Fine_Tuning_InceptionV3.ipynb

{
 "cells": [
  {
   "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",
    "from keras import backend as K\n",
    "\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "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": [],
   "source": [
    "pre_trained_model = InceptionV3(input_shape=(192, 256, 3), include_top=False, weights=\"imagenet\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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",
    "    if hasattr(layer, 'moving_mean') and hasattr(layer, 'moving_variance'):\n",
    "        layer.trainable = True\n",
    "        K.eval(K.update(layer.moving_mean, K.zeros_like(layer.moving_mean)))\n",
    "        K.eval(K.update(layer.moving_variance, K.zeros_like(layer.moving_variance)))\n",
    "    else:\n",
    "        layer.trainable = False\n",
    "\n",
    "print(len(pre_trained_model.layers))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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": "code",
   "execution_count": 12,
   "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 0.5\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": 13,
   "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: 1,069,895\n",
      "Non-trainable params: 21,785,568\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/3\n",
      "126/126 [==============================] - 125s 994ms/step - loss: 1.5077 - acc: 0.6045 - val_loss: 1.1479 - val_acc: 0.6496\n",
      "Epoch 2/3\n",
      "126/126 [==============================] - 109s 865ms/step - loss: 1.0800 - acc: 0.6632 - val_loss: 0.9732 - val_acc: 0.6897\n",
      "Epoch 3/3\n",
      "126/126 [==============================] - 107s 849ms/step - loss: 1.0364 - acc: 0.6674 - val_loss: 0.9118 - val_acc: 0.7014\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": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "for layer in pre_trained_model.layers[249:]:\n",
    "    layer.trainable = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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": 18,
   "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": 19,
   "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: 12,178,247\n",
      "Non-trainable params: 10,677,216\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/35\n",
      "126/126 [==============================] - 126s 998ms/step - loss: 0.9149 - acc: 0.6921 - val_loss: 0.8397 - val_acc: 0.7009\n",
      "Epoch 2/35\n",
      "126/126 [==============================] - 112s 886ms/step - loss: 0.7910 - acc: 0.7198 - val_loss: 0.7592 - val_acc: 0.7366\n",
      "Epoch 3/35\n",
      "126/126 [==============================] - 111s 882ms/step - loss: 0.7137 - acc: 0.7440 - val_loss: 0.8139 - val_acc: 0.7156\n",
      "Epoch 4/35\n",
      "126/126 [==============================] - 111s 883ms/step - loss: 0.6664 - acc: 0.7614 - val_loss: 0.6727 - val_acc: 0.7522\n",
      "Epoch 5/35\n",
      "126/126 [==============================] - 111s 882ms/step - loss: 0.6168 - acc: 0.7779 - val_loss: 0.7178 - val_acc: 0.7370\n",
      "Epoch 6/35\n",
      "126/126 [==============================] - 111s 879ms/step - loss: 0.5867 - acc: 0.7870 - val_loss: 0.7066 - val_acc: 0.7522\n",
      "Epoch 7/35\n",
      "126/126 [==============================] - 110s 877ms/step - loss: 0.5364 - acc: 0.8025 - val_loss: 0.7239 - val_acc: 0.7488\n",
      "\n",
      "Epoch 00007: ReduceLROnPlateau reducing learning rate to 4.999999873689376e-05.\n",
      "Epoch 8/35\n",
      "126/126 [==============================] - 111s 878ms/step - loss: 0.5206 - acc: 0.8136 - val_loss: 0.6172 - val_acc: 0.7812\n",
      "Epoch 9/35\n",
      "126/126 [==============================] - 110s 876ms/step - loss: 0.4848 - acc: 0.8226 - val_loss: 0.6283 - val_acc: 0.7678\n",
      "Epoch 10/35\n",
      "126/126 [==============================] - 111s 877ms/step - loss: 0.4660 - acc: 0.8291 - val_loss: 0.6477 - val_acc: 0.7634\n",
      "Epoch 11/35\n",
      "126/126 [==============================] - 110s 876ms/step - loss: 0.4631 - acc: 0.8288 - val_loss: 0.5939 - val_acc: 0.7820\n",
      "Epoch 12/35\n",
      "126/126 [==============================] - 111s 877ms/step - loss: 0.4377 - acc: 0.8429 - val_loss: 0.6533 - val_acc: 0.7768\n",
      "Epoch 13/35\n",
      "126/126 [==============================] - 110s 876ms/step - loss: 0.4127 - acc: 0.8503 - val_loss: 0.6776 - val_acc: 0.7630\n",
      "Epoch 14/35\n",
      "126/126 [==============================] - 111s 877ms/step - loss: 0.4097 - acc: 0.8502 - val_loss: 0.7174 - val_acc: 0.7433\n",
      "\n",
      "Epoch 00014: ReduceLROnPlateau reducing learning rate to 2.499999936844688e-05.\n",
