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@thegodone
Forked from tik0/VAE_plot_add_loss.ipynb
Created January 29, 2022 07:49
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Using TensorFlow backend.\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"2.2.4\n"
]
}
],
"source": [
"'''This script demonstrates how to build a variational\n",
" autoencoder with Keras having multiple heads with losses.\n",
"\n",
" #Reference\n",
"\n",
" - Auto-Encoding Variational Bayes\n",
" https://arxiv.org/abs/1312.6114\n",
"'''\n",
"import os,sys\n",
"import numpy as np\n",
"import random\n",
"import matplotlib\n",
"import matplotlib.pyplot as plt\n",
"from scipy.stats import norm\n",
"\n",
"import keras\n",
"from keras.layers import Input, Dense, Lambda, Layer, Concatenate\n",
"from keras.models import Model\n",
"from keras import backend as K\n",
"from keras import metrics\n",
"from keras.datasets import mnist\n",
"from keras.utils import plot_model\n",
"\n",
"# Set random seeds\n",
"def set_seed():\n",
" import numpy, tensorflow, random \n",
" seed_number = 0 # determinism only works for seed == 0: https://github.com/tensorflow/tensorflow/blob/master/RELEASE.md#bug-fixes-and-other-changes-14\n",
" random.seed(seed_number)\n",
" numpy.random.seed(seed_number)\n",
" tensorflow.set_random_seed(seed_number)\n",
"\n",
"print(keras.__version__)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"# Setup\n",
"batch_size = 1000\n",
"original_dim = 784\n",
"latent_dim = 2\n",
"intermediate_dim = 256\n",
"epochs = 50\n",
"epsilon_std = 1.0\n",
"beta = 1.\n",
"\n",
"# train the VAE on MNIST digits\n",
"(x_train, y_train), (x_test, y_test) = mnist.load_data()\n",
"\n",
"x_train = x_train.astype('float32') / 255.\n",
"x_test = x_test.astype('float32') / 255.\n",
"x_train = x_train.reshape((len(x_train), np.prod(x_train.shape[1:])))\n",
"x_test = x_test.reshape((len(x_test), np.prod(x_test.shape[1:])))\n",
"\n",
"# Function for plotting the latent representation\n",
"def plot_latent_space(x, z_mean):\n",
" # build a model to project inputs on the latent space\n",
" encoder = Model(x, z_mean)\n",
" # display a 2D plot of the digit classes in the latent space\n",
" x_test_encoded = encoder.predict(x_test, batch_size=batch_size)\n",
" plt.figure(figsize=(6, 6))\n",
" plt.scatter(x_test_encoded[:, 0], x_test_encoded[:, 1], c=y_test, cmap='tab10')\n",
" plt.colorbar()\n",
" plt.axis(\"equal\")\n",
" plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"# Split custom loss layer\n",
"#def VAE_split_custom_layer():\n",
"set_seed()\n",
"x = Input(shape=(original_dim,))\n",
"h = Dense(intermediate_dim, activation='relu')(x)\n",
"z_mean = Dense(latent_dim)(h)\n",
"z_log_var = Dense(latent_dim)(h)\n",
"\n",
"def sampling(args):\n",
" z_mean, z_log_var = args\n",
" epsilon = K.random_normal(shape=(K.shape(z_mean)[0], latent_dim), mean=0.,\n",
" stddev=epsilon_std)\n",
" return z_mean + K.exp(z_log_var / 2) * epsilon\n",
"\n",
"# note that \"output_shape\" isn't necessary with the TensorFlow backend\n",
"z = Lambda(sampling, output_shape=(latent_dim,))([z_mean, z_log_var])\n",
"\n",
"# we instantiate these layers separately so as to reuse them later\n",
"decoder_h = Dense(intermediate_dim, activation='relu')\n",
"decoder_mean = Dense(original_dim, activation='sigmoid')\n",
"h_decoded = decoder_h(z)\n",
"x_decoded_mean = decoder_mean(h_decoded)\n",
"\n",
"\n",
"# Custom loss layer for reconstruction\n",
