Retraining_InceptionV3.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Retraining Inception V3\n",
    "\n",
    "In this notebook, I will go over steps to retrain Inception V3 for the skin cancer dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "from glob import glob\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn.model_selection import train_test_split\n",
    "from keras.utils.np_utils import to_categorical # convert to one-hot-encoding\n",
    "\n",
    "from keras.preprocessing.image import ImageDataGenerator\n",
    "from keras import layers\n",
    "from keras import Model\n",
    "from keras.applications.inception_v3 import InceptionV3, preprocess_input\n",
    "from keras.optimizers import Adam\n",
    "from keras.callbacks import ReduceLROnPlateau, EarlyStopping\n",
    "\n",
    "\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load in the Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train = np.load(\"/floyd/input/skin_cancer_192_256/256_192_train.npy\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_train = np.load(\"/floyd/input/skin_cancer_192_256/train_labels.npy\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_val = np.load(\"/floyd/input/skin_cancer_192_256/256_192_val.npy\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_val = np.load(\"/floyd/input/skin_cancer_192_256/val_labels.npy\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((8111, 192, 256, 3), (902, 192, 256, 3))"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.shape, X_val.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((8111,), (902,))"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_train.shape, y_val.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_train = to_categorical(y_train)\n",
    "y_val = to_categorical(y_val)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((8111, 7), (902, 7))"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_train.shape, y_val.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load in Pretrained Inception Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "pre_trained_model = InceptionV3(input_shape=(192, 256, 3), include_top=False, weights=\"imagenet\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "input_1\n",
      "conv2d_1\n",
      "batch_normalization_1\n",
      "activation_1\n",
      "conv2d_2\n",
      "batch_normalization_2\n",
      "activation_2\n",
      "conv2d_3\n",
      "batch_normalization_3\n",
      "activation_3\n",
      "max_pooling2d_1\n",
      "conv2d_4\n",
      "batch_normalization_4\n",
      "activation_4\n",
      "conv2d_5\n",
      "batch_normalization_5\n",
      "activation_5\n",
      "max_pooling2d_2\n",
      "conv2d_9\n",
      "batch_normalization_9\n",
      "activation_9\n",
      "conv2d_7\n",
      "conv2d_10\n",
      "batch_normalization_7\n",
      "batch_normalization_10\n",
      "activation_7\n",
      "activation_10\n",
      "average_pooling2d_1\n",
      "conv2d_6\n",
      "conv2d_8\n",
      "conv2d_11\n",
      "conv2d_12\n",
      "batch_normalization_6\n",
      "batch_normalization_8\n",
      "batch_normalization_11\n",
      "batch_normalization_12\n",
      "activation_6\n",
      "activation_8\n",
      "activation_11\n",
      "activation_12\n",
      "mixed0\n",
      "conv2d_16\n",
      "batch_normalization_16\n",
      "activation_16\n",
      "conv2d_14\n",
      "conv2d_17\n",
      "batch_normalization_14\n",
      "batch_normalization_17\n",
      "activation_14\n",
      "activation_17\n",
      "average_pooling2d_2\n",
      "conv2d_13\n",
      "conv2d_15\n",
      "conv2d_18\n",
      "conv2d_19\n",
      "batch_normalization_13\n",
      "batch_normalization_15\n",
      "batch_normalization_18\n",
      "batch_normalization_19\n",
      "activation_13\n",
      "activation_15\n",
      "activation_18\n",
      "activation_19\n",
      "mixed1\n",
      "conv2d_23\n",
      "batch_normalization_23\n",
      "activation_23\n",
      "conv2d_21\n",
      "conv2d_24\n",
      "batch_normalization_21\n",
      "batch_normalization_24\n",
      "activation_21\n",
      "activation_24\n",
      "average_pooling2d_3\n",
      "conv2d_20\n",
      "conv2d_22\n",
      "conv2d_25\n",
      "conv2d_26\n",
      "batch_normalization_20\n",
      "batch_normalization_22\n",
      "batch_normalization_25\n",
      "batch_normalization_26\n",
      "activation_20\n",
      "activation_22\n",
      "activation_25\n",
      "activation_26\n",
      "mixed2\n",
      "conv2d_28\n",
      "batch_normalization_28\n",
      "activation_28\n",
      "conv2d_29\n",
      "batch_normalization_29\n",
      "activation_29\n",
      "conv2d_27\n",
      "conv2d_30\n",
      "batch_normalization_27\n",
      "batch_normalization_30\n",
      "activation_27\n",
      "activation_30\n",
      "max_pooling2d_3\n",
      "mixed3\n",
      "conv2d_35\n",
      "batch_normalization_35\n",
      "activation_35\n",
      "conv2d_36\n",
      "batch_normalization_36\n",
      "activation_36\n",
      "conv2d_32\n",
      "conv2d_37\n",
      "batch_normalization_32\n",
      "batch_normalization_37\n",
      "activation_32\n",
      "activation_37\n",
      "conv2d_33\n",
      "conv2d_38\n",
      "batch_normalization_33\n",
      "batch_normalization_38\n",
      "activation_33\n",
      "activation_38\n",
      "average_pooling2d_4\n",
      "conv2d_31\n",
      "conv2d_34\n",
      "conv2d_39\n",
      "conv2d_40\n",
      "batch_normalization_31\n",
      "batch_normalization_34\n",
      "batch_normalization_39\n",
      "batch_normalization_40\n",
      "activation_31\n",
      "activation_34\n",
      "activation_39\n",
      "activation_40\n",
      "mixed4\n",
      "conv2d_45\n",
      "batch_normalization_45\n",
      "activation_45\n",
      "conv2d_46\n",
      "batch_normalization_46\n",
      "activation_46\n",
      "conv2d_42\n",
      "conv2d_47\n",
      "batch_normalization_42\n",
      "batch_normalization_47\n",
      "activation_42\n",
      "activation_47\n",
      "conv2d_43\n",
      "conv2d_48\n",
      "batch_normalization_43\n",
      "batch_normalization_48\n",
      "activation_43\n",
      "activation_48\n",
      "average_pooling2d_5\n",
      "conv2d_41\n",
      "conv2d_44\n",
      "conv2d_49\n",
      "conv2d_50\n",
      "batch_normalization_41\n",
      "batch_normalization_44\n",
      "batch_normalization_49\n",
      "batch_normalization_50\n",
      "activation_41\n",
      "activation_44\n",
      "activation_49\n",
      "activation_50\n",
      "mixed5\n",
      "conv2d_55\n",
      "batch_normalization_55\n",
      "activation_55\n",
      "conv2d_56\n",
      "batch_normalization_56\n",
      "activation_56\n",
      "conv2d_52\n",
      "conv2d_57\n",
      "batch_normalization_52\n",
      "batch_normalization_57\n",
      "activation_52\n",
      "activation_57\n",
      "conv2d_53\n",
      "conv2d_58\n",
      "batch_normalization_53\n",
      "batch_normalization_58\n",
      "activation_53\n",
      "activation_58\n",
      "average_pooling2d_6\n",
      "conv2d_51\n",
      "conv2d_54\n",
      "conv2d_59\n",
      "conv2d_60\n",
      "batch_normalization_51\n",
      "batch_normalization_54\n",
      "batch_normalization_59\n",
      "batch_normalization_60\n",
      "activation_51\n",
      "activation_54\n",
      "activation_59\n",
      "activation_60\n",
      "mixed6\n",
      "conv2d_65\n",
      "batch_normalization_65\n",
      "activation_65\n",
      "conv2d_66\n",
      "batch_normalization_66\n",
      "activation_66\n",
      "conv2d_62\n",
      "conv2d_67\n",
      "batch_normalization_62\n",
      "batch_normalization_67\n",
      "activation_62\n",
      "activation_67\n",
      "conv2d_63\n",
      "conv2d_68\n",
      "batch_normalization_63\n",
      "batch_normalization_68\n",
      "activation_63\n",
      "activation_68\n",
      "average_pooling2d_7\n",
      "conv2d_61\n",
      "conv2d_64\n",
      "conv2d_69\n",
      "conv2d_70\n",
      "batch_normalization_61\n",
      "batch_normalization_64\n",
      "batch_normalization_69\n",
      "batch_normalization_70\n",
      "activation_61\n",
      "activation_64\n",
      "activation_69\n",
      "activation_70\n",
      "mixed7\n",
      "conv2d_73\n",
      "batch_normalization_73\n",
      "activation_73\n",
      "conv2d_74\n",
      "batch_normalization_74\n",
      "activation_74\n",
      "conv2d_71\n",
      "conv2d_75\n",
      "batch_normalization_71\n",
      "batch_normalization_75\n",
      "activation_71\n",
      "activation_75\n",
      "conv2d_72\n",
      "conv2d_76\n",
      "batch_normalization_72\n",
      "batch_normalization_76\n",
      "activation_72\n",
      "activation_76\n",
      "max_pooling2d_4\n",
      "mixed8\n",
      "conv2d_81\n",
      "batch_normalization_81\n",
      "activation_81\n",
      "conv2d_78\n",
      "conv2d_82\n",
      "batch_normalization_78\n",
      "batch_normalization_82\n",
      "activation_78\n",
      "activation_82\n",
      "conv2d_79\n",
      "conv2d_80\n",
      "conv2d_83\n",
      "conv2d_84\n",
      "average_pooling2d_8\n",
      "conv2d_77\n",
      "batch_normalization_79\n",
      "batch_normalization_80\n",
      "batch_normalization_83\n",
      "batch_normalization_84\n",
      "conv2d_85\n",
      "batch_normalization_77\n",
      "activation_79\n",
      "activation_80\n",
      "activation_83\n",
      "activation_84\n",
      "batch_normalization_85\n",
      "activation_77\n",
      "mixed9_0\n",
      "concatenate_1\n",
      "activation_85\n",
      "mixed9\n",
      "conv2d_90\n",
      "batch_normalization_90\n",
      "activation_90\n",
      "conv2d_87\n",
      "conv2d_91\n",
      "batch_normalization_87\n",
      "batch_normalization_91\n",
      "activation_87\n",
      "activation_91\n",
      "conv2d_88\n",
      "conv2d_89\n",
      "conv2d_92\n",
      "conv2d_93\n",
      "average_pooling2d_9\n",
      "conv2d_86\n",
      "batch_normalization_88\n",
      "batch_normalization_89\n",
      "batch_normalization_92\n",
      "batch_normalization_93\n",
      "conv2d_94\n",
      "batch_normalization_86\n",
      "activation_88\n",
      "activation_89\n",
      "activation_92\n",
      "activation_93\n",
      "batch_normalization_94\n",
      "activation_86\n",
      "mixed9_1\n",
      "concatenate_2\n",
      "activation_94\n",
      "mixed10\n",
      "311\n"
     ]
    }
   ],
   "source": [
    "for layer in pre_trained_model.layers:\n",
    "    print(layer.name)\n",
    "    layer.trainable = False\n",
    "    \n",
    "print(len(pre_trained_model.layers))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "last layer output shape: (None, 4, 6, 2048)\n"
     ]
    }
   ],
   "source": [
    "last_layer = pre_trained_model.get_layer('mixed10')\n",
    "print('last layer output shape:', last_layer.output_shape)\n",
    "last_output = last_layer.output"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define the Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Flatten the output layer to 1 dimension\n",
    "x = layers.GlobalMaxPooling2D()(last_output)\n",
    "# Add a fully connected layer with 512 hidden units and ReLU activation\n",
    "x = layers.Dense(512, activation='relu')(x)\n",
    "# Add a dropout rate of 0.7\n",
    "x = layers.Dropout(0.5)(x)\n",
    "# Add a final sigmoid layer for classification\n",
    "x = layers.Dense(7, activation='softmax')(x)\n",
    "\n",
    "# Configure and compile the model\n",
    "\n",
    "model = Model(pre_trained_model.input, x)\n",
    "optimizer = Adam(lr=0.0001, beta_1=0.9, beta_2=0.999, epsilon=None, decay=0.0, amsgrad=True)\n",
    "model.compile(loss='categorical_crossentropy',\n",
    "              optimizer=optimizer,\n",
