homework/Day_019_HW.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 『本次練習內容』\n",
    "#### 學習如何搭建Inception Block"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 『本次練習目的』\n",
    "  #### 了解Inceotion原理\n",
    "  #### 了解如何導入Inception block到原本架構中"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![Incpeiton](Inception架構.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-13T09:09:38.522031Z",
     "start_time": "2020-01-13T09:09:31.851931Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "'''\n",
    "import numpy as np\n",
    "from keras.models import Model\n",
    "from keras.layers import Flatten\n",
    "from keras.layers import Dense\n",
    "from keras.layers import Input\n",
    "from keras.layers import Conv2D\n",
    "from keras.layers import MaxPooling2D\n",
    "from keras.layers import GlobalMaxPooling2D\n",
    "from keras.layers import GlobalAveragePooling2D\n",
    "from keras import backend as K\n",
    "from keras import layers\n",
    "from keras.layers import BatchNormalization\n",
    "from keras.layers import Activation\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-13T09:12:19.204502Z",
     "start_time": "2020-01-13T09:12:19.195840Z"
    }
   },
   "outputs": [],
   "source": [
    "# use tensorflow 2.0\n",
    "import numpy as np\n",
    "from tensorflow.keras.models import Model\n",
    "from tensorflow.keras.layers import Flatten\n",
    "from tensorflow.keras.layers import Dense\n",
    "from tensorflow.keras.layers import Input\n",
    "from tensorflow.keras.layers import Conv2D\n",
    "from tensorflow.keras.layers import MaxPooling2D\n",
    "from tensorflow.keras.layers import GlobalMaxPooling2D\n",
    "from tensorflow.keras.layers import GlobalAveragePooling2D\n",
    "from tensorflow.keras import backend as K\n",
    "from tensorflow.keras import layers\n",
    "from tensorflow.keras.layers import BatchNormalization\n",
    "from tensorflow.keras.layers import Activation\n",
    "import tensorflow as tf"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 導入InceptionV2-有BatchNormalization的Convolution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-13T09:12:03.216285Z",
     "start_time": "2020-01-13T09:12:03.206118Z"
    }
   },
   "outputs": [],
   "source": [
    "def Conv2d_bn(x,filters,kernel_size,padding = 'same',strides = (1, 1),normalizer=True,activation = 'relu',name = None):\n",
    "    if name is not None:\n",
    "        conv_name = name + '_conv'\n",
    "        bn_name = name + '_bn'\n",
    "        act_name = name + '_act'\n",
    "    else:\n",
    "        conv_name = None\n",
    "        bn_name = None\n",
    "        act_name = None\n",
    "    if K.image_data_format() == 'channels_first':\n",
    "        bn_axis = 1\n",
    "    else:\n",
    "        bn_axis = 3\n",
    "    x = Conv2D(\n",
    "            filters, kernel_size,\n",
    "            strides=strides, padding=padding,\n",
    "            use_bias=False, name=conv_name)(x)\n",
    "    if normalizer:\n",
    "        x = BatchNormalization(axis = bn_axis, scale = False, name = bn_name)(x)\n",
    "    if activation:\n",
    "        x = Activation(activation, name = act_name)(x)\n",
    "    return x"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 參考上圖搭建 InceptionV1_block"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-13T09:12:04.038716Z",
     "start_time": "2020-01-13T09:12:04.027359Z"
    }
   },
   "outputs": [],
   "source": [
    "def InceptionV1_block(x, specs,channel_axis, name):\n",
    "    (br0, br1, br2, br3) = specs   # ((64,), (96,128), (16,32), (32,))\n",
    "    branch_0 = Conv2d_bn(x, br0[0], (1, 1), name = name + \"_Branch_0\")\n",
    "\n",
    "    branch_1 = Conv2d_bn(x, br1[0], (1, 1), name = name + \"_Branch_1\")\n",
    "    branch_1 = Conv2d_bn(branch_1, br1[1], (3, 3), name = name + \"_Branch_1_1\")\n",
    "\n",
    "    '''Branch_2'''\n",
    "    branch_2 = Conv2d_bn(x, br2[0], (1, 1), name = name + \"_Branch_2\")\n",
    "    branch_2 = Conv2d_bn(branch_2, br2[1], (5, 5), name = name + \"_Branch_2_1\")\n",
    "\n",
    "    '''Branch_3'''\n",
    "    branch_3 = MaxPooling2D(pool_size = (3,3), strides = (1,1), padding = 'same', name = name + \"_Branch_3\")(x)\n",
    "    branch_3 = Conv2d_bn(branch_3, br3[0], (1, 1), name = name + \"_Branch_3_1\")\n",
    "\n",
    "\n",
    "    x = layers.concatenate(\n",
    "        [branch_0, branch_1, branch_2, branch_3],\n",
    "        axis = channel_axis,\n",
