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@tevdoradze
Created December 1, 2019 12:45
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cnn_visualizer.ipynb
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{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "cnn_visualizer.ipynb",
"provenance": [],
"collapsed_sections": [],
"machine_shape": "hm",
"include_colab_link": true
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"accelerator": "GPU"
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/tevdoradze/862ed567c0c7c6d00f9a0f519c8fee7f/cnn_visualizer.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "4yYHsASEBZNq",
"colab_type": "text"
},
"source": [
"# Imports"
]
},
{
"cell_type": "code",
"metadata": {
"id": "oTuYZIHp8jBU",
"colab_type": "code",
"colab": {}
},
"source": [
"%tensorflow_version 2.x"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "n5-Z_a1YE2gv",
"colab_type": "code",
"outputId": "224456eb-d833-47f3-aac1-e0538587d088",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
}
},
"source": [
"%matplotlib inline\n",
"from matplotlib import pyplot as plt\n",
"import numpy as np\n",
"np.seterr(divide='ignore', invalid='ignore')\n",
"import tensorflow_datasets as tfds\n",
"import tensorflow as tf\n",
"print(tf.__version__)"
],
"execution_count": 137,
"outputs": [
{
"output_type": "stream",
"text": [
"2.0.0\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "PEab5uMZBgPB",
"colab_type": "text"
},
"source": [
"# CNN training"
]
},
{
"cell_type": "code",
"metadata": {
"id": "bjDQ7zAdGMxt",
"colab_type": "code",
"colab": {}
},
"source": [
"mnist_train, info_train = tfds.load(name=\"mnist\", split=\"train\", with_info=True, as_supervised=True)\n",
"mnist_test, info_test = tfds.load(name=\"mnist\", split=\"test\", with_info=True, as_supervised=True)\n",
"train_size = info_train.splits.get('train').num_examples\n",
"test_size = info_train.splits.get('test').num_examples"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "TtqntaOlqLUH",
"colab_type": "code",
"colab": {}
},
"source": [
"def preprocess(img,label):\n",
" img = tf.dtypes.cast(img, tf.float32) / 255.0\n",
" return img, label\n",
"mnist_train = mnist_train.map(preprocess)\n",
"mnist_test = mnist_test.map(preprocess)"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "QDqDf8glW4uI",
"colab_type": "code",
"colab": {}
},
"source": [
"shuffle_batch_size = 1024\n",
"batch_size=128"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "QUXqHCaPKDUg",
"colab_type": "code",
"colab": {}
},
"source": [
"mnist_train = mnist_train.shuffle(shuffle_batch_size).repeat().batch(batch_size)\n",
"mnist_train = mnist_train.prefetch(tf.data.experimental.AUTOTUNE)\n",
"mnist_test = mnist_test.shuffle(shuffle_batch_size).repeat().batch(batch_size)\n",
"mnist_test = mnist_test.prefetch(tf.data.experimental.AUTOTUNE)"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "o9W7eUsZJXZ_",
"colab_type": "code",
"outputId": "25a8f0f2-91e3-42c8-e56d-8fca1df5b234",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 538
}
},
"source": [
"classifier = tf.keras.Sequential()\n",
"classifier.add(tf.keras.layers.Conv2D(32, (3, 3), padding='same', input_shape=(28, 28, 1), activation = 'relu'))\n",
"classifier.add(tf.keras.layers.Conv2D(32, (3, 3), padding='same', activation = 'relu'))\n",
"classifier.add(tf.keras.layers.MaxPool2D())\n",
"classifier.add(tf.keras.layers.Dropout(0.5))\n",
"classifier.add(tf.keras.layers.Conv2D(64, (3, 3), padding='same',activation = 'relu'))\n",
"classifier.add(tf.keras.layers.Conv2D(64, (3, 3), padding='same', activation = 'relu'))\n",
"classifier.add(tf.keras.layers.MaxPool2D())\n",
"classifier.add(tf.keras.layers.Dropout(0.5))\n",
"classifier.add(tf.keras.layers.Flatten())\n",
"classifier.add(tf.keras.layers.Dense(units = 256, activation = 'relu'))\n",
"classifier.add(tf.keras.layers.Dense(units = 10, activation = 'softmax'))\n",
"classifier.summary()"
],
"execution_count": 129,
"outputs": [
{
"output_type": "stream",
"text": [
"Model: \"sequential\"\n",
"_________________________________________________________________\n",
"Layer (type) Output Shape Param # \n",
"=================================================================\n",
"conv2d (Conv2D) (None, 28, 28, 32) 320 \n",
"_________________________________________________________________\n",
"conv2d_1 (Conv2D) (None, 28, 28, 32) 9248 \n",