    "              metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_1 (InputLayer)            (None, 192, 256, 3)  0                                            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_1 (Conv2D)               (None, 95, 127, 32)  864         input_1[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_1 (BatchNor (None, 95, 127, 32)  96          conv2d_1[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_1 (Activation)       (None, 95, 127, 32)  0           batch_normalization_1[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_2 (Conv2D)               (None, 93, 125, 32)  9216        activation_1[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_2 (BatchNor (None, 93, 125, 32)  96          conv2d_2[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_2 (Activation)       (None, 93, 125, 32)  0           batch_normalization_2[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_3 (Conv2D)               (None, 93, 125, 64)  18432       activation_2[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_3 (BatchNor (None, 93, 125, 64)  192         conv2d_3[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_3 (Activation)       (None, 93, 125, 64)  0           batch_normalization_3[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_1 (MaxPooling2D)  (None, 46, 62, 64)   0           activation_3[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_4 (Conv2D)               (None, 46, 62, 80)   5120        max_pooling2d_1[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_4 (BatchNor (None, 46, 62, 80)   240         conv2d_4[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_4 (Activation)       (None, 46, 62, 80)   0           batch_normalization_4[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_5 (Conv2D)               (None, 44, 60, 192)  138240      activation_4[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_5 (BatchNor (None, 44, 60, 192)  576         conv2d_5[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_5 (Activation)       (None, 44, 60, 192)  0           batch_normalization_5[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_2 (MaxPooling2D)  (None, 21, 29, 192)  0           activation_5[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_9 (Conv2D)               (None, 21, 29, 64)   12288       max_pooling2d_2[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_9 (BatchNor (None, 21, 29, 64)   192         conv2d_9[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_9 (Activation)       (None, 21, 29, 64)   0           batch_normalization_9[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_7 (Conv2D)               (None, 21, 29, 48)   9216        max_pooling2d_2[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_10 (Conv2D)              (None, 21, 29, 96)   55296       activation_9[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_7 (BatchNor (None, 21, 29, 48)   144         conv2d_7[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_10 (BatchNo (None, 21, 29, 96)   288         conv2d_10[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_7 (Activation)       (None, 21, 29, 48)   0           batch_normalization_7[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "activation_10 (Activation)      (None, 21, 29, 96)   0           batch_normalization_10[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_1 (AveragePoo (None, 21, 29, 192)  0           max_pooling2d_2[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_6 (Conv2D)               (None, 21, 29, 64)   12288       max_pooling2d_2[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_8 (Conv2D)               (None, 21, 29, 64)   76800       activation_7[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_11 (Conv2D)              (None, 21, 29, 96)   82944       activation_10[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_12 (Conv2D)              (None, 21, 29, 32)   6144        average_pooling2d_1[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_6 (BatchNor (None, 21, 29, 64)   192         conv2d_6[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_8 (BatchNor (None, 21, 29, 64)   192         conv2d_8[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_11 (BatchNo (None, 21, 29, 96)   288         conv2d_11[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_12 (BatchNo (None, 21, 29, 32)   96          conv2d_12[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_6 (Activation)       (None, 21, 29, 64)   0           batch_normalization_6[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "activation_8 (Activation)       (None, 21, 29, 64)   0           batch_normalization_8[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "activation_11 (Activation)      (None, 21, 29, 96)   0           batch_normalization_11[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_12 (Activation)      (None, 21, 29, 32)   0           batch_normalization_12[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed0 (Concatenate)            (None, 21, 29, 256)  0           activation_6[0][0]               \n",
      "                                                                 activation_8[0][0]               \n",
      "                                                                 activation_11[0][0]              \n",
      "                                                                 activation_12[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_16 (Conv2D)              (None, 21, 29, 64)   16384       mixed0[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_16 (BatchNo (None, 21, 29, 64)   192         conv2d_16[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_16 (Activation)      (None, 21, 29, 64)   0           batch_normalization_16[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_14 (Conv2D)              (None, 21, 29, 48)   12288       mixed0[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_17 (Conv2D)              (None, 21, 29, 96)   55296       activation_16[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_14 (BatchNo (None, 21, 29, 48)   144         conv2d_14[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_17 (BatchNo (None, 21, 29, 96)   288         conv2d_17[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_14 (Activation)      (None, 21, 29, 48)   0           batch_normalization_14[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_17 (Activation)      (None, 21, 29, 96)   0           batch_normalization_17[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_2 (AveragePoo (None, 21, 29, 256)  0           mixed0[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_13 (Conv2D)              (None, 21, 29, 64)   16384       mixed0[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_15 (Conv2D)              (None, 21, 29, 64)   76800       activation_14[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_18 (Conv2D)              (None, 21, 29, 96)   82944       activation_17[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_19 (Conv2D)              (None, 21, 29, 64)   16384       average_pooling2d_2[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_13 (BatchNo (None, 21, 29, 64)   192         conv2d_13[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_15 (BatchNo (None, 21, 29, 64)   192         conv2d_15[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_18 (BatchNo (None, 21, 29, 96)   288         conv2d_18[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_19 (BatchNo (None, 21, 29, 64)   192         conv2d_19[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_13 (Activation)      (None, 21, 29, 64)   0           batch_normalization_13[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_15 (Activation)      (None, 21, 29, 64)   0           batch_normalization_15[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_18 (Activation)      (None, 21, 29, 96)   0           batch_normalization_18[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_19 (Activation)      (None, 21, 29, 64)   0           batch_normalization_19[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed1 (Concatenate)            (None, 21, 29, 288)  0           activation_13[0][0]              \n",
      "                                                                 activation_15[0][0]              \n",
      "                                                                 activation_18[0][0]              \n",
      "                                                                 activation_19[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_23 (Conv2D)              (None, 21, 29, 64)   18432       mixed1[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_23 (BatchNo (None, 21, 29, 64)   192         conv2d_23[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_23 (Activation)      (None, 21, 29, 64)   0           batch_normalization_23[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_21 (Conv2D)              (None, 21, 29, 48)   13824       mixed1[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_24 (Conv2D)              (None, 21, 29, 96)   55296       activation_23[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_21 (BatchNo (None, 21, 29, 48)   144         conv2d_21[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_24 (BatchNo (None, 21, 29, 96)   288         conv2d_24[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_21 (Activation)      (None, 21, 29, 48)   0           batch_normalization_21[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_24 (Activation)      (None, 21, 29, 96)   0           batch_normalization_24[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_3 (AveragePoo (None, 21, 29, 288)  0           mixed1[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_20 (Conv2D)              (None, 21, 29, 64)   18432       mixed1[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_22 (Conv2D)              (None, 21, 29, 64)   76800       activation_21[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_25 (Conv2D)              (None, 21, 29, 96)   82944       activation_24[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_26 (Conv2D)              (None, 21, 29, 64)   18432       average_pooling2d_3[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_20 (BatchNo (None, 21, 29, 64)   192         conv2d_20[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_22 (BatchNo (None, 21, 29, 64)   192         conv2d_22[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_25 (BatchNo (None, 21, 29, 96)   288         conv2d_25[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_26 (BatchNo (None, 21, 29, 64)   192         conv2d_26[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_20 (Activation)      (None, 21, 29, 64)   0           batch_normalization_20[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_22 (Activation)      (None, 21, 29, 64)   0           batch_normalization_22[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_25 (Activation)      (None, 21, 29, 96)   0           batch_normalization_25[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_26 (Activation)      (None, 21, 29, 64)   0           batch_normalization_26[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed2 (Concatenate)            (None, 21, 29, 288)  0           activation_20[0][0]              \n",
      "                                                                 activation_22[0][0]              \n",
      "                                                                 activation_25[0][0]              \n",
      "                                                                 activation_26[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_28 (Conv2D)              (None, 21, 29, 64)   18432       mixed2[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_28 (BatchNo (None, 21, 29, 64)   192         conv2d_28[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_28 (Activation)      (None, 21, 29, 64)   0           batch_normalization_28[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_29 (Conv2D)              (None, 21, 29, 96)   55296       activation_28[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_29 (BatchNo (None, 21, 29, 96)   288         conv2d_29[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_29 (Activation)      (None, 21, 29, 96)   0           batch_normalization_29[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_27 (Conv2D)              (None, 10, 14, 384)  995328      mixed2[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_30 (Conv2D)              (None, 10, 14, 96)   82944       activation_29[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_27 (BatchNo (None, 10, 14, 384)  1152        conv2d_27[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_30 (BatchNo (None, 10, 14, 96)   288         conv2d_30[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_27 (Activation)      (None, 10, 14, 384)  0           batch_normalization_27[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_30 (Activation)      (None, 10, 14, 96)   0           batch_normalization_30[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_3 (MaxPooling2D)  (None, 10, 14, 288)  0           mixed2[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "mixed3 (Concatenate)            (None, 10, 14, 768)  0           activation_27[0][0]              \n",
      "                                                                 activation_30[0][0]              \n",