      "Epoch 15/35\n",
      "126/126 [==============================] - 110s 876ms/step - loss: 0.4023 - acc: 0.8564 - val_loss: 0.6920 - val_acc: 0.7915\n",
      "Epoch 16/35\n",
      "126/126 [==============================] - 111s 877ms/step - loss: 0.3759 - acc: 0.8638 - val_loss: 0.5571 - val_acc: 0.7969\n",
      "Epoch 17/35\n",
      "126/126 [==============================] - 110s 876ms/step - loss: 0.3592 - acc: 0.8693 - val_loss: 0.6749 - val_acc: 0.7630\n",
      "Epoch 18/35\n",
      "126/126 [==============================] - 110s 877ms/step - loss: 0.3538 - acc: 0.8683 - val_loss: 0.6179 - val_acc: 0.7924\n",
      "Epoch 19/35\n",
      "126/126 [==============================] - 110s 876ms/step - loss: 0.3580 - acc: 0.8732 - val_loss: 0.5775 - val_acc: 0.8057\n",
      "Epoch 20/35\n",
      "126/126 [==============================] - 110s 877ms/step - loss: 0.3466 - acc: 0.8741 - val_loss: 0.6076 - val_acc: 0.7991\n",
      "Epoch 21/35\n",
      "126/126 [==============================] - 110s 876ms/step - loss: 0.3395 - acc: 0.8759 - val_loss: 0.6784 - val_acc: 0.7630\n",
      "Epoch 22/35\n",
      "126/126 [==============================] - 111s 877ms/step - loss: 0.3318 - acc: 0.8770 - val_loss: 0.5841 - val_acc: 0.8058\n",
      "Epoch 23/35\n",
      "126/126 [==============================] - 110s 876ms/step - loss: 0.3154 - acc: 0.8835 - val_loss: 0.7083 - val_acc: 0.7725\n",
      "Epoch 24/35\n",
      "126/126 [==============================] - 111s 877ms/step - loss: 0.3240 - acc: 0.8847 - val_loss: 0.6087 - val_acc: 0.8080\n",
      "Epoch 25/35\n",
      "126/126 [==============================] - 110s 876ms/step - loss: 0.3049 - acc: 0.8886 - val_loss: 0.7642 - val_acc: 0.7725\n",
      "Epoch 26/35\n",
      "126/126 [==============================] - 111s 877ms/step - loss: 0.3123 - acc: 0.8882 - val_loss: 0.6861 - val_acc: 0.8013\n",
      "Epoch 27/35\n",
      "126/126 [==============================] - 110s 876ms/step - loss: 0.2995 - acc: 0.8935 - val_loss: 0.6753 - val_acc: 0.7725\n",
      "\n",
      "Epoch 00027: ReduceLROnPlateau reducing learning rate to 1.249999968422344e-05.\n",
      "Epoch 28/35\n",
      "126/126 [==============================] - 110s 877ms/step - loss: 0.2937 - acc: 0.8964 - val_loss: 0.6672 - val_acc: 0.7879\n",
      "Epoch 29/35\n",
      "126/126 [==============================] - 110s 876ms/step - loss: 0.2922 - acc: 0.8899 - val_loss: 0.6256 - val_acc: 0.8057\n",
      "Epoch 30/35\n",
      "126/126 [==============================] - 111s 877ms/step - loss: 0.2844 - acc: 0.8978 - val_loss: 0.6403 - val_acc: 0.7857\n",
      "Epoch 31/35\n",
      "126/126 [==============================] - 111s 878ms/step - loss: 0.2776 - acc: 0.8971 - val_loss: 0.6824 - val_acc: 0.7924\n",
      "\n",
      "Epoch 00031: ReduceLROnPlateau reducing learning rate to 6.24999984211172e-06.\n",
      "Epoch 32/35\n",
      "126/126 [==============================] - 110s 876ms/step - loss: 0.2740 - acc: 0.9008 - val_loss: 0.6319 - val_acc: 0.7962\n",
      "Epoch 33/35\n",
      "126/126 [==============================] - 111s 877ms/step - loss: 0.2777 - acc: 0.8998 - val_loss: 0.7288 - val_acc: 0.7857\n",
      "Epoch 34/35\n",
      "126/126 [==============================] - 110s 876ms/step - loss: 0.2666 - acc: 0.9007 - val_loss: 0.6356 - val_acc: 0.8009\n",
      "Epoch 35/35\n",
      "126/126 [==============================] - 110s 877ms/step - loss: 0.2627 - acc: 0.9023 - val_loss: 0.6626 - val_acc: 0.7946\n",
      "\n",
      "Epoch 00035: ReduceLROnPlateau reducing learning rate to 3.12499992105586e-06.\n"
     ]
    }
   ],
   "source": [
    "batch_size = 64\n",
    "epochs = 35\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": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "902/902 [==============================] - 5s 6ms/step\n",
      "Validation: accuracy = 0.799335  ;  loss_v = 0.676574\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": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_test = np.load(\"/floyd/input/skin_cancer_192_256/256_192_test.npy\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1002/1002 [==============================] - 6s 6ms/step\n",
      "Test: accuracy = 0.799401  ;  loss = 0.748205\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": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.save(\"InceptionV3FT.h5\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,'Training and validation loss')"
      ]
     },
     "execution_count": 26,
     "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')"
   ]
  }
 ],
 "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
}