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cftang0827/keras-to-tensorflow.ipynb

Created March 3, 2020 16:51
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keras-to-tensorflow.ipynb
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keras-to-tensorflow.ipynb
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "keras-to-tensorflow.ipynb",
"provenance": [],
"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/cftang0827/00ad54710ca4fe95911c07ae0f54438c/keras-to-tensorflow.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "code",
"metadata": {
"id": "p3dURhDxJGfl",
"colab_type": "code",
"outputId": "5d66af84-2f84-485c-ad5e-423fa97bb29f",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 510
}
},
"source": [
"!pip install tensorflow==1.15\n",
"!pip install keras"
],
"execution_count": 1,
"outputs": [
{
"output_type": "stream",
"text": [
"Requirement already satisfied: tensorflow==1.15 in /usr/local/lib/python3.6/dist-packages (1.15.0)\n",
"Requirement already satisfied: opt-einsum>=2.3.2 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.15) (3.1.0)\n",
"Requirement already satisfied: termcolor>=1.1.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.15) (1.1.0)\n",
"Requirement already satisfied: keras-applications>=1.0.8 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.15) (1.0.8)\n",
"Requirement already satisfied: google-pasta>=0.1.6 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.15) (0.1.8)\n",
"Requirement already satisfied: tensorflow-estimator==1.15.1 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.15) (1.15.1)\n",
"Requirement already satisfied: gast==0.2.2 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.15) (0.2.2)\n",
"Requirement already satisfied: wheel>=0.26 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.15) (0.34.2)\n",
"Requirement already satisfied: tensorboard<1.16.0,>=1.15.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.15) (1.15.0)\n",
"Requirement already satisfied: numpy<2.0,>=1.16.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.15) (1.17.5)\n",
"Requirement already satisfied: grpcio>=1.8.6 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.15) (1.27.1)\n",
"Requirement already satisfied: six>=1.10.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.15) (1.12.0)\n",
"Requirement already satisfied: protobuf>=3.6.1 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.15) (3.10.0)\n",
"Requirement already satisfied: astor>=0.6.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.15) (0.8.1)\n",
"Requirement already satisfied: keras-preprocessing>=1.0.5 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.15) (1.1.0)\n",
"Requirement already satisfied: absl-py>=0.7.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.15) (0.9.0)\n",
"Requirement already satisfied: wrapt>=1.11.1 in /usr/local/lib/python3.6/dist-packages (from tensorflow==1.15) (1.11.2)\n",
"Requirement already satisfied: h5py in /usr/local/lib/python3.6/dist-packages (from keras-applications>=1.0.8->tensorflow==1.15) (2.8.0)\n",
"Requirement already satisfied: werkzeug>=0.11.15 in /usr/local/lib/python3.6/dist-packages (from tensorboard<1.16.0,>=1.15.0->tensorflow==1.15) (1.0.0)\n",
"Requirement already satisfied: setuptools>=41.0.0 in /usr/local/lib/python3.6/dist-packages (from tensorboard<1.16.0,>=1.15.0->tensorflow==1.15) (45.1.0)\n",
"Requirement already satisfied: markdown>=2.6.8 in /usr/local/lib/python3.6/dist-packages (from tensorboard<1.16.0,>=1.15.0->tensorflow==1.15) (3.2.1)\n",
"Requirement already satisfied: keras in /usr/local/lib/python3.6/dist-packages (2.2.5)\n",
"Requirement already satisfied: pyyaml in /usr/local/lib/python3.6/dist-packages (from keras) (3.13)\n",
"Requirement already satisfied: scipy>=0.14 in /usr/local/lib/python3.6/dist-packages (from keras) (1.4.1)\n",
"Requirement already satisfied: keras-preprocessing>=1.1.0 in /usr/local/lib/python3.6/dist-packages (from keras) (1.1.0)\n",
"Requirement already satisfied: keras-applications>=1.0.8 in /usr/local/lib/python3.6/dist-packages (from keras) (1.0.8)\n",
"Requirement already satisfied: six>=1.9.0 in /usr/local/lib/python3.6/dist-packages (from keras) (1.12.0)\n",