    "        name = name + \"_Concatenated\")\n",
    "    return x"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 測試"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-13T09:12:24.243852Z",
     "start_time": "2020-01-13T09:12:23.806631Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tensor(\"Block_1_Concatenated/Identity:0\", shape=(None, 224, 224, 256), dtype=float32)\n"
     ]
    }
   ],
   "source": [
    "img_input = Input(shape = (224,224,1))\n",
    "x=InceptionV1_block(img_input, ((64,), (96,128), (16,32), (32,)), 3, 'Block_1')\n",
    "print(x)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 將 InceptionV1_block中n*n卷積改為1 x n+n x 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-13T09:13:40.508970Z",
     "start_time": "2020-01-13T09:13:40.488143Z"
    }
   },
   "outputs": [],
   "source": [
    "def InceptionV3_block(x, specs,channel_axis, name):\n",
    "    (br0, br1, br2, br3) = specs   # ((64,), (96,128), (16,32), (32,))\n",
    "    branch_0 = Conv2d_bn(x, br0[0], (1, 1), name = name + \"_Branch_0\")\n",
    "\n",
    "    branch_1 = Conv2d_bn(x, br1[0], (1, 1), name = name + \"_Branch_1\")\n",
    "    branch_1 = Conv2d_bn(branch_1, br1[1], (1, 3), name = name + \"_Branch_1_1\")\n",
    "    branch_1 = Conv2d_bn(branch_1, br1[1], (3, 1), name = name + \"_Branch_1_2\")\n",
    "\n",
    "    '''Branch_2'''\n",
    "    branch_2 = Conv2d_bn(x, br2[0], (1, 1), name=name + \"_Branch_2\")\n",
    "    branch_2 = Conv2d_bn(branch_2, br2[1], (1, 5), name = name + \"_Branch_2_1\")\n",
    "    branch_2 = Conv2d_bn(branch_2, br2[1], (5, 1), name = name + \"_Branch_2_2\")\n",
    "\n",
    "    '''Branch_3'''\n",
    "    branch_3 = MaxPooling2D((3, 3), strides = (1, 1), padding = 'same', name = name + \"Branch_3_pool\")(x)\n",
    "    branch_3 = Conv2d_bn(branch_3, br3[0], (1, 1), name = name + \"_Branch_3_1\")\n",
    "\n",
    "    x = layers.concatenate(\n",
    "        [branch_0, branch_1, branch_2, branch_3],\n",
    "        axis = channel_axis,\n",
    "        name = name + \"_Concatenated\")\n",
    "    return x"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 測試"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-01-13T09:13:43.130840Z",
     "start_time": "2020-01-13T09:13:42.702853Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tensor(\"Block_1_Concatenated_1/Identity:0\", shape=(None, 224, 224, 256), dtype=float32)\n"
     ]
    }
   ],
   "source": [
    "img_input = Input(shape=(224,224,1))\n",
    "x=InceptionV3_block(img_input, ((64,), (96,128), (16,32), (32,)), 3, 'Block_1')\n",
    "print(x)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 額外練習"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 將VGG16 Block_3中的Convolution全部改為InceptionV1_block\n",
    "## Block_5中的Convolution全部改為InceptionV3_block\n",
    "## 並將所有Convolution改為Conv2d_bn"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 原vgg16架構"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "def VGG16(include_top=True,input_tensor=None, input_shape=(224,224,1),\n",
    "          pooling='max',classes=1000):\n",
    " \n",
    "    img_input = Input(shape=input_shape)\n",
    "\n",
    "    x = Conv2D(64, (3, 3), activation='relu', padding='same', name='block1_conv1')(img_input)\n",
    "    x = Conv2D(64, (3, 3), activation='relu', padding='same', name='block1_conv2')(x)\n",
    "    x = MaxPooling2D((2, 2), strides=(2, 2), name='block1_pool')(x)\n",
    "\n",
    "    # Block 2\n",
    "    x = Conv2D(128, (3, 3), activation='relu', padding='same', name='block2_conv1')(x)\n",
    "    x = Conv2D(128, (3, 3), activation='relu', padding='same', name='block2_conv2')(x)\n",
    "    x = MaxPooling2D((2, 2), strides=(2, 2), name='block2_pool')(x)\n",
    "\n",
    "    # Block 3\n",
    "    x = Conv2D(256, (3, 3), activation='relu', padding='same', name='block3_conv1')(x)\n",
    "    x = Conv2D(256, (3, 3), activation='relu', padding='same', name='block3_conv2')(x)\n",
    "    x = Conv2D(256, (3, 3), activation='relu', padding='same', name='block3_conv3')(x)\n",
    "    x = MaxPooling2D((2, 2), strides=(2, 2), name='block3_pool')(x)\n",
    "\n",
    "    # Block 4\n",
    "    x = Conv2D(512, (3, 3), activation='relu', padding='same', name='block4_conv1')(x)\n",
    "    x = Conv2D(512, (3, 3), activation='relu', padding='same', name='block4_conv2')(x)\n",
    "    x = Conv2D(512, (3, 3), activation='relu', padding='same', name='block4_conv3')(x)\n",
    "    x = MaxPooling2D((2, 2), strides=(2, 2), name='block4_pool')(x)\n",