      "                                                                 max_pooling2d_3[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_35 (Conv2D)              (None, 10, 14, 128)  98304       mixed3[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_35 (BatchNo (None, 10, 14, 128)  384         conv2d_35[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_35 (Activation)      (None, 10, 14, 128)  0           batch_normalization_35[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_36 (Conv2D)              (None, 10, 14, 128)  114688      activation_35[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_36 (BatchNo (None, 10, 14, 128)  384         conv2d_36[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_36 (Activation)      (None, 10, 14, 128)  0           batch_normalization_36[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_32 (Conv2D)              (None, 10, 14, 128)  98304       mixed3[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_37 (Conv2D)              (None, 10, 14, 128)  114688      activation_36[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_32 (BatchNo (None, 10, 14, 128)  384         conv2d_32[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_37 (BatchNo (None, 10, 14, 128)  384         conv2d_37[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_32 (Activation)      (None, 10, 14, 128)  0           batch_normalization_32[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_37 (Activation)      (None, 10, 14, 128)  0           batch_normalization_37[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_33 (Conv2D)              (None, 10, 14, 128)  114688      activation_32[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_38 (Conv2D)              (None, 10, 14, 128)  114688      activation_37[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_33 (BatchNo (None, 10, 14, 128)  384         conv2d_33[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_38 (BatchNo (None, 10, 14, 128)  384         conv2d_38[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_33 (Activation)      (None, 10, 14, 128)  0           batch_normalization_33[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_38 (Activation)      (None, 10, 14, 128)  0           batch_normalization_38[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_4 (AveragePoo (None, 10, 14, 768)  0           mixed3[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_31 (Conv2D)              (None, 10, 14, 192)  147456      mixed3[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_34 (Conv2D)              (None, 10, 14, 192)  172032      activation_33[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_39 (Conv2D)              (None, 10, 14, 192)  172032      activation_38[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_40 (Conv2D)              (None, 10, 14, 192)  147456      average_pooling2d_4[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_31 (BatchNo (None, 10, 14, 192)  576         conv2d_31[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_34 (BatchNo (None, 10, 14, 192)  576         conv2d_34[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_39 (BatchNo (None, 10, 14, 192)  576         conv2d_39[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_40 (BatchNo (None, 10, 14, 192)  576         conv2d_40[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_31 (Activation)      (None, 10, 14, 192)  0           batch_normalization_31[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_34 (Activation)      (None, 10, 14, 192)  0           batch_normalization_34[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_39 (Activation)      (None, 10, 14, 192)  0           batch_normalization_39[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_40 (Activation)      (None, 10, 14, 192)  0           batch_normalization_40[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed4 (Concatenate)            (None, 10, 14, 768)  0           activation_31[0][0]              \n",
      "                                                                 activation_34[0][0]              \n",
      "                                                                 activation_39[0][0]              \n",
      "                                                                 activation_40[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_45 (Conv2D)              (None, 10, 14, 160)  122880      mixed4[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_45 (BatchNo (None, 10, 14, 160)  480         conv2d_45[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_45 (Activation)      (None, 10, 14, 160)  0           batch_normalization_45[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_46 (Conv2D)              (None, 10, 14, 160)  179200      activation_45[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_46 (BatchNo (None, 10, 14, 160)  480         conv2d_46[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_46 (Activation)      (None, 10, 14, 160)  0           batch_normalization_46[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_42 (Conv2D)              (None, 10, 14, 160)  122880      mixed4[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_47 (Conv2D)              (None, 10, 14, 160)  179200      activation_46[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_42 (BatchNo (None, 10, 14, 160)  480         conv2d_42[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_47 (BatchNo (None, 10, 14, 160)  480         conv2d_47[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_42 (Activation)      (None, 10, 14, 160)  0           batch_normalization_42[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_47 (Activation)      (None, 10, 14, 160)  0           batch_normalization_47[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_43 (Conv2D)              (None, 10, 14, 160)  179200      activation_42[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_48 (Conv2D)              (None, 10, 14, 160)  179200      activation_47[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_43 (BatchNo (None, 10, 14, 160)  480         conv2d_43[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_48 (BatchNo (None, 10, 14, 160)  480         conv2d_48[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_43 (Activation)      (None, 10, 14, 160)  0           batch_normalization_43[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_48 (Activation)      (None, 10, 14, 160)  0           batch_normalization_48[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_5 (AveragePoo (None, 10, 14, 768)  0           mixed4[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_41 (Conv2D)              (None, 10, 14, 192)  147456      mixed4[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_44 (Conv2D)              (None, 10, 14, 192)  215040      activation_43[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_49 (Conv2D)              (None, 10, 14, 192)  215040      activation_48[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_50 (Conv2D)              (None, 10, 14, 192)  147456      average_pooling2d_5[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_41 (BatchNo (None, 10, 14, 192)  576         conv2d_41[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_44 (BatchNo (None, 10, 14, 192)  576         conv2d_44[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_49 (BatchNo (None, 10, 14, 192)  576         conv2d_49[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_50 (BatchNo (None, 10, 14, 192)  576         conv2d_50[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_41 (Activation)      (None, 10, 14, 192)  0           batch_normalization_41[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_44 (Activation)      (None, 10, 14, 192)  0           batch_normalization_44[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_49 (Activation)      (None, 10, 14, 192)  0           batch_normalization_49[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_50 (Activation)      (None, 10, 14, 192)  0           batch_normalization_50[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed5 (Concatenate)            (None, 10, 14, 768)  0           activation_41[0][0]              \n",
      "                                                                 activation_44[0][0]              \n",
      "                                                                 activation_49[0][0]              \n",
      "                                                                 activation_50[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_55 (Conv2D)              (None, 10, 14, 160)  122880      mixed5[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_55 (BatchNo (None, 10, 14, 160)  480         conv2d_55[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_55 (Activation)      (None, 10, 14, 160)  0           batch_normalization_55[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_56 (Conv2D)              (None, 10, 14, 160)  179200      activation_55[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_56 (BatchNo (None, 10, 14, 160)  480         conv2d_56[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_56 (Activation)      (None, 10, 14, 160)  0           batch_normalization_56[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_52 (Conv2D)              (None, 10, 14, 160)  122880      mixed5[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_57 (Conv2D)              (None, 10, 14, 160)  179200      activation_56[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_52 (BatchNo (None, 10, 14, 160)  480         conv2d_52[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_57 (BatchNo (None, 10, 14, 160)  480         conv2d_57[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_52 (Activation)      (None, 10, 14, 160)  0           batch_normalization_52[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_57 (Activation)      (None, 10, 14, 160)  0           batch_normalization_57[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_53 (Conv2D)              (None, 10, 14, 160)  179200      activation_52[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_58 (Conv2D)              (None, 10, 14, 160)  179200      activation_57[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_53 (BatchNo (None, 10, 14, 160)  480         conv2d_53[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_58 (BatchNo (None, 10, 14, 160)  480         conv2d_58[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_53 (Activation)      (None, 10, 14, 160)  0           batch_normalization_53[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_58 (Activation)      (None, 10, 14, 160)  0           batch_normalization_58[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_6 (AveragePoo (None, 10, 14, 768)  0           mixed5[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_51 (Conv2D)              (None, 10, 14, 192)  147456      mixed5[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_54 (Conv2D)              (None, 10, 14, 192)  215040      activation_53[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_59 (Conv2D)              (None, 10, 14, 192)  215040      activation_58[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_60 (Conv2D)              (None, 10, 14, 192)  147456      average_pooling2d_6[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_51 (BatchNo (None, 10, 14, 192)  576         conv2d_51[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_54 (BatchNo (None, 10, 14, 192)  576         conv2d_54[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_59 (BatchNo (None, 10, 14, 192)  576         conv2d_59[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_60 (BatchNo (None, 10, 14, 192)  576         conv2d_60[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_51 (Activation)      (None, 10, 14, 192)  0           batch_normalization_51[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_54 (Activation)      (None, 10, 14, 192)  0           batch_normalization_54[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_59 (Activation)      (None, 10, 14, 192)  0           batch_normalization_59[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_60 (Activation)      (None, 10, 14, 192)  0           batch_normalization_60[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed6 (Concatenate)            (None, 10, 14, 768)  0           activation_51[0][0]              \n",
      "                                                                 activation_54[0][0]              \n",
      "                                                                 activation_59[0][0]              \n",
      "                                                                 activation_60[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_65 (Conv2D)              (None, 10, 14, 192)  147456      mixed6[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_65 (BatchNo (None, 10, 14, 192)  576         conv2d_65[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_65 (Activation)      (None, 10, 14, 192)  0           batch_normalization_65[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_66 (Conv2D)              (None, 10, 14, 192)  258048      activation_65[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_66 (BatchNo (None, 10, 14, 192)  576         conv2d_66[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_66 (Activation)      (None, 10, 14, 192)  0           batch_normalization_66[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_62 (Conv2D)              (None, 10, 14, 192)  147456      mixed6[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_67 (Conv2D)              (None, 10, 14, 192)  258048      activation_66[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_62 (BatchNo (None, 10, 14, 192)  576         conv2d_62[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_67 (BatchNo (None, 10, 14, 192)  576         conv2d_67[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_62 (Activation)      (None, 10, 14, 192)  0           batch_normalization_62[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_67 (Activation)      (None, 10, 14, 192)  0           batch_normalization_67[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_63 (Conv2D)              (None, 10, 14, 192)  258048      activation_62[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_68 (Conv2D)              (None, 10, 14, 192)  258048      activation_67[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_63 (BatchNo (None, 10, 14, 192)  576         conv2d_63[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_68 (BatchNo (None, 10, 14, 192)  576         conv2d_68[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_63 (Activation)      (None, 10, 14, 192)  0           batch_normalization_63[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_68 (Activation)      (None, 10, 14, 192)  0           batch_normalization_68[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_7 (AveragePoo (None, 10, 14, 768)  0           mixed6[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_61 (Conv2D)              (None, 10, 14, 192)  147456      mixed6[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_64 (Conv2D)              (None, 10, 14, 192)  258048      activation_63[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_69 (Conv2D)              (None, 10, 14, 192)  258048      activation_68[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_70 (Conv2D)              (None, 10, 14, 192)  147456      average_pooling2d_7[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_61 (BatchNo (None, 10, 14, 192)  576         conv2d_61[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_64 (BatchNo (None, 10, 14, 192)  576         conv2d_64[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_69 (BatchNo (None, 10, 14, 192)  576         conv2d_69[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_70 (BatchNo (None, 10, 14, 192)  576         conv2d_70[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_61 (Activation)      (None, 10, 14, 192)  0           batch_normalization_61[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_64 (Activation)      (None, 10, 14, 192)  0           batch_normalization_64[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_69 (Activation)      (None, 10, 14, 192)  0           batch_normalization_69[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_70 (Activation)      (None, 10, 14, 192)  0           batch_normalization_70[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed7 (Concatenate)            (None, 10, 14, 768)  0           activation_61[0][0]              \n",
