AC4w8AHwJ2Cn+ra6aNsGZEHtIQQwh133BHj\nQYMGqdy5554b47Zt26qcbFmZPn26ylVVValrOb1lBQZqK9X2YsldV+QOQCHoA37sqiP52Vm0aJHK\nLV++POP7saul5Ovn8r7rE098ANxh4APgDgMfAHcKvsZnpQ7jlm0pH374ocp98MEHMU7t4nKkGgYt\nK0iR98/R2rk5dc9dfPHFMbYHesvlZQsWLFA5eTBWCLp2bZdeZlvLpp0FAOoRAx8Ad4puqpsipxm5\nTGdT01v72J/qsAeyne7Zn5P3UmqXH9uyUl5eHmNbBpLn+tqcnRbLFpZcWlYa0vRW4okPgDsMfADc\nYeAD4I6rGp+sk1B/QyGRtTJ778qan12y9vLLL8d4yZIlKidbVtatW6dyqRaZQtmBJYUnPgDuMPAB\ncMfVVBcoFKkzd+10UraiyJ1SQgjh999/j7FdnSHZqW0ur18oO7JIPPEBcIeBD4A7DHwA3GlUiPNz\nAPgveOID4A4DHwB3GPgAuMPAB8AdBj4A7jDwAXCHgQ+AOwx8ANxh4APgDgMfAHcY+AC4w8AHwB0G\nPgDuMPABcIeBD4A7DHwA3GHgA+AOAx8Adxj4ALjDwAfAHQY+AO4w8AFwh4EPgDv/B18pg3/8x+YU\nAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 48 ---------------\ndLoss: 0.26\ngLoss: 2.41\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f1384e964a8>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 49 ---------------\ndLoss: 0.26\ngLoss: 2.42\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f13848af4e0>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "text": "--------------- Epoch 50 ---------------\ndLoss: 0.26\ngLoss: 2.41\n(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f1384e9bb00>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAT4AAAD8CAYAAADub8g7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nnf8DW9F/LLvI/44AAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "trusted": true,
        "_uuid": "39b6919ff84e392c02154a19078dc43cee4f30cd"
      },
      "cell_type": "code",
      "source": "plt.figure(figsize=(10,7))\nplt.plot(gLosses,label='Generator Loss')\nplt.plot(dLosses, label='Discriminator Loss')\nplt.legend()",
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 47,
          "data": {
            "text/plain": "<matplotlib.legend.Legend at 0x7f13845ce0b8>"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f1363312d30>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAlYAAAGfCAYAAACdqpz+AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nS/4/y2vLAG7DxD0AAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "trusted": true,
        "_uuid": "5499c2ebc83a351298edc08b25d256dca36a3d02"
      },
      "cell_type": "code",
      "source": "r, c = 2, 2\nnoise = np.random.normal(0, 1, (r * c, 100))\ngen_imgs = generator.predict(noise)\nprint(gen_imgs.shape)\n# Rescale images 0 - 1\ngen_imgs = 0.5 * gen_imgs + 1\n\nfig, axs = plt.subplots(r, c,figsize=(15,15))\ncnt = 0\nfor i in range(r):\n    for j in range(c):\n        axs[i,j].imshow(gen_imgs[cnt, 0,:,:], cmap='gray')\n        axs[i,j].axis('off')\n        cnt += 1\n#fig.savefig(\"images/mnist_%d.png\" % epoch)\nplt.show()",
      "execution_count": 56,
      "outputs": [
        {
          "output_type": "stream",
          "text": "(4, 1, 28, 28)\n",
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<matplotlib.figure.Figure at 0x7f13a0c0a7b8>",
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAA2AAAANSCAYAAAADIK0CAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAMAAIgIMAAAgIgAAwAAiAgwAACAyAVbEdbqnYnfXAAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "collapsed": true,
        "_cell_guid": "233abc0e-db93-42f0-9741-d31a0e821de9",
        "_uuid": "47a682bb7bee7a2855147e54bda1605166349b24",
        "trusted": false
      },
      "cell_type": "code",
      "source": "",
      "execution_count": null,
      "outputs": []
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "name": "python",
      "version": "3.6.4",
      "mimetype": "text/x-python",
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "pygments_lexer": "ipython3",
      "nbconvert_exporter": "python",
      "file_extension": ".py"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 1
}