"_________________________________________________________________\n",
"max_pooling2d (MaxPooling2D) (None, 14, 14, 32) 0 \n",
"_________________________________________________________________\n",
"dropout (Dropout) (None, 14, 14, 32) 0 \n",
"_________________________________________________________________\n",
"conv2d_2 (Conv2D) (None, 14, 14, 64) 18496 \n",
"_________________________________________________________________\n",
"conv2d_3 (Conv2D) (None, 14, 14, 64) 36928 \n",
"_________________________________________________________________\n",
"max_pooling2d_1 (MaxPooling2 (None, 7, 7, 64) 0 \n",
"_________________________________________________________________\n",
"dropout_1 (Dropout) (None, 7, 7, 64) 0 \n",
"_________________________________________________________________\n",
"flatten (Flatten) (None, 3136) 0 \n",
"_________________________________________________________________\n",
"dense (Dense) (None, 256) 803072 \n",
"_________________________________________________________________\n",
"dense_1 (Dense) (None, 10) 2570 \n",
"=================================================================\n",
"Total params: 870,634\n",
"Trainable params: 870,634\n",
"Non-trainable params: 0\n",
"_________________________________________________________________\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "xifh7HNgLrr7",
"colab_type": "code",
"colab": {}
},
"source": [
"classifier.compile(optimize='rmsprop', metrics=['accuracy'],loss='sparse_categorical_crossentropy')"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "QET-VYRKLo17",
"colab_type": "code",
"outputId": "002ddeae-97f1-4e34-dcd3-418d5748f30c",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 225
}
},
"source": [
"classifier.fit(mnist_train, epochs=5 ,validation_data=mnist_test, steps_per_epoch=train_size//batch_size, validation_steps=test_size//batch_size, verbose=1)"
],
"execution_count": 131,
"outputs": [
{
"output_type": "stream",
"text": [
"Train for 468 steps, validate for 78 steps\n",
"Epoch 1/5\n",
"468/468 [==============================] - 15s 31ms/step - loss: 0.2151 - accuracy: 0.9302 - val_loss: 0.0520 - val_accuracy: 0.9823\n",
"Epoch 2/5\n",
"468/468 [==============================] - 12s 25ms/step - loss: 0.0712 - accuracy: 0.9784 - val_loss: 0.0316 - val_accuracy: 0.9888\n",
"Epoch 3/5\n",
"468/468 [==============================] - 12s 25ms/step - loss: 0.0531 - accuracy: 0.9833 - val_loss: 0.0251 - val_accuracy: 0.9908\n",
"Epoch 4/5\n",
"468/468 [==============================] - 12s 25ms/step - loss: 0.0438 - accuracy: 0.9864 - val_loss: 0.0310 - val_accuracy: 0.9898\n",
"Epoch 5/5\n",
"468/468 [==============================] - 12s 25ms/step - loss: 0.0384 - accuracy: 0.9884 - val_loss: 0.0187 - val_accuracy: 0.9934\n"
],
"name": "stdout"
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<tensorflow.python.keras.callbacks.History at 0x7f71a6bda3c8>"
]
},
"metadata": {
"tags": []
},
"execution_count": 131
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "OoYo28WSh2Ig",
"colab_type": "code",
"colab": {}
},
"source": [
"classifier.save('shapes_cnn.h5')"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "UIToN0Wn_XJ6",
"colab_type": "text"
},
"source": [
"# Visualizer"
]
},
{
"cell_type": "code",
"metadata": {
"id": "JrvWRQ7vQySx",
"colab_type": "code",
"colab": {}
},
"source": [
"classifier = tf.keras.models.load_model('shapes_cnn.h5')"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "04dDyhjxATEH",
"colab_type": "code",
"colab": {}
},
"source": [
"class Visualizer:\n",
" '''\n",
" Should import in the parent scope:\n",
" - tensorflow as tf\n",
" - pyplot as plt\n",
" '''\n",
" def __init__(self, model, color_precision=4, images_per_row=16):\n",
" '''\n",
" -model: a trained model\n",
" -tensor_sample: the image's tensor to show\n",
" -images_per_row: number of images per row\n",
" -color_preicision:\n",
" Should be greater than 1. Divides the perceptrons with a value greater\n",
" than the activation's image mean into color_precision colors.\n",
" '''\n",
" self.model = model\n",
" self.images_per_row = images_per_row\n",
" self.color_precision = max(1, color_precision)\n",
" self.layer_names = []\n",
" self.layer_outputs = [layer.output for layer in model.layers[:7]]\n",
" self.activation_model = tf.keras.models.Model(inputs=model.input, outputs=self.layer_outputs)\n",
" for layer in model.layers[:7]:\n",