"class CustomLossLayerReconstruction(Layer):\n",
" def __init__(self, **kwargs):\n",
" self.is_placeholder = True\n",
" super().__init__(**kwargs)\n",
"\n",
" def call(self, inputs):\n",
" x = inputs[0]\n",
" x_decoded_mean = inputs[1]\n",
" xent_loss = original_dim * metrics.binary_crossentropy(x, x_decoded_mean)\n",
" self.add_loss(xent_loss, inputs=inputs)\n",
" return xent_loss # define the loss as output\n",
"\n",
"# Custom loss layer for kl-loss\n",
"class CustomLossLayerKL(Layer):\n",
" def __init__(self, **kwargs):\n",
" self.is_placeholder = True\n",
" super().__init__(**kwargs)\n",
"\n",
" def call(self, inputs):\n",
" z_mean = inputs[0]\n",
" z_log_var = inputs[1]\n",
" kl_loss = - 0.5 * K.sum(1 + z_log_var - K.square(z_mean) - K.exp(z_log_var), axis=-1)\n",
" self.add_loss(kl_loss, inputs=inputs)\n",
" return kl_loss # define the loss as output\n",
"\n",
"y_ent = CustomLossLayerReconstruction(name = \"myCustomLossLayerReconstruction\")([x, x_decoded_mean])\n",
"y_kl = CustomLossLayerKL(name = \"myCustomLossLayerKL\")([z_mean, z_log_var])\n",
"vae = Model(inputs = x, outputs = [y_kl, y_ent])\n",
"vae.compile(optimizer='rmsprop', loss=None)\n",
"\n",
"# Create a history class which stores the ouputs of the loss layer after every epoch\n",
"class History(keras.callbacks.Callback):\n",
" def on_train_begin(self, logs={}):\n",
" self.history = {}\n",
" self.epoch = []\n",
" \n",
" def on_train_end(self, logs={}):\n",
" return\n",
" \n",
" def on_epoch_begin(self, epoch, logs={}):\n",
" return\n",
" \n",
" def on_epoch_end(self, epoch, logs={}):\n",
" self.epoch.append(epoch)\n",
" # Get the output layer names (we only have loss layers as output)\n",
" output_layer_names = [output_layer.name for output_layer in self.model.output]\n",
" # Get the mean error over all batches in this epoch\n",
" output_layer_values = np.mean(self.model.predict(x_test), axis = 1)\n",
" # Store it to the history\n",
" for k, v in zip(output_layer_names, output_layer_values):\n",
" self.history.setdefault(k, []).append(v)\n",
" return\n",
" \n",
" def on_batch_begin(self, batch, logs={}):\n",
" return\n",
" \n",
" def on_batch_end(self, batch, logs={}):\n",
" return"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 1440x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# Show the model\n",
"plot_model(vae, to_file='model.png')\n",
"plt.figure(figsize=(20,10))\n",
"plt.imshow(matplotlib.image.imread('model.png'))\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Train on 60000 samples, validate on 10000 samples\n",
"Epoch 1/50\n",
"60000/60000 [==============================] - 1s 19us/step - loss: 266.3198 - val_loss: 208.6639\n",
"Epoch 2/50\n",
"60000/60000 [==============================] - 0s 7us/step - loss: 199.2605 - val_loss: 190.9858\n",
"Epoch 3/50\n",
"60000/60000 [==============================] - 0s 7us/step - loss: 187.7361 - val_loss: 184.0141\n",
"Epoch 4/50\n",
"60000/60000 [==============================] - 0s 7us/step - loss: 181.9327 - val_loss: 178.6062\n",
"Epoch 5/50\n",
"60000/60000 [==============================] - 0s 7us/step - loss: 177.6862 - val_loss: 175.4489\n",
"Epoch 6/50\n",
"60000/60000 [==============================] - 0s 8us/step - loss: 174.8471 - val_loss: 173.1417\n",
"Epoch 7/50\n",
"60000/60000 [==============================] - 0s 8us/step - loss: 172.7229 - val_loss: 171.3819\n",
"Epoch 8/50\n",