    "\n",
    "    # Block 5\n",
    "    x = Conv2D(512, (3, 3), activation='relu', padding='same', name='block5_conv1')(x)\n",
    "    x = Conv2D(512, (3, 3), activation='relu', padding='same', name='block5_conv2')(x)\n",
    "    x = Conv2D(512, (3, 3), activation='relu', padding='same', name='block5_conv3')(x)\n",
    "    x = MaxPooling2D((2, 2), strides=(2, 2), name='block5_pool')(x)\n",
    "\n",
    "    if include_top:\n",
    "        # Classification block\n",
    "        x = Flatten(name='flatten')(x)\n",
    "        x = Dense(4096, activation='relu', name='fc1')(x)\n",
    "        x = Dense(4096, activation='relu', name='fc2')(x)\n",
    "        x = Dense(classes, activation='softmax', name='predictions')(x)\n",
    "    else:\n",
    "        if pooling == 'avg':\n",
    "            x = GlobalAveragePooling2D()(x)\n",
    "        elif pooling == 'max':\n",
    "            x = GlobalMaxPooling2D()(x)\n",
    "\n",
    "    inputs = img_input\n",
    "    # Create model.\n",
    "    model = Model(inputs, x, name='vgg16')\n",
    "\n",
    "   \n",
    "    return model\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 修改後"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def VGG16_Inception(include_top=True,input_tensor=None, input_shape=(224,224,1),\n",
    "          pooling='max',classes=1000):\n",
    " \n",
    "    '''修改模型'''\n",
    "   \n",
    "    return model\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = VGG16_Inception(include_top=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_19 (InputLayer)           (None, 224, 224, 1)  0                                            \n",
      "__________________________________________________________________________________________________\n",
      "block1_conv1_conv (Conv2D)      (None, 224, 224, 64) 576         input_19[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "block1_conv1_bn (BatchNormaliza (None, 224, 224, 64) 192         block1_conv1_conv[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "block1_conv1_act (Activation)   (None, 224, 224, 64) 0           block1_conv1_bn[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block1_conv2_conv (Conv2D)      (None, 224, 224, 64) 36864       block1_conv1_act[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "block1_conv2_bn (BatchNormaliza (None, 224, 224, 64) 192         block1_conv2_conv[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "block1_conv2_act (Activation)   (None, 224, 224, 64) 0           block1_conv2_bn[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block1_pool (MaxPooling2D)      (None, 112, 112, 64) 0           block1_conv2_act[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "block2_conv1_conv (Conv2D)      (None, 112, 112, 128 73728       block1_pool[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "block2_conv1_bn (BatchNormaliza (None, 112, 112, 128 384         block2_conv1_conv[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "block2_conv1_act (Activation)   (None, 112, 112, 128 0           block2_conv1_bn[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block2_conv2_conv (Conv2D)      (None, 112, 112, 128 147456      block2_conv1_act[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "block2_conv2_bn (BatchNormaliza (None, 112, 112, 128 384         block2_conv2_conv[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "block2_conv2_act (Activation)   (None, 112, 112, 128 0           block2_conv2_bn[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block2_pool (MaxPooling2D)      (None, 56, 56, 128)  0           block2_conv2_act[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "Block_1_Branch_1_conv (Conv2D)  (None, 56, 56, 96)   12288       block2_pool[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "Block_1_Branch_2_conv (Conv2D)  (None, 56, 56, 16)   2048        block2_pool[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "Block_1_Branch_1_bn (BatchNorma (None, 56, 56, 96)   288         Block_1_Branch_1_conv[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_1_Branch_2_bn (BatchNorma (None, 56, 56, 16)   48          Block_1_Branch_2_conv[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_1_Branch_1_act (Activatio (None, 56, 56, 96)   0           Block_1_Branch_1_bn[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "Block_1_Branch_2_act (Activatio (None, 56, 56, 16)   0           Block_1_Branch_2_bn[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "Block_1_Branch_3 (MaxPooling2D) (None, 56, 56, 128)  0           block2_pool[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "Block_1_Branch_0_conv (Conv2D)  (None, 56, 56, 64)   8192        block2_pool[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "Block_1_Branch_1_1_conv (Conv2D (None, 56, 56, 128)  110592      Block_1_Branch_1_act[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "Block_1_Branch_2_1_conv (Conv2D (None, 56, 56, 32)   4608        Block_1_Branch_2_act[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "Block_1_Branch_3_1_conv (Conv2D (None, 56, 56, 32)   4096        Block_1_Branch_3[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "Block_1_Branch_0_bn (BatchNorma (None, 56, 56, 64)   192         Block_1_Branch_0_conv[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_1_Branch_1_1_bn (BatchNor (None, 56, 56, 128)  384         Block_1_Branch_1_1_conv[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "Block_1_Branch_2_1_bn (BatchNor (None, 56, 56, 32)   96          Block_1_Branch_2_1_conv[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "Block_1_Branch_3_1_bn (BatchNor (None, 56, 56, 32)   96          Block_1_Branch_3_1_conv[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "Block_1_Branch_0_act (Activatio (None, 56, 56, 64)   0           Block_1_Branch_0_bn[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "Block_1_Branch_1_1_act (Activat (None, 56, 56, 128)  0           Block_1_Branch_1_1_bn[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_1_Branch_2_1_act (Activat (None, 56, 56, 32)   0           Block_1_Branch_2_1_bn[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_1_Branch_3_1_act (Activat (None, 56, 56, 32)   0           Block_1_Branch_3_1_bn[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_1_Concatenated (Concatena (None, 56, 56, 256)  0           Block_1_Branch_0_act[0][0]       \n",
      "                                                                 Block_1_Branch_1_1_act[0][0]     \n",
      "                                                                 Block_1_Branch_2_1_act[0][0]     \n",
      "                                                                 Block_1_Branch_3_1_act[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "Block_2_Branch_1_conv (Conv2D)  (None, 56, 56, 96)   24576       Block_1_Concatenated[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "Block_2_Branch_2_conv (Conv2D)  (None, 56, 56, 16)   4096        Block_1_Concatenated[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "Block_2_Branch_1_bn (BatchNorma (None, 56, 56, 96)   288         Block_2_Branch_1_conv[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_2_Branch_2_bn (BatchNorma (None, 56, 56, 16)   48          Block_2_Branch_2_conv[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_2_Branch_1_act (Activatio (None, 56, 56, 96)   0           Block_2_Branch_1_bn[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "Block_2_Branch_2_act (Activatio (None, 56, 56, 16)   0           Block_2_Branch_2_bn[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "Block_2_Branch_3 (MaxPooling2D) (None, 56, 56, 256)  0           Block_1_Concatenated[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "Block_2_Branch_0_conv (Conv2D)  (None, 56, 56, 64)   16384       Block_1_Concatenated[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "Block_2_Branch_1_1_conv (Conv2D (None, 56, 56, 128)  110592      Block_2_Branch_1_act[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "Block_2_Branch_2_1_conv (Conv2D (None, 56, 56, 32)   4608        Block_2_Branch_2_act[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "Block_2_Branch_3_1_conv (Conv2D (None, 56, 56, 32)   8192        Block_2_Branch_3[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "Block_2_Branch_0_bn (BatchNorma (None, 56, 56, 64)   192         Block_2_Branch_0_conv[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_2_Branch_1_1_bn (BatchNor (None, 56, 56, 128)  384         Block_2_Branch_1_1_conv[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "Block_2_Branch_2_1_bn (BatchNor (None, 56, 56, 32)   96          Block_2_Branch_2_1_conv[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "Block_2_Branch_3_1_bn (BatchNor (None, 56, 56, 32)   96          Block_2_Branch_3_1_conv[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "Block_2_Branch_0_act (Activatio (None, 56, 56, 64)   0           Block_2_Branch_0_bn[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "Block_2_Branch_1_1_act (Activat (None, 56, 56, 128)  0           Block_2_Branch_1_1_bn[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_2_Branch_2_1_act (Activat (None, 56, 56, 32)   0           Block_2_Branch_2_1_bn[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_2_Branch_3_1_act (Activat (None, 56, 56, 32)   0           Block_2_Branch_3_1_bn[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_2_Concatenated (Concatena (None, 56, 56, 256)  0           Block_2_Branch_0_act[0][0]       \n",