"Requirement already satisfied: h5py in /usr/local/lib/python3.6/dist-packages (from keras) (2.8.0)\n",
"Requirement already satisfied: numpy>=1.9.1 in /usr/local/lib/python3.6/dist-packages (from keras) (1.17.5)\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "0X59FdDpJLc9",
"colab_type": "code",
"outputId": "360d3f8c-ca03-4a0e-bdeb-129ca62720aa",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
}
},
"source": [
"from __future__ import print_function\n",
"import keras\n",
"from keras.datasets import mnist\n",
"from keras.models import Sequential\n",
"from keras.layers import Dense, Dropout, Flatten\n",
"from keras.layers import Conv2D, MaxPooling2D\n",
"from keras import backend as K\n",
"\n",
"\n",
"import tensorflow as tf\n",
"\n",
"batch_size = 128\n",
"num_classes = 10\n",
"epochs = 5\n",
"\n",
"# input image dimensions\n",
"img_rows, img_cols = 28, 28\n",
"\n",
"# the data, split between train and test sets\n",
"(x_train, y_train), (x_test, y_test) = mnist.load_data()\n",
"\n",
"if K.image_data_format() == 'channels_first':\n",
" x_train = x_train.reshape(x_train.shape[0], 1, img_rows, img_cols)\n",
" x_test = x_test.reshape(x_test.shape[0], 1, img_rows, img_cols)\n",
" input_shape = (1, img_rows, img_cols)\n",
"else:\n",
" x_train = x_train.reshape(x_train.shape[0], img_rows, img_cols, 1)\n",
" x_test = x_test.reshape(x_test.shape[0], img_rows, img_cols, 1)\n",
" input_shape = (img_rows, img_cols, 1)\n",
"\n",
"x_train = x_train.astype('float32')\n",
"x_test = x_test.astype('float32')\n",
"x_train /= 255\n",
"x_test /= 255\n",
"print('x_train shape:', x_train.shape)\n",
"print(x_train.shape[0], 'train samples')\n",
"print(x_test.shape[0], 'test samples')\n",
"\n",
"# convert class vectors to binary class matrices\n",
"y_train = keras.utils.to_categorical(y_train, num_classes)\n",
"y_test = keras.utils.to_categorical(y_test, num_classes)\n",
"\n",
"model = Sequential()\n",
"model.add(Conv2D(32, kernel_size=(3, 3),\n",
" activation='relu',\n",
" input_shape=input_shape))\n",
"model.add(Conv2D(64, (3, 3), activation='relu'))\n",
"model.add(MaxPooling2D(pool_size=(2, 2)))\n",
"model.add(Dropout(0.25))\n",
"model.add(Flatten())\n",
"model.add(Dense(128, activation='relu'))\n",
"model.add(Dropout(0.5))\n",
"model.add(Dense(num_classes, activation='softmax', name='output_layer'))\n",
"\n",
"model.compile(loss=keras.losses.categorical_crossentropy,\n",
" optimizer=keras.optimizers.Adadelta(),\n",
" metrics=['accuracy'])\n",
"\n",
"model.fit(x_train, y_train,\n",
" batch_size=batch_size,\n",
" epochs=epochs,\n",
" verbose=1,\n",
" validation_data=(x_test, y_test))\n",
"score = model.evaluate(x_test, y_test, verbose=0)\n",
"print('Test loss:', score[0])\n",
"print('Test accuracy:', score[1])"
],
"execution_count": 2,
"outputs": [
{
"output_type": "stream",
"text": [
"Using TensorFlow backend.\n"
],
"name": "stderr"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"<p style=\"color: red;\">\n",
"The default version of TensorFlow in Colab will soon switch to TensorFlow 2.x.<br>\n",
"We recommend you <a href=\"https://www.tensorflow.org/guide/migrate\" target=\"_blank\">upgrade</a> now \n",
"or ensure your notebook will continue to use TensorFlow 1.x via the <code>%tensorflow_version 1.x</code> magic:\n",
"<a href=\"https://colab.research.google.com/notebooks/tensorflow_version.ipynb\" target=\"_blank\">more info</a>.</p>\n"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"Downloading data from https://s3.amazonaws.com/img-datasets/mnist.npz\n",
"11493376/11490434 [==============================] - 1s 0us/step\n",
"x_train shape: (60000, 28, 28, 1)\n",
"60000 train samples\n",
"10000 test samples\n",
"WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:66: The name tf.get_default_graph is deprecated. Please use tf.compat.v1.get_default_graph instead.\n",
"\n",
"WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:541: The name tf.placeholder is deprecated. Please use tf.compat.v1.placeholder instead.\n",
"\n",
"WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:4432: The name tf.random_uniform is deprecated. Please use tf.random.uniform instead.\n",