      "                                                                 activation_64[0][0]              \n",
      "                                                                 activation_69[0][0]              \n",
      "                                                                 activation_70[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_73 (Conv2D)              (None, 10, 14, 192)  147456      mixed7[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_73 (BatchNo (None, 10, 14, 192)  576         conv2d_73[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_73 (Activation)      (None, 10, 14, 192)  0           batch_normalization_73[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_74 (Conv2D)              (None, 10, 14, 192)  258048      activation_73[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_74 (BatchNo (None, 10, 14, 192)  576         conv2d_74[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_74 (Activation)      (None, 10, 14, 192)  0           batch_normalization_74[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_71 (Conv2D)              (None, 10, 14, 192)  147456      mixed7[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_75 (Conv2D)              (None, 10, 14, 192)  258048      activation_74[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_71 (BatchNo (None, 10, 14, 192)  576         conv2d_71[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_75 (BatchNo (None, 10, 14, 192)  576         conv2d_75[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_71 (Activation)      (None, 10, 14, 192)  0           batch_normalization_71[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_75 (Activation)      (None, 10, 14, 192)  0           batch_normalization_75[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_72 (Conv2D)              (None, 4, 6, 320)    552960      activation_71[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_76 (Conv2D)              (None, 4, 6, 192)    331776      activation_75[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_72 (BatchNo (None, 4, 6, 320)    960         conv2d_72[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_76 (BatchNo (None, 4, 6, 192)    576         conv2d_76[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_72 (Activation)      (None, 4, 6, 320)    0           batch_normalization_72[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_76 (Activation)      (None, 4, 6, 192)    0           batch_normalization_76[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_4 (MaxPooling2D)  (None, 4, 6, 768)    0           mixed7[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "mixed8 (Concatenate)            (None, 4, 6, 1280)   0           activation_72[0][0]              \n",
      "                                                                 activation_76[0][0]              \n",
      "                                                                 max_pooling2d_4[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_81 (Conv2D)              (None, 4, 6, 448)    573440      mixed8[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_81 (BatchNo (None, 4, 6, 448)    1344        conv2d_81[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_81 (Activation)      (None, 4, 6, 448)    0           batch_normalization_81[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_78 (Conv2D)              (None, 4, 6, 384)    491520      mixed8[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_82 (Conv2D)              (None, 4, 6, 384)    1548288     activation_81[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_78 (BatchNo (None, 4, 6, 384)    1152        conv2d_78[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_82 (BatchNo (None, 4, 6, 384)    1152        conv2d_82[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_78 (Activation)      (None, 4, 6, 384)    0           batch_normalization_78[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_82 (Activation)      (None, 4, 6, 384)    0           batch_normalization_82[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_79 (Conv2D)              (None, 4, 6, 384)    442368      activation_78[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_80 (Conv2D)              (None, 4, 6, 384)    442368      activation_78[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_83 (Conv2D)              (None, 4, 6, 384)    442368      activation_82[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_84 (Conv2D)              (None, 4, 6, 384)    442368      activation_82[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_8 (AveragePoo (None, 4, 6, 1280)   0           mixed8[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_77 (Conv2D)              (None, 4, 6, 320)    409600      mixed8[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_79 (BatchNo (None, 4, 6, 384)    1152        conv2d_79[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_80 (BatchNo (None, 4, 6, 384)    1152        conv2d_80[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_83 (BatchNo (None, 4, 6, 384)    1152        conv2d_83[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_84 (BatchNo (None, 4, 6, 384)    1152        conv2d_84[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_85 (Conv2D)              (None, 4, 6, 192)    245760      average_pooling2d_8[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_77 (BatchNo (None, 4, 6, 320)    960         conv2d_77[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_79 (Activation)      (None, 4, 6, 384)    0           batch_normalization_79[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_80 (Activation)      (None, 4, 6, 384)    0           batch_normalization_80[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_83 (Activation)      (None, 4, 6, 384)    0           batch_normalization_83[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_84 (Activation)      (None, 4, 6, 384)    0           batch_normalization_84[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_85 (BatchNo (None, 4, 6, 192)    576         conv2d_85[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_77 (Activation)      (None, 4, 6, 320)    0           batch_normalization_77[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed9_0 (Concatenate)          (None, 4, 6, 768)    0           activation_79[0][0]              \n",
      "                                                                 activation_80[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "concatenate_1 (Concatenate)     (None, 4, 6, 768)    0           activation_83[0][0]              \n",
      "                                                                 activation_84[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "activation_85 (Activation)      (None, 4, 6, 192)    0           batch_normalization_85[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed9 (Concatenate)            (None, 4, 6, 2048)   0           activation_77[0][0]              \n",
      "                                                                 mixed9_0[0][0]                   \n",
      "                                                                 concatenate_1[0][0]              \n",
      "                                                                 activation_85[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_90 (Conv2D)              (None, 4, 6, 448)    917504      mixed9[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_90 (BatchNo (None, 4, 6, 448)    1344        conv2d_90[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_90 (Activation)      (None, 4, 6, 448)    0           batch_normalization_90[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_87 (Conv2D)              (None, 4, 6, 384)    786432      mixed9[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_91 (Conv2D)              (None, 4, 6, 384)    1548288     activation_90[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_87 (BatchNo (None, 4, 6, 384)    1152        conv2d_87[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_91 (BatchNo (None, 4, 6, 384)    1152        conv2d_91[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_87 (Activation)      (None, 4, 6, 384)    0           batch_normalization_87[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_91 (Activation)      (None, 4, 6, 384)    0           batch_normalization_91[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_88 (Conv2D)              (None, 4, 6, 384)    442368      activation_87[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_89 (Conv2D)              (None, 4, 6, 384)    442368      activation_87[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_92 (Conv2D)              (None, 4, 6, 384)    442368      activation_91[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_93 (Conv2D)              (None, 4, 6, 384)    442368      activation_91[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_9 (AveragePoo (None, 4, 6, 2048)   0           mixed9[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_86 (Conv2D)              (None, 4, 6, 320)    655360      mixed9[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_88 (BatchNo (None, 4, 6, 384)    1152        conv2d_88[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_89 (BatchNo (None, 4, 6, 384)    1152        conv2d_89[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_92 (BatchNo (None, 4, 6, 384)    1152        conv2d_92[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_93 (BatchNo (None, 4, 6, 384)    1152        conv2d_93[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_94 (Conv2D)              (None, 4, 6, 192)    393216      average_pooling2d_9[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_86 (BatchNo (None, 4, 6, 320)    960         conv2d_86[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_88 (Activation)      (None, 4, 6, 384)    0           batch_normalization_88[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_89 (Activation)      (None, 4, 6, 384)    0           batch_normalization_89[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_92 (Activation)      (None, 4, 6, 384)    0           batch_normalization_92[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_93 (Activation)      (None, 4, 6, 384)    0           batch_normalization_93[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_94 (BatchNo (None, 4, 6, 192)    576         conv2d_94[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_86 (Activation)      (None, 4, 6, 320)    0           batch_normalization_86[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed9_1 (Concatenate)          (None, 4, 6, 768)    0           activation_88[0][0]              \n",
      "                                                                 activation_89[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "concatenate_2 (Concatenate)     (None, 4, 6, 768)    0           activation_92[0][0]              \n",
      "                                                                 activation_93[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "activation_94 (Activation)      (None, 4, 6, 192)    0           batch_normalization_94[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed10 (Concatenate)           (None, 4, 6, 2048)   0           activation_86[0][0]              \n",
      "                                                                 mixed9_1[0][0]                   \n",
      "                                                                 concatenate_2[0][0]              \n",
      "                                                                 activation_94[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "global_max_pooling2d_1 (GlobalM (None, 2048)         0           mixed10[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "dense_1 (Dense)                 (None, 512)          1049088     global_max_pooling2d_1[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "dropout_1 (Dropout)             (None, 512)          0           dense_1[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "dense_2 (Dense)                 (None, 7)            3591        dropout_1[0][0]                  \n",