      "                                                                 Block_2_Branch_1_1_act[0][0]     \n",
      "                                                                 Block_2_Branch_2_1_act[0][0]     \n",
      "                                                                 Block_2_Branch_3_1_act[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "Block_3_Branch_1_conv (Conv2D)  (None, 56, 56, 96)   24576       Block_2_Concatenated[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "Block_3_Branch_2_conv (Conv2D)  (None, 56, 56, 16)   4096        Block_2_Concatenated[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "Block_3_Branch_1_bn (BatchNorma (None, 56, 56, 96)   288         Block_3_Branch_1_conv[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_3_Branch_2_bn (BatchNorma (None, 56, 56, 16)   48          Block_3_Branch_2_conv[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_3_Branch_1_act (Activatio (None, 56, 56, 96)   0           Block_3_Branch_1_bn[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "Block_3_Branch_2_act (Activatio (None, 56, 56, 16)   0           Block_3_Branch_2_bn[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "Block_3_Branch_3 (MaxPooling2D) (None, 56, 56, 256)  0           Block_2_Concatenated[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "Block_3_Branch_0_conv (Conv2D)  (None, 56, 56, 64)   16384       Block_2_Concatenated[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "Block_3_Branch_1_1_conv (Conv2D (None, 56, 56, 128)  110592      Block_3_Branch_1_act[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "Block_3_Branch_2_1_conv (Conv2D (None, 56, 56, 32)   4608        Block_3_Branch_2_act[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "Block_3_Branch_3_1_conv (Conv2D (None, 56, 56, 32)   8192        Block_3_Branch_3[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "Block_3_Branch_0_bn (BatchNorma (None, 56, 56, 64)   192         Block_3_Branch_0_conv[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_3_Branch_1_1_bn (BatchNor (None, 56, 56, 128)  384         Block_3_Branch_1_1_conv[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "Block_3_Branch_2_1_bn (BatchNor (None, 56, 56, 32)   96          Block_3_Branch_2_1_conv[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "Block_3_Branch_3_1_bn (BatchNor (None, 56, 56, 32)   96          Block_3_Branch_3_1_conv[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "Block_3_Branch_0_act (Activatio (None, 56, 56, 64)   0           Block_3_Branch_0_bn[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "Block_3_Branch_1_1_act (Activat (None, 56, 56, 128)  0           Block_3_Branch_1_1_bn[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_3_Branch_2_1_act (Activat (None, 56, 56, 32)   0           Block_3_Branch_2_1_bn[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_3_Branch_3_1_act (Activat (None, 56, 56, 32)   0           Block_3_Branch_3_1_bn[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_3_Concatenated (Concatena (None, 56, 56, 256)  0           Block_3_Branch_0_act[0][0]       \n",
      "                                                                 Block_3_Branch_1_1_act[0][0]     \n",
      "                                                                 Block_3_Branch_2_1_act[0][0]     \n",
      "                                                                 Block_3_Branch_3_1_act[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "block3_pool (MaxPooling2D)      (None, 28, 28, 256)  0           Block_3_Concatenated[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "block4_conv1_conv (Conv2D)      (None, 28, 28, 512)  1179648     block3_pool[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "block4_conv1_bn (BatchNormaliza (None, 28, 28, 512)  1536        block4_conv1_conv[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "block4_conv1_act (Activation)   (None, 28, 28, 512)  0           block4_conv1_bn[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block4_conv2_conv (Conv2D)      (None, 28, 28, 512)  2359296     block4_conv1_act[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "block4_conv2_bn (BatchNormaliza (None, 28, 28, 512)  1536        block4_conv2_conv[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "block4_conv2_act (Activation)   (None, 28, 28, 512)  0           block4_conv2_bn[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block4_conv3_conv (Conv2D)      (None, 28, 28, 512)  2359296     block4_conv2_act[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "block4_conv3_bn (BatchNormaliza (None, 28, 28, 512)  1536        block4_conv3_conv[0][0]          \n",