"\n",
"WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:4267: The name tf.nn.max_pool is deprecated. Please use tf.nn.max_pool2d instead.\n",
"\n",
"WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:148: The name tf.placeholder_with_default is deprecated. Please use tf.compat.v1.placeholder_with_default instead.\n",
"\n",
"WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:3733: calling dropout (from tensorflow.python.ops.nn_ops) with keep_prob is deprecated and will be removed in a future version.\n",
"Instructions for updating:\n",
"Please use `rate` instead of `keep_prob`. Rate should be set to `rate = 1 - keep_prob`.\n",
"WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/optimizers.py:793: The name tf.train.Optimizer is deprecated. Please use tf.compat.v1.train.Optimizer instead.\n",
"\n",
"WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:3576: The name tf.log is deprecated. Please use tf.math.log instead.\n",
"\n",
"WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/ops/math_grad.py:1424: where (from tensorflow.python.ops.array_ops) is deprecated and will be removed in a future version.\n",
"Instructions for updating:\n",
"Use tf.where in 2.0, which has the same broadcast rule as np.where\n",
"WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:1033: The name tf.assign_add is deprecated. Please use tf.compat.v1.assign_add instead.\n",
"\n",
"WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:1020: The name tf.assign is deprecated. Please use tf.compat.v1.assign instead.\n",
"\n",
"WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:3005: The name tf.Session is deprecated. Please use tf.compat.v1.Session instead.\n",
"\n",
"Train on 60000 samples, validate on 10000 samples\n",
"Epoch 1/5\n",
"WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:190: The name tf.get_default_session is deprecated. Please use tf.compat.v1.get_default_session instead.\n",
"\n",
"WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:197: The name tf.ConfigProto is deprecated. Please use tf.compat.v1.ConfigProto instead.\n",
"\n",
"WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:207: The name tf.global_variables is deprecated. Please use tf.compat.v1.global_variables instead.\n",
"\n",
"WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:216: The name tf.is_variable_initialized is deprecated. Please use tf.compat.v1.is_variable_initialized instead.\n",
"\n",
"WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:223: The name tf.variables_initializer is deprecated. Please use tf.compat.v1.variables_initializer instead.\n",
"\n",
"60000/60000 [==============================] - 18s 294us/step - loss: 0.2724 - acc: 0.9161 - val_loss: 0.0588 - val_acc: 0.9811\n",
"Epoch 2/5\n",
"60000/60000 [==============================] - 4s 64us/step - loss: 0.0919 - acc: 0.9735 - val_loss: 0.0413 - val_acc: 0.9862\n",
"Epoch 3/5\n",
"60000/60000 [==============================] - 4s 62us/step - loss: 0.0681 - acc: 0.9794 - val_loss: 0.0348 - val_acc: 0.9884\n",
"Epoch 4/5\n",
"60000/60000 [==============================] - 4s 61us/step - loss: 0.0552 - acc: 0.9838 - val_loss: 0.0322 - val_acc: 0.9886\n",
"Epoch 5/5\n",
"60000/60000 [==============================] - 4s 61us/step - loss: 0.0465 - acc: 0.9862 - val_loss: 0.0314 - val_acc: 0.9887\n",
"Test loss: 0.031373630624765794\n",
"Test accuracy: 0.9887\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "TjzHBZJbJYnG",
"colab_type": "code",
"outputId": "ec61e5cf-44b5-43a4-8acf-5de7c45a9840",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 425
}
},
"source": [
"model.summary()\n",
"model.save(\"model.h5\")\n"
],
"execution_count": 3,
"outputs": [
{
"output_type": "stream",
"text": [
"Model: \"sequential_1\"\n",
"_________________________________________________________________\n",
"Layer (type) Output Shape Param # \n",
"=================================================================\n",
"conv2d_1 (Conv2D) (None, 26, 26, 32) 320 \n",
"_________________________________________________________________\n",
"conv2d_2 (Conv2D) (None, 24, 24, 64) 18496 \n",
