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.ipynb_checkpoints/keras_to_tensorflow-checkpoint.ipynb
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,173 @@ | ||
| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "# Set parameters" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 1, | ||
| "metadata": { | ||
| "collapsed": true | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "input_fld = 'input_fld_path'\n", | ||
| "weight_file = 'kerasmodel_file_name located inside input_fld'\n", | ||
| "num_output = 1\n", | ||
| "write_graph_def_ascii_flag = True\n", | ||
| "prefix_output_node_names_of_final_network = 'output_node'\n", | ||
| "output_graph_name = 'constant_graph_weights.pb'" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "# initialize" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 2, | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "name": "stderr", | ||
| "output_type": "stream", | ||
| "text": [ | ||
| "Using TensorFlow backend.\n" | ||
| ] | ||
| } | ||
| ], | ||
| "source": [ | ||
| "from keras.models import load_model\n", | ||
| "import tensorflow as tf\n", | ||
| "import os\n", | ||
| "import os.path as osp\n", | ||
| "\n", | ||
| "output_fld = input_fld + 'tensorflow_model/'\n", | ||
| "if not os.path.isdir(output_fld):\n", | ||
| " os.mkdir(output_fld)\n", | ||
| "weight_file_path = osp.join(input_fld, weight_file)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "# Load keras model and rename output" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 3, | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "name": "stdout", | ||
| "output_type": "stream", | ||
| "text": [ | ||
| "output nodes names are: ['output_node0']\n" | ||
| ] | ||
| } | ||
| ], | ||
| "source": [ | ||
| "net_model = load_model(weight_file_path)\n", | ||
| "\n", | ||
| "pred = [None]*num_output\n", | ||
| "pred_node_names = [None]*num_output\n", | ||
| "for i in range(num_output):\n", | ||
| " pred_node_names[i] = prefix_output_node_names_of_final_network+str(i)\n", | ||
| " pred[i] = tf.identity(net_model.output[i], name=pred_node_names[i])\n", | ||
| "print('output nodes names are: ', pred_node_names)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "#### [optional] write graph definition in ascii" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 4, | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "name": "stdout", | ||
| "output_type": "stream", | ||
| "text": [ | ||
| "saved the graph definition in ascii format at: /home/amir/deep-batch/trained/KerasEchoQualityMultiStream/snapshots/freeze_uniformValid_bn/s/tensorflow_model/only_the_graph_def.pb.ascii\n" | ||
| ] | ||
| } | ||
| ], | ||
| "source": [ | ||
| "from keras import backend as K\n", | ||
| "sess = K.get_session()\n", | ||
| "\n", | ||
| "if write_graph_def_ascii_flag:\n", | ||
| " f = 'only_the_graph_def.pb.ascii'\n", | ||
| " tf.train.write_graph(sess.graph.as_graph_def(), output_fld, f, as_text=True)\n", | ||
| " print('saved the graph definition in ascii format at: ', osp.join(output_fld, f))" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "#### convert variables to constants and save" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 5, | ||
| "metadata": { | ||
| "scrolled": true | ||
| }, | ||
| "outputs": [ | ||
| { | ||
| "name": "stdout", | ||
| "output_type": "stream", | ||
| "text": [ | ||
| "INFO:tensorflow:Froze 27 variables.\n", | ||
| "Converted 27 variables to const ops.\n", | ||
| "saved the constant graph (ready for inference) at: /home/amir/deep-batch/trained/KerasEchoQualityMultiStream/snapshots/freeze_uniformValid_bn/s/tensorflow_model/constant_graph_weights.pb\n" | ||
| ] | ||
| } | ||
| ], | ||
| "source": [ | ||
| "from tensorflow.python.framework import graph_util\n", | ||
| "from tensorflow.python.framework import graph_io\n", | ||
| "constant_graph = graph_util.convert_variables_to_constants(sess, sess.graph.as_graph_def(), pred_node_names)\n", | ||
| "graph_io.write_graph(constant_graph, output_fld, output_graph_name, as_text=False)\n", | ||
| "print('saved the constant graph (ready for inference) at: ', osp.join(output_fld, output_graph_name))" | ||
| ] | ||
| } | ||
| ], | ||
| "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": "3.5.0" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 1 | ||
| } |
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