"60000/60000 [==============================] - 0s 8us/step - loss: 171.1873 - val_loss: 170.1225\n",
"Epoch 9/50\n",
"60000/60000 [==============================] - 0s 8us/step - loss: 169.9670 - val_loss: 169.3821\n",
"Epoch 10/50\n",
"60000/60000 [==============================] - 0s 8us/step - loss: 169.1517 - val_loss: 168.5668\n",
"Epoch 11/50\n",
"60000/60000 [==============================] - 0s 8us/step - loss: 168.3434 - val_loss: 167.8356\n",
"Epoch 12/50\n",
"60000/60000 [==============================] - 0s 8us/step - loss: 167.6748 - val_loss: 167.6271\n",
"Epoch 13/50\n",
"60000/60000 [==============================] - 0s 7us/step - loss: 167.0818 - val_loss: 166.8217\n",
"Epoch 14/50\n",
"60000/60000 [==============================] - 0s 7us/step - loss: 166.5191 - val_loss: 166.4166\n",
"Epoch 15/50\n",
"60000/60000 [==============================] - 0s 7us/step - loss: 165.9591 - val_loss: 165.6445\n",
"Epoch 16/50\n",
"60000/60000 [==============================] - 0s 7us/step - loss: 165.4566 - val_loss: 165.5391\n",
"Epoch 17/50\n",
"60000/60000 [==============================] - 0s 7us/step - loss: 164.9700 - val_loss: 164.9015\n",
"Epoch 18/50\n",
"60000/60000 [==============================] - 0s 7us/step - loss: 164.4987 - val_loss: 164.6274\n",
"Epoch 19/50\n",
"60000/60000 [==============================] - 0s 7us/step - loss: 164.0510 - val_loss: 164.3412\n",
"Epoch 20/50\n",
"60000/60000 [==============================] - 0s 8us/step - loss: 163.6856 - val_loss: 163.7659\n",
"Epoch 21/50\n",
"60000/60000 [==============================] - 0s 7us/step - loss: 163.3235 - val_loss: 163.5108\n",
"Epoch 22/50\n",
"60000/60000 [==============================] - 0s 7us/step - loss: 162.9648 - val_loss: 163.4215\n",
"Epoch 23/50\n",
"60000/60000 [==============================] - 0s 7us/step - loss: 162.6424 - val_loss: 162.6970\n",
"Epoch 24/50\n",
"60000/60000 [==============================] - 0s 7us/step - loss: 162.3183 - val_loss: 162.4816\n",
"Epoch 25/50\n",
"60000/60000 [==============================] - 0s 7us/step - loss: 162.0582 - val_loss: 162.4159\n",
"Epoch 26/50\n",
"60000/60000 [==============================] - 0s 7us/step - loss: 161.7754 - val_loss: 162.1738\n",
"Epoch 27/50\n",
"60000/60000 [==============================] - 0s 8us/step - loss: 161.4656 - val_loss: 161.6333\n",
"Epoch 28/50\n",
"60000/60000 [==============================] - 0s 7us/step - loss: 161.2278 - val_loss: 161.5503\n",
"Epoch 29/50\n",
"60000/60000 [==============================] - 0s 8us/step - loss: 160.9633 - val_loss: 161.1082\n",
"Epoch 30/50\n",
"60000/60000 [==============================] - 0s 8us/step - loss: 160.7125 - val_loss: 160.9645\n",
"Epoch 31/50\n",
"60000/60000 [==============================] - 0s 8us/step - loss: 160.4232 - val_loss: 160.5957\n",
"Epoch 32/50\n",
"60000/60000 [==============================] - 0s 8us/step - loss: 160.2068 - val_loss: 160.4119\n",
"Epoch 33/50\n",
"60000/60000 [==============================] - 0s 8us/step - loss: 159.9657 - val_loss: 160.3139\n",
"Epoch 34/50\n",
"60000/60000 [==============================] - 0s 7us/step - loss: 159.6956 - val_loss: 160.2022\n",
"Epoch 35/50\n",
"60000/60000 [==============================] - 0s 7us/step - loss: 159.4501 - val_loss: 159.9078\n",
"Epoch 36/50\n",
"60000/60000 [==============================] - 0s 6us/step - loss: 159.2795 - val_loss: 159.6718\n",
"Epoch 37/50\n",