"_________________________________________________________________\n",
"max_pooling2d_1 (MaxPooling2 (None, 12, 12, 64) 0 \n",
"_________________________________________________________________\n",
"dropout_1 (Dropout) (None, 12, 12, 64) 0 \n",
"_________________________________________________________________\n",
"flatten_1 (Flatten) (None, 9216) 0 \n",
"_________________________________________________________________\n",
"dense_1 (Dense) (None, 128) 1179776 \n",
"_________________________________________________________________\n",
"dropout_2 (Dropout) (None, 128) 0 \n",
"_________________________________________________________________\n",
"output_layer (Dense) (None, 10) 1290 \n",
"=================================================================\n",
"Total params: 1,199,882\n",
"Trainable params: 1,199,882\n",
"Non-trainable params: 0\n",
"_________________________________________________________________\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "DwQsbjYwJhxb",
"colab_type": "code",
"colab": {}
},
"source": [
"# The part to get tensorflow session\n",
"sess = K.get_session()\n",
"graph = sess.graph"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "O_ruWkLsJouD",
"colab_type": "code",
"colab": {}
},
"source": [
"output_layer = graph.get_tensor_by_name(\"output_layer/Softmax:0\")"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "jYoYlwNRKXYT",
"colab_type": "code",
"outputId": "884d3bba-9b9f-4cba-abc0-f71049a8fe7a",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
}
},
"source": [
"output_layer"
],
"execution_count": 6,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<tf.Tensor 'output_layer/Softmax:0' shape=(?, 10) dtype=float32>"
]
},
"metadata": {
"tags": []
},
"execution_count": 6
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "hW9s-cE-Kcd4",
"colab_type": "code",
"outputId": "621eb534-bf7b-4414-8596-67f4186816ad",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 173
}
},
"source": [
"output_graph_def = tf.graph_util.convert_variables_to_constants(\n",
" sess,\n",
" graph.as_graph_def(),\n",
" [\"output_layer/Softmax\"]\n",
")\n"
],
"execution_count": 7,
"outputs": [
{
"output_type": "stream",
"text": [
"WARNING:tensorflow:From <ipython-input-7-bdab531501a6>:4: convert_variables_to_constants (from tensorflow.python.framework.graph_util_impl) is deprecated and will be removed in a future version.\n",
"Instructions for updating:\n",
"Use `tf.compat.v1.graph_util.convert_variables_to_constants`\n",
"WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/graph_util_impl.py:277: extract_sub_graph (from tensorflow.python.framework.graph_util_impl) is deprecated and will be removed in a future version.\n",
"Instructions for updating:\n",
"Use `tf.compat.v1.graph_util.extract_sub_graph`\n",
"INFO:tensorflow:Froze 8 variables.\n",
"INFO:tensorflow:Converted 8 variables to const ops.\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "qJfZceKvKu6C",
"colab_type": "code",
"colab": {}
},
"source": [
"with tf.gfile.GFile(\"model.pb\", \"wb\") as f:\n",
" f.write(output_graph_def.SerializeToString())"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "b5_zdX3pLCkG",
"colab_type": "code",
"outputId": "a7497711-96d4-4bbd-a3c6-dd440f5fb0cd",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 34
}
},
"source": [
"!ls\n"
],
"execution_count": 9,
"outputs": [
{
"output_type": "stream",
"text": [
"model.h5 model.pb sample_data\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "NJQwoiP4LGU8",
"colab_type": "code",
"colab": {}
},
"source": [
"from google.colab import files\n"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "gsZ5Z870Lqh8",
"colab_type": "code",
"colab": {}
},
"source": [
"# download tensorflow model\n",
"files.download(\"model.pb\")"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "rsTMqP5VLrzn",
"colab_type": "code",
"colab": {}
},
"source": [
"# download keras model\n",
"files.download(\"model.h5\")"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "hg-76YaCMAuL",
"colab_type": "code",
"colab": {}
},
"source": [
""
],
"execution_count": 0,
"outputs": []
}
]
}
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