" self.layer_names.append(layer.name) # Names of the layers, so you can have them as part of your plot\n",
"\n",
" def visualize(self, img_tensor):\n",
" activations = self.activation_model.predict(img_tensor)\n",
" for layer_name, layer_activation in zip(self.layer_names, activations): # Displays the feature maps\n",
" n_features = layer_activation.shape[-1] # Number of features in the feature map\n",
" size = layer_activation.shape[1] #The feature map has shape (1, size, size, n_features).\n",
" n_cols = n_features // self.images_per_row # Tiles the activation channels in this matrix\n",
" display_grid = np.zeros((size * n_cols, self.images_per_row * size))\n",
" for col in range(n_cols): # Tiles each filter into a big horizontal grid\n",
" for row in range(self.images_per_row):\n",
" channel_image = layer_activation[0,:, :, col * self.images_per_row + row]\n",
" # Post-processes to \n",
" #Standardization\n",
" channel_image -= channel_image.mean()\n",
" channel_image /= channel_image.std()\n",
" #Sets values < mean to 0, creates a heat map of 255//color_precision colors\n",
" channel_image *= 255 // self.color_precision\n",
" channel_image = np.clip(channel_image, 0, 255).astype('uint8')\n",
" display_grid[col * size : (col + 1) * size, row * size : (row + 1) * size] = channel_image\n",
" scale = 1. / size\n",
" plt.figure(figsize=(scale * display_grid.shape[1], scale * display_grid.shape[0]))\n",
" plt.title(layer_name)\n",
" plt.grid(False)\n",
" plt.imshow(display_grid, aspect='auto', cmap='viridis')\n",
" plt.colorbar()"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "gC9Wfr3rAWqH",
"colab_type": "code",
"colab": {}
},
"source": [
"v = Visualizer(classifier, 4)"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "qE6mo4xwI8X2",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"outputId": "d30337fb-bd16-45a3-9fd5-b25e070a1175"
},
"source": [
"v.visualize(mnist_test.take(1))"
],
"execution_count": 143,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": 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K6ou1/CKSRjNL7uPetMCuvXuLl3mz3O08KpION4Q2c6ezi3iKuJavCvq2/wrq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\nSUVORK5CYII=\n",
"text/plain": [
"<Figure size 1152x144 with 2 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "display_data",
"data": {
"image/png": 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hj57XxxcZ/vWKVmS8J5G7ZOqeAmXi40kZsh2A/dMzARj3xW2krpQIg6HmdMINsel2eZ9e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\nLJEeOrshZV8AAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 1152x144 with 2 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "display_data",
"data": {
"image/png": 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h1uV46zZfR92+OU6fvTDq/JFPXeXiQb+J/b1x3nF2Lj3095+4uO9fW27oiWyRbA2OiJQD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\nLlkAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 1152x144 with 2 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "display_data",
"data": {
"image/png": 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O/7x62H4u9tbd+La5PnpfVl94WNTHck28FziqenqUh46P0FYBXBxvn3bbCxwi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\n",
"text/plain": [
"<Figure size 1152x144 with 2 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "display_data",
"data": {
"image/png": 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86CEiIiIiopREEqSu5QoxjTTkYCxtpL05Rtjeh4iap8DhAzXe4QyAHs5ukoNx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\nAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 1152x288 with 2 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "display_data",
"data": {
"image/png": 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e3zw0fe/xfMrDKRSzdTr26W5/PDaJaNCzk5Y9/L34BQGsuvJn81V1UPySmeGP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\n7hheU5QAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 1152x288 with 2 Axes>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "display_data",
"data": {
"image/png": 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qW5UkPeYtTNTMBku6RVI/Za/cm+ruPzOzKyV9WdL6ZNUp7v5ArrH2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\nizZQK3wAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 1152x288 with 2 Axes>"
]
},
"metadata": {
"tags": []
}
}
]
}
]
}
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