"60000/60000 [==============================] - 0s 7us/step - loss: 158.9429 - val_loss: 159.5777\n",
"Epoch 38/50\n",
"60000/60000 [==============================] - 0s 7us/step - loss: 158.7752 - val_loss: 159.0704\n",
"Epoch 39/50\n",
"60000/60000 [==============================] - 0s 7us/step - loss: 158.5018 - val_loss: 159.1409\n",
"Epoch 40/50\n",
"60000/60000 [==============================] - 0s 6us/step - loss: 158.3198 - val_loss: 158.9218\n",
"Epoch 41/50\n",
"60000/60000 [==============================] - 0s 7us/step - loss: 158.0733 - val_loss: 158.5709\n",
"Epoch 42/50\n",
"60000/60000 [==============================] - 0s 7us/step - loss: 157.8443 - val_loss: 158.2788\n",
"Epoch 43/50\n",
"60000/60000 [==============================] - 0s 7us/step - loss: 157.6536 - val_loss: 158.5555\n",
"Epoch 44/50\n",
"60000/60000 [==============================] - 0s 6us/step - loss: 157.4120 - val_loss: 158.3142\n",
"Epoch 45/50\n",
"60000/60000 [==============================] - 0s 8us/step - loss: 157.2963 - val_loss: 157.9197\n",
"Epoch 46/50\n",
"60000/60000 [==============================] - 0s 8us/step - loss: 157.0183 - val_loss: 157.8095\n",
"Epoch 47/50\n",
"60000/60000 [==============================] - 0s 7us/step - loss: 156.8752 - val_loss: 158.1492\n",
"Epoch 48/50\n",
"60000/60000 [==============================] - 0s 8us/step - loss: 156.7158 - val_loss: 157.5806\n",
"Epoch 49/50\n",
"60000/60000 [==============================] - 0s 7us/step - loss: 156.4837 - val_loss: 157.1907\n",
"Epoch 50/50\n",
"60000/60000 [==============================] - 0s 7us/step - loss: 156.3074 - val_loss: 157.4017\n"
]
},
{
"data": {
"text/plain": [
"<keras.callbacks.History at 0x7f7ecaacc2e8>"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Train the model\n",
"my_history = History()\n",
"vae.fit(x_train,\n",
" shuffle=True,\n",
" epochs=epochs,\n",
" batch_size=batch_size,\n",
" validation_data=(x_test, None),\n",
" verbose = 1,\n",
" callbacks=[my_history])"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 432x432 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# Show the latent space\n",
"plot_latent_space(x, z_mean)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# Show both loss in one plot\n",
"for v in my_history.history.values():\n",
" plt.plot(v)\n",
"plt.legend(list(my_history.history.keys()), loc='upper right')\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# Show the plots in more detail\n",
"plt.plot(list(my_history.history.values())[0])\n",
"plt.legend([list(my_history.history.keys())[0]], loc='upper right')\n",
"plt.show()\n",
"plt.plot(list(my_history.history.values())[1])\n",
"plt.legend([list(my_history.history.keys())[1]], loc='upper right')\n",
"plt.show()\n"
]
}
],
"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": "3.5.2"
},
"varInspector": {
"cols": {
"lenName": 16,
"lenType": 16,
"lenVar": 40
},
"kernels_config": {
"python": {
"delete_cmd_postfix": "",
"delete_cmd_prefix": "del ",
"library": "var_list.py",
"varRefreshCmd": "print(var_dic_list())"
},
"r": {
"delete_cmd_postfix": ") ",
"delete_cmd_prefix": "rm(",
"library": "var_list.r",
"varRefreshCmd": "cat(var_dic_list()) "
}
},
"types_to_exclude": [
"module",
"function",
"builtin_function_or_method",
"instance",
"_Feature"
],
"window_display": false
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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