      "==================================================================================================\n",
      "Total params: 22,855,463\n",
      "Trainable params: 1,052,679\n",
      "Non-trainable params: 21,802,784\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Training\n",
    "\n",
    "Here we retrain using the whole model instead of performing transfer learning. The reason for this is the issue with batch-normalization layer implemented in Keras. During training the network will always use the mini-batch statistics either the BN layer is frozen or not; also during inference it will use the previously learned statistics of the frozen BN layers. As a result, if we fine-tune the top layers, their weights will be adjusted to the mean/variance of the new dataset. Nevertheless, during inference they will receive data which are scaled differently because the mean/variance of the original dataset will be used. Consequently, performing transfer-learning with InceptionV3 will result in very bad validation accuracy. For solution to this issue, have a look at: https://github.com/keras-team/keras/pull/9965 and https://github.com/keras-team/keras/issues/9214. For now, let's just retrain the whole model with very small learning_rate = 0.0001 and large momentum and a learning_rate_reduction function that halves the learning whenever the validation accuracy doesn't change for a 3 consecutive epochs. We will train for only 20 epochs so that the weights of the original pretrained model won't change too much and overfit the train data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Feature Extraction\n",
    "\n",
    "Before we even retrain our model, it's better that we freeze all the layers in InceptionV3 and just train our top fully-connected and classification layers so that the weights for these layers won't be too random. The intuition for this is that if we didn't perform feature-extraction, then the gradient would be too large and would change the pretrained weights too much."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_datagen = ImageDataGenerator(rotation_range=60, width_shift_range=0.2, height_shift_range=0.2,\n",
    "                                   shear_range=0.2, zoom_range=0.2, fill_mode='nearest')\n",
    "\n",
    "train_datagen.fit(X_train)\n",
    "\n",
    "val_datagen = ImageDataGenerator()\n",
    "val_datagen.fit(X_val)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/3\n",
      "126/126 [==============================] - 90s 712ms/step - loss: 1.5553 - acc: 0.6029 - val_loss: 1.5893 - val_acc: 0.6719\n",
      "Epoch 2/3\n",
      "126/126 [==============================] - 83s 662ms/step - loss: 1.0996 - acc: 0.6609 - val_loss: 1.7558 - val_acc: 0.6562\n",
      "Epoch 3/3\n",
      "126/126 [==============================] - 85s 673ms/step - loss: 1.0364 - acc: 0.6737 - val_loss: 1.7136 - val_acc: 0.6706\n"
     ]
    }
   ],
   "source": [
    "batch_size = 64\n",
    "epochs = 3\n",
    "history = model.fit_generator(train_datagen.flow(X_train,y_train, batch_size=batch_size),\n",
    "                              epochs = epochs, validation_data = val_datagen.flow(X_val, y_val),\n",
    "                              verbose = 1, steps_per_epoch=(X_train.shape[0] // batch_size), \n",
    "                              validation_steps=(X_val.shape[0] // batch_size))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Retraining\n",
    "\n",
    "Now, we are retraining the whole models. The goal is to just tune the weights a bit for our dataset and avoid changing the pretrained weights too much!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "for layer in pre_trained_model.layers:\n",
    "    layer.trainable = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "optimizer = Adam(lr=0.0001, beta_1=0.9, beta_2=0.999, epsilon=None, decay=0.0, amsgrad=False)\n",
    "model.compile(loss='categorical_crossentropy',\n",
    "              optimizer=optimizer,\n",
    "              metrics=['acc'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "learning_rate_reduction = ReduceLROnPlateau(monitor='val_acc', patience=3, verbose=1, factor=0.5, \n",
    "                                            min_lr=0.000001, cooldown=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_1 (InputLayer)            (None, 192, 256, 3)  0                                            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_1 (Conv2D)               (None, 95, 127, 32)  864         input_1[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_1 (BatchNor (None, 95, 127, 32)  96          conv2d_1[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_1 (Activation)       (None, 95, 127, 32)  0           batch_normalization_1[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_2 (Conv2D)               (None, 93, 125, 32)  9216        activation_1[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_2 (BatchNor (None, 93, 125, 32)  96          conv2d_2[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_2 (Activation)       (None, 93, 125, 32)  0           batch_normalization_2[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_3 (Conv2D)               (None, 93, 125, 64)  18432       activation_2[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_3 (BatchNor (None, 93, 125, 64)  192         conv2d_3[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_3 (Activation)       (None, 93, 125, 64)  0           batch_normalization_3[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_1 (MaxPooling2D)  (None, 46, 62, 64)   0           activation_3[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_4 (Conv2D)               (None, 46, 62, 80)   5120        max_pooling2d_1[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_4 (BatchNor (None, 46, 62, 80)   240         conv2d_4[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_4 (Activation)       (None, 46, 62, 80)   0           batch_normalization_4[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_5 (Conv2D)               (None, 44, 60, 192)  138240      activation_4[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_5 (BatchNor (None, 44, 60, 192)  576         conv2d_5[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_5 (Activation)       (None, 44, 60, 192)  0           batch_normalization_5[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_2 (MaxPooling2D)  (None, 21, 29, 192)  0           activation_5[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_9 (Conv2D)               (None, 21, 29, 64)   12288       max_pooling2d_2[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_9 (BatchNor (None, 21, 29, 64)   192         conv2d_9[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_9 (Activation)       (None, 21, 29, 64)   0           batch_normalization_9[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_7 (Conv2D)               (None, 21, 29, 48)   9216        max_pooling2d_2[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_10 (Conv2D)              (None, 21, 29, 96)   55296       activation_9[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_7 (BatchNor (None, 21, 29, 48)   144         conv2d_7[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_10 (BatchNo (None, 21, 29, 96)   288         conv2d_10[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_7 (Activation)       (None, 21, 29, 48)   0           batch_normalization_7[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "activation_10 (Activation)      (None, 21, 29, 96)   0           batch_normalization_10[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_1 (AveragePoo (None, 21, 29, 192)  0           max_pooling2d_2[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_6 (Conv2D)               (None, 21, 29, 64)   12288       max_pooling2d_2[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_8 (Conv2D)               (None, 21, 29, 64)   76800       activation_7[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_11 (Conv2D)              (None, 21, 29, 96)   82944       activation_10[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_12 (Conv2D)              (None, 21, 29, 32)   6144        average_pooling2d_1[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_6 (BatchNor (None, 21, 29, 64)   192         conv2d_6[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_8 (BatchNor (None, 21, 29, 64)   192         conv2d_8[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_11 (BatchNo (None, 21, 29, 96)   288         conv2d_11[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_12 (BatchNo (None, 21, 29, 32)   96          conv2d_12[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_6 (Activation)       (None, 21, 29, 64)   0           batch_normalization_6[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "activation_8 (Activation)       (None, 21, 29, 64)   0           batch_normalization_8[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "activation_11 (Activation)      (None, 21, 29, 96)   0           batch_normalization_11[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_12 (Activation)      (None, 21, 29, 32)   0           batch_normalization_12[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed0 (Concatenate)            (None, 21, 29, 256)  0           activation_6[0][0]               \n",
      "                                                                 activation_8[0][0]               \n",
      "                                                                 activation_11[0][0]              \n",
      "                                                                 activation_12[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_16 (Conv2D)              (None, 21, 29, 64)   16384       mixed0[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_16 (BatchNo (None, 21, 29, 64)   192         conv2d_16[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_16 (Activation)      (None, 21, 29, 64)   0           batch_normalization_16[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_14 (Conv2D)              (None, 21, 29, 48)   12288       mixed0[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_17 (Conv2D)              (None, 21, 29, 96)   55296       activation_16[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_14 (BatchNo (None, 21, 29, 48)   144         conv2d_14[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_17 (BatchNo (None, 21, 29, 96)   288         conv2d_17[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_14 (Activation)      (None, 21, 29, 48)   0           batch_normalization_14[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_17 (Activation)      (None, 21, 29, 96)   0           batch_normalization_17[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_2 (AveragePoo (None, 21, 29, 256)  0           mixed0[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_13 (Conv2D)              (None, 21, 29, 64)   16384       mixed0[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_15 (Conv2D)              (None, 21, 29, 64)   76800       activation_14[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_18 (Conv2D)              (None, 21, 29, 96)   82944       activation_17[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_19 (Conv2D)              (None, 21, 29, 64)   16384       average_pooling2d_2[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_13 (BatchNo (None, 21, 29, 64)   192         conv2d_13[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_15 (BatchNo (None, 21, 29, 64)   192         conv2d_15[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_18 (BatchNo (None, 21, 29, 96)   288         conv2d_18[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_19 (BatchNo (None, 21, 29, 64)   192         conv2d_19[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_13 (Activation)      (None, 21, 29, 64)   0           batch_normalization_13[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_15 (Activation)      (None, 21, 29, 64)   0           batch_normalization_15[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_18 (Activation)      (None, 21, 29, 96)   0           batch_normalization_18[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_19 (Activation)      (None, 21, 29, 64)   0           batch_normalization_19[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed1 (Concatenate)            (None, 21, 29, 288)  0           activation_13[0][0]              \n",
      "                                                                 activation_15[0][0]              \n",
      "                                                                 activation_18[0][0]              \n",