      "__________________________________________________________________________________________________\n",
      "block4_conv3_act (Activation)   (None, 28, 28, 512)  0           block4_conv3_bn[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block4_pool (MaxPooling2D)      (None, 14, 14, 512)  0           block4_conv3_act[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "Block_4_Branch_1_conv (Conv2D)  (None, 14, 14, 192)  98304       block4_pool[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "Block_4_Branch_2_conv (Conv2D)  (None, 14, 14, 32)   16384       block4_pool[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "Block_4_Branch_1_bn (BatchNorma (None, 14, 14, 192)  576         Block_4_Branch_1_conv[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_4_Branch_2_bn (BatchNorma (None, 14, 14, 32)   96          Block_4_Branch_2_conv[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_4_Branch_1_act (Activatio (None, 14, 14, 192)  0           Block_4_Branch_1_bn[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "Block_4_Branch_2_act (Activatio (None, 14, 14, 32)   0           Block_4_Branch_2_bn[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "Block_4_Branch_1_1_conv (Conv2D (None, 14, 14, 256)  147456      Block_4_Branch_1_act[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "Block_4_Branch_2_1_conv (Conv2D (None, 14, 14, 64)   6144        Block_4_Branch_2_act[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "Block_4_Branch_1_1_bn (BatchNor (None, 14, 14, 256)  768         Block_4_Branch_1_1_conv[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "Block_4_Branch_2_1_bn (BatchNor (None, 14, 14, 64)   192         Block_4_Branch_2_1_conv[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "Block_4_Branch_1_1_act (Activat (None, 14, 14, 256)  0           Block_4_Branch_1_1_bn[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_4_Branch_2_1_act (Activat (None, 14, 14, 64)   0           Block_4_Branch_2_1_bn[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_4_Branch_3 (MaxPooling2D) (None, 14, 14, 512)  0           block4_pool[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "Block_4_Branch_0_conv (Conv2D)  (None, 14, 14, 128)  65536       block4_pool[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "Block_4_Branch_1_2_conv (Conv2D (None, 14, 14, 256)  196608      Block_4_Branch_1_1_act[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "Block_4_Branch_2_2_conv (Conv2D (None, 14, 14, 64)   12288       Block_4_Branch_2_1_act[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "Block_4_Branch_3_1_conv (Conv2D (None, 14, 14, 64)   32768       Block_4_Branch_3[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "Block_4_Branch_0_bn (BatchNorma (None, 14, 14, 128)  384         Block_4_Branch_0_conv[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_4_Branch_1_2_bn (BatchNor (None, 14, 14, 256)  768         Block_4_Branch_1_2_conv[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "Block_4_Branch_2_2_bn (BatchNor (None, 14, 14, 64)   192         Block_4_Branch_2_2_conv[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "Block_4_Branch_3_1_bn (BatchNor (None, 14, 14, 64)   192         Block_4_Branch_3_1_conv[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "Block_4_Branch_0_act (Activatio (None, 14, 14, 128)  0           Block_4_Branch_0_bn[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "Block_4_Branch_1_2_act (Activat (None, 14, 14, 256)  0           Block_4_Branch_1_2_bn[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_4_Branch_2_2_act (Activat (None, 14, 14, 64)   0           Block_4_Branch_2_2_bn[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_4_Branch_3_1_act (Activat (None, 14, 14, 64)   0           Block_4_Branch_3_1_bn[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_4_Concatenated (Concatena (None, 14, 14, 512)  0           Block_4_Branch_0_act[0][0]       \n",