      "                                                                 activation_19[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_23 (Conv2D)              (None, 21, 29, 64)   18432       mixed1[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_23 (BatchNo (None, 21, 29, 64)   192         conv2d_23[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_23 (Activation)      (None, 21, 29, 64)   0           batch_normalization_23[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_21 (Conv2D)              (None, 21, 29, 48)   13824       mixed1[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_24 (Conv2D)              (None, 21, 29, 96)   55296       activation_23[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_21 (BatchNo (None, 21, 29, 48)   144         conv2d_21[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_24 (BatchNo (None, 21, 29, 96)   288         conv2d_24[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_21 (Activation)      (None, 21, 29, 48)   0           batch_normalization_21[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_24 (Activation)      (None, 21, 29, 96)   0           batch_normalization_24[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_3 (AveragePoo (None, 21, 29, 288)  0           mixed1[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_20 (Conv2D)              (None, 21, 29, 64)   18432       mixed1[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_22 (Conv2D)              (None, 21, 29, 64)   76800       activation_21[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_25 (Conv2D)              (None, 21, 29, 96)   82944       activation_24[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_26 (Conv2D)              (None, 21, 29, 64)   18432       average_pooling2d_3[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_20 (BatchNo (None, 21, 29, 64)   192         conv2d_20[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_22 (BatchNo (None, 21, 29, 64)   192         conv2d_22[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_25 (BatchNo (None, 21, 29, 96)   288         conv2d_25[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_26 (BatchNo (None, 21, 29, 64)   192         conv2d_26[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_20 (Activation)      (None, 21, 29, 64)   0           batch_normalization_20[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_22 (Activation)      (None, 21, 29, 64)   0           batch_normalization_22[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_25 (Activation)      (None, 21, 29, 96)   0           batch_normalization_25[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_26 (Activation)      (None, 21, 29, 64)   0           batch_normalization_26[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed2 (Concatenate)            (None, 21, 29, 288)  0           activation_20[0][0]              \n",
      "                                                                 activation_22[0][0]              \n",
      "                                                                 activation_25[0][0]              \n",
      "                                                                 activation_26[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_28 (Conv2D)              (None, 21, 29, 64)   18432       mixed2[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_28 (BatchNo (None, 21, 29, 64)   192         conv2d_28[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_28 (Activation)      (None, 21, 29, 64)   0           batch_normalization_28[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_29 (Conv2D)              (None, 21, 29, 96)   55296       activation_28[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_29 (BatchNo (None, 21, 29, 96)   288         conv2d_29[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_29 (Activation)      (None, 21, 29, 96)   0           batch_normalization_29[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_27 (Conv2D)              (None, 10, 14, 384)  995328      mixed2[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_30 (Conv2D)              (None, 10, 14, 96)   82944       activation_29[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_27 (BatchNo (None, 10, 14, 384)  1152        conv2d_27[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_30 (BatchNo (None, 10, 14, 96)   288         conv2d_30[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_27 (Activation)      (None, 10, 14, 384)  0           batch_normalization_27[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_30 (Activation)      (None, 10, 14, 96)   0           batch_normalization_30[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_3 (MaxPooling2D)  (None, 10, 14, 288)  0           mixed2[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "mixed3 (Concatenate)            (None, 10, 14, 768)  0           activation_27[0][0]              \n",
      "                                                                 activation_30[0][0]              \n",
      "                                                                 max_pooling2d_3[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_35 (Conv2D)              (None, 10, 14, 128)  98304       mixed3[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_35 (BatchNo (None, 10, 14, 128)  384         conv2d_35[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_35 (Activation)      (None, 10, 14, 128)  0           batch_normalization_35[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_36 (Conv2D)              (None, 10, 14, 128)  114688      activation_35[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_36 (BatchNo (None, 10, 14, 128)  384         conv2d_36[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_36 (Activation)      (None, 10, 14, 128)  0           batch_normalization_36[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_32 (Conv2D)              (None, 10, 14, 128)  98304       mixed3[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_37 (Conv2D)              (None, 10, 14, 128)  114688      activation_36[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_32 (BatchNo (None, 10, 14, 128)  384         conv2d_32[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_37 (BatchNo (None, 10, 14, 128)  384         conv2d_37[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_32 (Activation)      (None, 10, 14, 128)  0           batch_normalization_32[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_37 (Activation)      (None, 10, 14, 128)  0           batch_normalization_37[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_33 (Conv2D)              (None, 10, 14, 128)  114688      activation_32[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_38 (Conv2D)              (None, 10, 14, 128)  114688      activation_37[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_33 (BatchNo (None, 10, 14, 128)  384         conv2d_33[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_38 (BatchNo (None, 10, 14, 128)  384         conv2d_38[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_33 (Activation)      (None, 10, 14, 128)  0           batch_normalization_33[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_38 (Activation)      (None, 10, 14, 128)  0           batch_normalization_38[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_4 (AveragePoo (None, 10, 14, 768)  0           mixed3[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_31 (Conv2D)              (None, 10, 14, 192)  147456      mixed3[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_34 (Conv2D)              (None, 10, 14, 192)  172032      activation_33[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_39 (Conv2D)              (None, 10, 14, 192)  172032      activation_38[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_40 (Conv2D)              (None, 10, 14, 192)  147456      average_pooling2d_4[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_31 (BatchNo (None, 10, 14, 192)  576         conv2d_31[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_34 (BatchNo (None, 10, 14, 192)  576         conv2d_34[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_39 (BatchNo (None, 10, 14, 192)  576         conv2d_39[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_40 (BatchNo (None, 10, 14, 192)  576         conv2d_40[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_31 (Activation)      (None, 10, 14, 192)  0           batch_normalization_31[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_34 (Activation)      (None, 10, 14, 192)  0           batch_normalization_34[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_39 (Activation)      (None, 10, 14, 192)  0           batch_normalization_39[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_40 (Activation)      (None, 10, 14, 192)  0           batch_normalization_40[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed4 (Concatenate)            (None, 10, 14, 768)  0           activation_31[0][0]              \n",
      "                                                                 activation_34[0][0]              \n",
      "                                                                 activation_39[0][0]              \n",
      "                                                                 activation_40[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_45 (Conv2D)              (None, 10, 14, 160)  122880      mixed4[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_45 (BatchNo (None, 10, 14, 160)  480         conv2d_45[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_45 (Activation)      (None, 10, 14, 160)  0           batch_normalization_45[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_46 (Conv2D)              (None, 10, 14, 160)  179200      activation_45[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_46 (BatchNo (None, 10, 14, 160)  480         conv2d_46[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_46 (Activation)      (None, 10, 14, 160)  0           batch_normalization_46[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_42 (Conv2D)              (None, 10, 14, 160)  122880      mixed4[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_47 (Conv2D)              (None, 10, 14, 160)  179200      activation_46[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_42 (BatchNo (None, 10, 14, 160)  480         conv2d_42[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_47 (BatchNo (None, 10, 14, 160)  480         conv2d_47[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_42 (Activation)      (None, 10, 14, 160)  0           batch_normalization_42[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_47 (Activation)      (None, 10, 14, 160)  0           batch_normalization_47[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_43 (Conv2D)              (None, 10, 14, 160)  179200      activation_42[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_48 (Conv2D)              (None, 10, 14, 160)  179200      activation_47[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_43 (BatchNo (None, 10, 14, 160)  480         conv2d_43[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_48 (BatchNo (None, 10, 14, 160)  480         conv2d_48[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_43 (Activation)      (None, 10, 14, 160)  0           batch_normalization_43[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_48 (Activation)      (None, 10, 14, 160)  0           batch_normalization_48[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_5 (AveragePoo (None, 10, 14, 768)  0           mixed4[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_41 (Conv2D)              (None, 10, 14, 192)  147456      mixed4[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_44 (Conv2D)              (None, 10, 14, 192)  215040      activation_43[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_49 (Conv2D)              (None, 10, 14, 192)  215040      activation_48[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_50 (Conv2D)              (None, 10, 14, 192)  147456      average_pooling2d_5[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_41 (BatchNo (None, 10, 14, 192)  576         conv2d_41[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_44 (BatchNo (None, 10, 14, 192)  576         conv2d_44[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_49 (BatchNo (None, 10, 14, 192)  576         conv2d_49[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_50 (BatchNo (None, 10, 14, 192)  576         conv2d_50[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_41 (Activation)      (None, 10, 14, 192)  0           batch_normalization_41[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_44 (Activation)      (None, 10, 14, 192)  0           batch_normalization_44[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_49 (Activation)      (None, 10, 14, 192)  0           batch_normalization_49[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_50 (Activation)      (None, 10, 14, 192)  0           batch_normalization_50[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed5 (Concatenate)            (None, 10, 14, 768)  0           activation_41[0][0]              \n",
      "                                                                 activation_44[0][0]              \n",
      "                                                                 activation_49[0][0]              \n",
      "                                                                 activation_50[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_55 (Conv2D)              (None, 10, 14, 160)  122880      mixed5[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_55 (BatchNo (None, 10, 14, 160)  480         conv2d_55[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_55 (Activation)      (None, 10, 14, 160)  0           batch_normalization_55[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_56 (Conv2D)              (None, 10, 14, 160)  179200      activation_55[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_56 (BatchNo (None, 10, 14, 160)  480         conv2d_56[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_56 (Activation)      (None, 10, 14, 160)  0           batch_normalization_56[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_52 (Conv2D)              (None, 10, 14, 160)  122880      mixed5[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_57 (Conv2D)              (None, 10, 14, 160)  179200      activation_56[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_52 (BatchNo (None, 10, 14, 160)  480         conv2d_52[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_57 (BatchNo (None, 10, 14, 160)  480         conv2d_57[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_52 (Activation)      (None, 10, 14, 160)  0           batch_normalization_52[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_57 (Activation)      (None, 10, 14, 160)  0           batch_normalization_57[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_53 (Conv2D)              (None, 10, 14, 160)  179200      activation_52[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_58 (Conv2D)              (None, 10, 14, 160)  179200      activation_57[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_53 (BatchNo (None, 10, 14, 160)  480         conv2d_53[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_58 (BatchNo (None, 10, 14, 160)  480         conv2d_58[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_53 (Activation)      (None, 10, 14, 160)  0           batch_normalization_53[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_58 (Activation)      (None, 10, 14, 160)  0           batch_normalization_58[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_6 (AveragePoo (None, 10, 14, 768)  0           mixed5[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_51 (Conv2D)              (None, 10, 14, 192)  147456      mixed5[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_54 (Conv2D)              (None, 10, 14, 192)  215040      activation_53[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_59 (Conv2D)              (None, 10, 14, 192)  215040      activation_58[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_60 (Conv2D)              (None, 10, 14, 192)  147456      average_pooling2d_6[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_51 (BatchNo (None, 10, 14, 192)  576         conv2d_51[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_54 (BatchNo (None, 10, 14, 192)  576         conv2d_54[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_59 (BatchNo (None, 10, 14, 192)  576         conv2d_59[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_60 (BatchNo (None, 10, 14, 192)  576         conv2d_60[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_51 (Activation)      (None, 10, 14, 192)  0           batch_normalization_51[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_54 (Activation)      (None, 10, 14, 192)  0           batch_normalization_54[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_59 (Activation)      (None, 10, 14, 192)  0           batch_normalization_59[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_60 (Activation)      (None, 10, 14, 192)  0           batch_normalization_60[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed6 (Concatenate)            (None, 10, 14, 768)  0           activation_51[0][0]              \n",
      "                                                                 activation_54[0][0]              \n",
      "                                                                 activation_59[0][0]              \n",
      "                                                                 activation_60[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_65 (Conv2D)              (None, 10, 14, 192)  147456      mixed6[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_65 (BatchNo (None, 10, 14, 192)  576         conv2d_65[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_65 (Activation)      (None, 10, 14, 192)  0           batch_normalization_65[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_66 (Conv2D)              (None, 10, 14, 192)  258048      activation_65[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_66 (BatchNo (None, 10, 14, 192)  576         conv2d_66[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_66 (Activation)      (None, 10, 14, 192)  0           batch_normalization_66[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_62 (Conv2D)              (None, 10, 14, 192)  147456      mixed6[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_67 (Conv2D)              (None, 10, 14, 192)  258048      activation_66[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_62 (BatchNo (None, 10, 14, 192)  576         conv2d_62[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_67 (BatchNo (None, 10, 14, 192)  576         conv2d_67[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_62 (Activation)      (None, 10, 14, 192)  0           batch_normalization_62[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_67 (Activation)      (None, 10, 14, 192)  0           batch_normalization_67[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_63 (Conv2D)              (None, 10, 14, 192)  258048      activation_62[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_68 (Conv2D)              (None, 10, 14, 192)  258048      activation_67[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_63 (BatchNo (None, 10, 14, 192)  576         conv2d_63[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_68 (BatchNo (None, 10, 14, 192)  576         conv2d_68[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_63 (Activation)      (None, 10, 14, 192)  0           batch_normalization_63[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_68 (Activation)      (None, 10, 14, 192)  0           batch_normalization_68[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_7 (AveragePoo (None, 10, 14, 768)  0           mixed6[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_61 (Conv2D)              (None, 10, 14, 192)  147456      mixed6[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_64 (Conv2D)              (None, 10, 14, 192)  258048      activation_63[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_69 (Conv2D)              (None, 10, 14, 192)  258048      activation_68[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_70 (Conv2D)              (None, 10, 14, 192)  147456      average_pooling2d_7[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_61 (BatchNo (None, 10, 14, 192)  576         conv2d_61[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_64 (BatchNo (None, 10, 14, 192)  576         conv2d_64[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_69 (BatchNo (None, 10, 14, 192)  576         conv2d_69[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_70 (BatchNo (None, 10, 14, 192)  576         conv2d_70[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_61 (Activation)      (None, 10, 14, 192)  0           batch_normalization_61[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_64 (Activation)      (None, 10, 14, 192)  0           batch_normalization_64[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_69 (Activation)      (None, 10, 14, 192)  0           batch_normalization_69[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_70 (Activation)      (None, 10, 14, 192)  0           batch_normalization_70[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed7 (Concatenate)            (None, 10, 14, 768)  0           activation_61[0][0]              \n",
      "                                                                 activation_64[0][0]              \n",
      "                                                                 activation_69[0][0]              \n",
      "                                                                 activation_70[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_73 (Conv2D)              (None, 10, 14, 192)  147456      mixed7[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_73 (BatchNo (None, 10, 14, 192)  576         conv2d_73[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_73 (Activation)      (None, 10, 14, 192)  0           batch_normalization_73[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_74 (Conv2D)              (None, 10, 14, 192)  258048      activation_73[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_74 (BatchNo (None, 10, 14, 192)  576         conv2d_74[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_74 (Activation)      (None, 10, 14, 192)  0           batch_normalization_74[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_71 (Conv2D)              (None, 10, 14, 192)  147456      mixed7[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_75 (Conv2D)              (None, 10, 14, 192)  258048      activation_74[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_71 (BatchNo (None, 10, 14, 192)  576         conv2d_71[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_75 (BatchNo (None, 10, 14, 192)  576         conv2d_75[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_71 (Activation)      (None, 10, 14, 192)  0           batch_normalization_71[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_75 (Activation)      (None, 10, 14, 192)  0           batch_normalization_75[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_72 (Conv2D)              (None, 4, 6, 320)    552960      activation_71[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_76 (Conv2D)              (None, 4, 6, 192)    331776      activation_75[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_72 (BatchNo (None, 4, 6, 320)    960         conv2d_72[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_76 (BatchNo (None, 4, 6, 192)    576         conv2d_76[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_72 (Activation)      (None, 4, 6, 320)    0           batch_normalization_72[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_76 (Activation)      (None, 4, 6, 192)    0           batch_normalization_76[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_4 (MaxPooling2D)  (None, 4, 6, 768)    0           mixed7[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "mixed8 (Concatenate)            (None, 4, 6, 1280)   0           activation_72[0][0]              \n",
      "                                                                 activation_76[0][0]              \n",
      "                                                                 max_pooling2d_4[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_81 (Conv2D)              (None, 4, 6, 448)    573440      mixed8[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_81 (BatchNo (None, 4, 6, 448)    1344        conv2d_81[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_81 (Activation)      (None, 4, 6, 448)    0           batch_normalization_81[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_78 (Conv2D)              (None, 4, 6, 384)    491520      mixed8[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_82 (Conv2D)              (None, 4, 6, 384)    1548288     activation_81[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_78 (BatchNo (None, 4, 6, 384)    1152        conv2d_78[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_82 (BatchNo (None, 4, 6, 384)    1152        conv2d_82[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_78 (Activation)      (None, 4, 6, 384)    0           batch_normalization_78[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_82 (Activation)      (None, 4, 6, 384)    0           batch_normalization_82[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_79 (Conv2D)              (None, 4, 6, 384)    442368      activation_78[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_80 (Conv2D)              (None, 4, 6, 384)    442368      activation_78[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_83 (Conv2D)              (None, 4, 6, 384)    442368      activation_82[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_84 (Conv2D)              (None, 4, 6, 384)    442368      activation_82[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_8 (AveragePoo (None, 4, 6, 1280)   0           mixed8[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_77 (Conv2D)              (None, 4, 6, 320)    409600      mixed8[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_79 (BatchNo (None, 4, 6, 384)    1152        conv2d_79[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_80 (BatchNo (None, 4, 6, 384)    1152        conv2d_80[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_83 (BatchNo (None, 4, 6, 384)    1152        conv2d_83[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_84 (BatchNo (None, 4, 6, 384)    1152        conv2d_84[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_85 (Conv2D)              (None, 4, 6, 192)    245760      average_pooling2d_8[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_77 (BatchNo (None, 4, 6, 320)    960         conv2d_77[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_79 (Activation)      (None, 4, 6, 384)    0           batch_normalization_79[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_80 (Activation)      (None, 4, 6, 384)    0           batch_normalization_80[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_83 (Activation)      (None, 4, 6, 384)    0           batch_normalization_83[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_84 (Activation)      (None, 4, 6, 384)    0           batch_normalization_84[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_85 (BatchNo (None, 4, 6, 192)    576         conv2d_85[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_77 (Activation)      (None, 4, 6, 320)    0           batch_normalization_77[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed9_0 (Concatenate)          (None, 4, 6, 768)    0           activation_79[0][0]              \n",