      "                                                                 Block_4_Branch_1_2_act[0][0]     \n",
      "                                                                 Block_4_Branch_2_2_act[0][0]     \n",
      "                                                                 Block_4_Branch_3_1_act[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "Block_5_Branch_1_conv (Conv2D)  (None, 14, 14, 192)  98304       Block_4_Concatenated[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "Block_5_Branch_2_conv (Conv2D)  (None, 14, 14, 32)   16384       Block_4_Concatenated[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "Block_5_Branch_1_bn (BatchNorma (None, 14, 14, 192)  576         Block_5_Branch_1_conv[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_5_Branch_2_bn (BatchNorma (None, 14, 14, 32)   96          Block_5_Branch_2_conv[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_5_Branch_1_act (Activatio (None, 14, 14, 192)  0           Block_5_Branch_1_bn[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "Block_5_Branch_2_act (Activatio (None, 14, 14, 32)   0           Block_5_Branch_2_bn[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "Block_5_Branch_1_1_conv (Conv2D (None, 14, 14, 256)  147456      Block_5_Branch_1_act[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "Block_5_Branch_2_1_conv (Conv2D (None, 14, 14, 64)   6144        Block_5_Branch_2_act[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "Block_5_Branch_1_1_bn (BatchNor (None, 14, 14, 256)  768         Block_5_Branch_1_1_conv[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "Block_5_Branch_2_1_bn (BatchNor (None, 14, 14, 64)   192         Block_5_Branch_2_1_conv[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "Block_5_Branch_1_1_act (Activat (None, 14, 14, 256)  0           Block_5_Branch_1_1_bn[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_5_Branch_2_1_act (Activat (None, 14, 14, 64)   0           Block_5_Branch_2_1_bn[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_5_Branch_3 (MaxPooling2D) (None, 14, 14, 512)  0           Block_4_Concatenated[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "Block_5_Branch_0_conv (Conv2D)  (None, 14, 14, 128)  65536       Block_4_Concatenated[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "Block_5_Branch_1_2_conv (Conv2D (None, 14, 14, 256)  196608      Block_5_Branch_1_1_act[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "Block_5_Branch_2_2_conv (Conv2D (None, 14, 14, 64)   12288       Block_5_Branch_2_1_act[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "Block_5_Branch_3_1_conv (Conv2D (None, 14, 14, 64)   32768       Block_5_Branch_3[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "Block_5_Branch_0_bn (BatchNorma (None, 14, 14, 128)  384         Block_5_Branch_0_conv[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_5_Branch_1_2_bn (BatchNor (None, 14, 14, 256)  768         Block_5_Branch_1_2_conv[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "Block_5_Branch_2_2_bn (BatchNor (None, 14, 14, 64)   192         Block_5_Branch_2_2_conv[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "Block_5_Branch_3_1_bn (BatchNor (None, 14, 14, 64)   192         Block_5_Branch_3_1_conv[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "Block_5_Branch_0_act (Activatio (None, 14, 14, 128)  0           Block_5_Branch_0_bn[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "Block_5_Branch_1_2_act (Activat (None, 14, 14, 256)  0           Block_5_Branch_1_2_bn[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_5_Branch_2_2_act (Activat (None, 14, 14, 64)   0           Block_5_Branch_2_2_bn[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_5_Branch_3_1_act (Activat (None, 14, 14, 64)   0           Block_5_Branch_3_1_bn[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_5_Concatenated (Concatena (None, 14, 14, 512)  0           Block_5_Branch_0_act[0][0]       \n",
      "                                                                 Block_5_Branch_1_2_act[0][0]     \n",
      "                                                                 Block_5_Branch_2_2_act[0][0]     \n",