      "                                                                 activation_80[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "concatenate_1 (Concatenate)     (None, 4, 6, 768)    0           activation_83[0][0]              \n",
      "                                                                 activation_84[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "activation_85 (Activation)      (None, 4, 6, 192)    0           batch_normalization_85[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed9 (Concatenate)            (None, 4, 6, 2048)   0           activation_77[0][0]              \n",
      "                                                                 mixed9_0[0][0]                   \n",
      "                                                                 concatenate_1[0][0]              \n",
      "                                                                 activation_85[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_90 (Conv2D)              (None, 4, 6, 448)    917504      mixed9[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_90 (BatchNo (None, 4, 6, 448)    1344        conv2d_90[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_90 (Activation)      (None, 4, 6, 448)    0           batch_normalization_90[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_87 (Conv2D)              (None, 4, 6, 384)    786432      mixed9[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_91 (Conv2D)              (None, 4, 6, 384)    1548288     activation_90[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_87 (BatchNo (None, 4, 6, 384)    1152        conv2d_87[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_91 (BatchNo (None, 4, 6, 384)    1152        conv2d_91[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_87 (Activation)      (None, 4, 6, 384)    0           batch_normalization_87[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_91 (Activation)      (None, 4, 6, 384)    0           batch_normalization_91[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_88 (Conv2D)              (None, 4, 6, 384)    442368      activation_87[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_89 (Conv2D)              (None, 4, 6, 384)    442368      activation_87[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_92 (Conv2D)              (None, 4, 6, 384)    442368      activation_91[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_93 (Conv2D)              (None, 4, 6, 384)    442368      activation_91[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_9 (AveragePoo (None, 4, 6, 2048)   0           mixed9[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_86 (Conv2D)              (None, 4, 6, 320)    655360      mixed9[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_88 (BatchNo (None, 4, 6, 384)    1152        conv2d_88[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_89 (BatchNo (None, 4, 6, 384)    1152        conv2d_89[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_92 (BatchNo (None, 4, 6, 384)    1152        conv2d_92[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_93 (BatchNo (None, 4, 6, 384)    1152        conv2d_93[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_94 (Conv2D)              (None, 4, 6, 192)    393216      average_pooling2d_9[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_86 (BatchNo (None, 4, 6, 320)    960         conv2d_86[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_88 (Activation)      (None, 4, 6, 384)    0           batch_normalization_88[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_89 (Activation)      (None, 4, 6, 384)    0           batch_normalization_89[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_92 (Activation)      (None, 4, 6, 384)    0           batch_normalization_92[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_93 (Activation)      (None, 4, 6, 384)    0           batch_normalization_93[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_94 (BatchNo (None, 4, 6, 192)    576         conv2d_94[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_86 (Activation)      (None, 4, 6, 320)    0           batch_normalization_86[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed9_1 (Concatenate)          (None, 4, 6, 768)    0           activation_88[0][0]              \n",
      "                                                                 activation_89[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "concatenate_2 (Concatenate)     (None, 4, 6, 768)    0           activation_92[0][0]              \n",
      "                                                                 activation_93[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "activation_94 (Activation)      (None, 4, 6, 192)    0           batch_normalization_94[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "mixed10 (Concatenate)           (None, 4, 6, 2048)   0           activation_86[0][0]              \n",
      "                                                                 mixed9_1[0][0]                   \n",
      "                                                                 concatenate_2[0][0]              \n",
      "                                                                 activation_94[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "global_max_pooling2d_1 (GlobalM (None, 2048)         0           mixed10[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "dense_1 (Dense)                 (None, 512)          1049088     global_max_pooling2d_1[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "dropout_1 (Dropout)             (None, 512)          0           dense_1[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "dense_2 (Dense)                 (None, 7)            3591        dropout_1[0][0]                  \n",
      "==================================================================================================\n",
      "Total params: 22,855,463\n",
      "Trainable params: 22,821,031\n",
      "Non-trainable params: 34,432\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/20\n",
      "126/126 [==============================] - 168s 1s/step - loss: 0.8607 - acc: 0.7015 - val_loss: 0.7481 - val_acc: 0.7165\n",
      "Epoch 2/20\n",
      "126/126 [==============================] - 150s 1s/step - loss: 0.6642 - acc: 0.7636 - val_loss: 0.5757 - val_acc: 0.7969\n",
      "Epoch 3/20\n",
      "126/126 [==============================] - 148s 1s/step - loss: 0.5690 - acc: 0.7949 - val_loss: 0.5249 - val_acc: 0.8057\n",
      "Epoch 4/20\n",
      "126/126 [==============================] - 148s 1s/step - loss: 0.4897 - acc: 0.8233 - val_loss: 0.6070 - val_acc: 0.7879\n",
      "Epoch 5/20\n",
      "126/126 [==============================] - 148s 1s/step - loss: 0.4337 - acc: 0.8484 - val_loss: 0.6431 - val_acc: 0.7844\n",
      "Epoch 6/20\n",
      "126/126 [==============================] - 148s 1s/step - loss: 0.3747 - acc: 0.8647 - val_loss: 0.5480 - val_acc: 0.8326\n",
      "Epoch 7/20\n",
      "126/126 [==============================] - 148s 1s/step - loss: 0.3477 - acc: 0.8775 - val_loss: 0.5732 - val_acc: 0.8246\n",
      "Epoch 8/20\n",
      "126/126 [==============================] - 148s 1s/step - loss: 0.2910 - acc: 0.8934 - val_loss: 0.5575 - val_acc: 0.8237\n",
      "Epoch 9/20\n",
      "126/126 [==============================] - 148s 1s/step - loss: 0.2719 - acc: 0.9013 - val_loss: 0.5548 - val_acc: 0.8152\n",
      "\n",
      "Epoch 00009: ReduceLROnPlateau reducing learning rate to 4.999999873689376e-05.\n",
      "Epoch 10/20\n",
      "126/126 [==============================] - 148s 1s/step - loss: 0.2089 - acc: 0.9257 - val_loss: 0.4309 - val_acc: 0.8705\n",
      "Epoch 11/20\n",
      "126/126 [==============================] - 148s 1s/step - loss: 0.1761 - acc: 0.9386 - val_loss: 0.5424 - val_acc: 0.8649\n",
      "Epoch 12/20\n",
      "126/126 [==============================] - 148s 1s/step - loss: 0.1501 - acc: 0.9480 - val_loss: 0.5050 - val_acc: 0.8460\n",
      "Epoch 13/20\n",
      "126/126 [==============================] - 147s 1s/step - loss: 0.1335 - acc: 0.9509 - val_loss: 0.6281 - val_acc: 0.8270\n",
      "\n",
      "Epoch 00013: ReduceLROnPlateau reducing learning rate to 2.499999936844688e-05.\n",
      "Epoch 14/20\n",
      "126/126 [==============================] - 147s 1s/step - loss: 0.1231 - acc: 0.9565 - val_loss: 0.4763 - val_acc: 0.8728\n",
      "Epoch 15/20\n",
      "126/126 [==============================] - 147s 1s/step - loss: 0.0964 - acc: 0.9666 - val_loss: 0.5849 - val_acc: 0.8578\n",
      "Epoch 16/20\n",
      "126/126 [==============================] - 147s 1s/step - loss: 0.0885 - acc: 0.9705 - val_loss: 0.5964 - val_acc: 0.8326\n",
      "Epoch 17/20\n",
      "126/126 [==============================] - 147s 1s/step - loss: 0.0818 - acc: 0.9716 - val_loss: 0.5651 - val_acc: 0.8697\n",
      "\n",
      "Epoch 00017: ReduceLROnPlateau reducing learning rate to 1.249999968422344e-05.\n",
      "Epoch 18/20\n",
      "126/126 [==============================] - 147s 1s/step - loss: 0.0761 - acc: 0.9743 - val_loss: 0.5558 - val_acc: 0.8661\n",
      "Epoch 19/20\n",
      "126/126 [==============================] - 147s 1s/step - loss: 0.0737 - acc: 0.9740 - val_loss: 0.4439 - val_acc: 0.8791\n",
      "Epoch 20/20\n",
      "126/126 [==============================] - 147s 1s/step - loss: 0.0607 - acc: 0.9794 - val_loss: 0.5579 - val_acc: 0.8527\n"
     ]
    }
   ],
   "source": [
    "batch_size = 64\n",
    "epochs = 20\n",
    "history = model.fit_generator(train_datagen.flow(X_train,y_train, batch_size=batch_size),\n",
    "                              epochs = epochs, validation_data = val_datagen.flow(X_val, y_val),\n",
    "                              verbose = 1, steps_per_epoch=(X_train.shape[0] // batch_size),\n",
    "                              validation_steps=(X_val.shape[0] // batch_size),\n",
    "                              callbacks=[learning_rate_reduction])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "902/902 [==============================] - 5s 6ms/step\n",
      "Validation: accuracy = 0.869180  ;  loss_v = 0.517105\n"
     ]
    }
   ],
   "source": [
    "loss_val, acc_val = model.evaluate(X_val, y_val, verbose=1)\n",
    "print(\"Validation: accuracy = %f  ;  loss_v = %f\" % (acc_val, loss_val))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Even though this model overfits the training data, we also observe some significant improvement with the validation accuracy. Our final validation accuracy is 86.9%, a nearly 10% improvement from the baseline model, which justifies some more training time. We can also see that this model is extremely \"sensitive\", a small change in learning rate can can change the model by a whole lot. Future work on choosing learning rate as well as monitor learning rate is needed for further improvement. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Testing\n",
    "\n",
    "Let's load in the intact test set and test our model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_test = np.load(\"/floyd/input/skin_cancer_192_256/256_192_test.npy\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_test = np.load(\"/floyd/input/skin_cancer_192_256/test_labels.npy\")\n",
    "y_test = to_categorical(y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1002/1002 [==============================] - 6s 6ms/step\n",
      "Test: accuracy = 0.868263  ;  loss = 0.624153\n"
     ]
    }
   ],
   "source": [
    "loss_test, acc_test = model.evaluate(X_test, y_test, verbose=1)\n",
    "print(\"Test: accuracy = %f  ;  loss = %f\" % (acc_test, loss_test))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Achieving test accuracy of 86.8% after 20 training epochs is a good result! This experiment proved that the architecture and the weights of Inception trained on ImageNet help learning for a complete different domain dataset. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.save(\"InceptionV3.h5\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,'Training and validation loss')"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Retrieve a list of accuracy results on training and test data\n",
    "# sets for each training epoch\n",
    "acc = history.history['acc']\n",
    "val_acc = history.history['val_acc']\n",
    "\n",
    "# Retrieve a list of list results on training and test data\n",
    "# sets for each training epoch\n",
    "loss = history.history['loss']\n",
    "val_loss = history.history['val_loss']\n",
    "\n",
    "# Get number of epochs\n",
    "epochs = range(len(acc))\n",
    "\n",
    "# Plot training and validation accuracy per epoch\n",
    "plt.plot(epochs, acc, label = \"training\")\n",
    "plt.plot(epochs, val_acc, label = \"validation\")\n",
    "plt.legend(loc=\"upper left\")\n",
    "plt.title('Training and validation accuracy')\n",
    "\n",
    "plt.figure()\n",
    "\n",
    "# Plot training and validation loss per epoch\n",
    "plt.plot(epochs, loss, label = \"training\")\n",
    "plt.plot(epochs, val_loss, label = \"validation\")\n",
    "plt.legend(loc=\"upper right\")\n",
    "plt.title('Training and validation loss')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}