      "                                                                 Block_5_Branch_3_1_act[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "Block_6_Branch_1_conv (Conv2D)  (None, 14, 14, 192)  98304       Block_5_Concatenated[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "Block_6_Branch_2_conv (Conv2D)  (None, 14, 14, 32)   16384       Block_5_Concatenated[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "Block_6_Branch_1_bn (BatchNorma (None, 14, 14, 192)  576         Block_6_Branch_1_conv[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_6_Branch_2_bn (BatchNorma (None, 14, 14, 32)   96          Block_6_Branch_2_conv[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_6_Branch_1_act (Activatio (None, 14, 14, 192)  0           Block_6_Branch_1_bn[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "Block_6_Branch_2_act (Activatio (None, 14, 14, 32)   0           Block_6_Branch_2_bn[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "Block_6_Branch_1_1_conv (Conv2D (None, 14, 14, 256)  147456      Block_6_Branch_1_act[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "Block_6_Branch_2_1_conv (Conv2D (None, 14, 14, 64)   6144        Block_6_Branch_2_act[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "Block_6_Branch_1_1_bn (BatchNor (None, 14, 14, 256)  768         Block_6_Branch_1_1_conv[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "Block_6_Branch_2_1_bn (BatchNor (None, 14, 14, 64)   192         Block_6_Branch_2_1_conv[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "Block_6_Branch_1_1_act (Activat (None, 14, 14, 256)  0           Block_6_Branch_1_1_bn[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_6_Branch_2_1_act (Activat (None, 14, 14, 64)   0           Block_6_Branch_2_1_bn[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_6_Branch_3 (MaxPooling2D) (None, 14, 14, 512)  0           Block_5_Concatenated[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "Block_6_Branch_0_conv (Conv2D)  (None, 14, 14, 128)  65536       Block_5_Concatenated[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "Block_6_Branch_1_2_conv (Conv2D (None, 14, 14, 256)  196608      Block_6_Branch_1_1_act[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "Block_6_Branch_2_2_conv (Conv2D (None, 14, 14, 64)   12288       Block_6_Branch_2_1_act[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "Block_6_Branch_3_1_conv (Conv2D (None, 14, 14, 64)   32768       Block_6_Branch_3[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "Block_6_Branch_0_bn (BatchNorma (None, 14, 14, 128)  384         Block_6_Branch_0_conv[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_6_Branch_1_2_bn (BatchNor (None, 14, 14, 256)  768         Block_6_Branch_1_2_conv[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "Block_6_Branch_2_2_bn (BatchNor (None, 14, 14, 64)   192         Block_6_Branch_2_2_conv[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "Block_6_Branch_3_1_bn (BatchNor (None, 14, 14, 64)   192         Block_6_Branch_3_1_conv[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "Block_6_Branch_0_act (Activatio (None, 14, 14, 128)  0           Block_6_Branch_0_bn[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "Block_6_Branch_1_2_act (Activat (None, 14, 14, 256)  0           Block_6_Branch_1_2_bn[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_6_Branch_2_2_act (Activat (None, 14, 14, 64)   0           Block_6_Branch_2_2_bn[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_6_Branch_3_1_act (Activat (None, 14, 14, 64)   0           Block_6_Branch_3_1_bn[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "Block_6_Concatenated (Concatena (None, 14, 14, 512)  0           Block_6_Branch_0_act[0][0]       \n",
      "                                                                 Block_6_Branch_1_2_act[0][0]     \n",
      "                                                                 Block_6_Branch_2_2_act[0][0]     \n",
      "                                                                 Block_6_Branch_3_1_act[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "block5_pool (MaxPooling2D)      (None, 7, 7, 512)    0           Block_6_Concatenated[0][0]       \n",
      "__________________________________________________________________________________________________\n",
      "global_max_pooling2d_6 (GlobalM (None, 512)          0           block5_pool[0][0]                \n",
      "==================================================================================================\n",
      "Total params: 8,380,624\n",
      "Trainable params: 8,368,240\n",
      "Non-trainable params: 12,384\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
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