How to remove dropout from frozen model

how_to_remove_dropout_from_frozen_model.ipynb

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      "source": "How to remove dropout from frozen model\n==="
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      "source": "from __future__ import print_function\nfrom tensorflow.core.framework import graph_pb2\nimport tensorflow as tf\nimport numpy as np\nfrom tensorflow.examples.tutorials.mnist import input_data\n\nmnist = input_data.read_data_sets('/tmp/data/', one_hot=True)\n\ndef display_nodes(nodes):\n    for i, node in enumerate(nodes):\n        print('%d %s %s' % (i, node.name, node.op))\n        [print(u'└─── %d ─ %s' % (i, n)) for i, n in enumerate(node.input)]\n        \ndef accuracy(predictions, labels):\n    return (100.0 * np.sum(np.argmax(predictions, 1) == np.argmax(labels, 1)) / predictions.shape[0])\n\ndef test_graph(graph_path, use_dropout):\n    tf.reset_default_graph()\n    graph_def = tf.GraphDef()\n    \n    with tf.gfile.FastGFile(graph_path, 'rb') as f:\n        graph_def.ParseFromString(f.read())\n        \n    _ = tf.import_graph_def(graph_def, name='')\n    sess = tf.Session()    \n    prediction_tensor = sess.graph.get_tensor_by_name('final_result:0') \n    \n    feed_dict = {'input:0': mnist.test.images[:256]}\n    if use_dropout:\n        feed_dict['keep_prob:0'] = 1.0\n        \n    predictions = sess.run(prediction_tensor, feed_dict)\n    result = accuracy(predictions, mnist.test.labels[:256])\n    return result",
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": "Extracting /tmp/data/train-images-idx3-ubyte.gz\nExtracting /tmp/data/train-labels-idx1-ubyte.gz\nExtracting /tmp/data/t10k-images-idx3-ubyte.gz\nExtracting /tmp/data/t10k-labels-idx1-ubyte.gz\n"
        }
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      "cell_type": "code",
      "source": "# read frozen graph and display nodes\ngraph = tf.GraphDef()\nwith tf.gfile.Open('./frozen_model.pb', 'r') as f:\n    data = f.read()\n    graph.ParseFromString(data)\n    \ndisplay_nodes(graph.node)",
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": "0 input Placeholder\n1 keep_prob Placeholder\n2 Variable Const\n3 Variable/read Identity\n└─── 0 ─ Variable\n4 Variable_1 Const\n5 Variable_1/read Identity\n└─── 0 ─ Variable_1\n6 Variable_2 Const\n7 Variable_2/read Identity\n└─── 0 ─ Variable_2\n8 Variable_3 Const\n9 Variable_3/read Identity\n└─── 0 ─ Variable_3\n10 Variable_4 Const\n11 Variable_4/read Identity\n└─── 0 ─ Variable_4\n12 Variable_5 Const\n13 Variable_5/read Identity\n└─── 0 ─ Variable_5\n14 Variable_6 Const\n15 Variable_6/read Identity\n└─── 0 ─ Variable_6\n16 Variable_7 Const\n17 Variable_7/read Identity\n└─── 0 ─ Variable_7\n18 Reshape/shape Const\n19 Reshape Reshape\n└─── 0 ─ input\n└─── 1 ─ Reshape/shape\n20 Conv2D Conv2D\n└─── 0 ─ Reshape\n└─── 1 ─ Variable/read\n21 BiasAdd BiasAdd\n└─── 0 ─ Conv2D\n└─── 1 ─ Variable_4/read\n22 Relu Relu\n└─── 0 ─ BiasAdd\n23 MaxPool MaxPool\n└─── 0 ─ Relu\n24 Conv2D_1 Conv2D\n└─── 0 ─ MaxPool\n└─── 1 ─ Variable_1/read\n25 BiasAdd_1 BiasAdd\n└─── 0 ─ Conv2D_1\n└─── 1 ─ Variable_5/read\n26 Relu_1 Relu\n└─── 0 ─ BiasAdd_1\n27 MaxPool_1 MaxPool\n└─── 0 ─ Relu_1\n28 Reshape_1/shape Const\n29 Reshape_1 Reshape\n└─── 0 ─ MaxPool_1\n└─── 1 ─ Reshape_1/shape\n30 MatMul MatMul\n└─── 0 ─ Reshape_1\n└─── 1 ─ Variable_2/read\n31 Add Add\n└─── 0 ─ MatMul\n└─── 1 ─ Variable_6/read\n32 Relu_2 Relu\n└─── 0 ─ Add\n33 dropout/Shape Shape\n└─── 0 ─ Relu_2\n34 dropout/random_uniform/min Const\n35 dropout/random_uniform/max Const\n36 dropout/random_uniform/RandomUniform RandomUniform\n└─── 0 ─ dropout/Shape\n37 dropout/random_uniform/sub Sub\n└─── 0 ─ dropout/random_uniform/max\n└─── 1 ─ dropout/random_uniform/min\n38 dropout/random_uniform/mul Mul\n└─── 0 ─ dropout/random_uniform/RandomUniform\n└─── 1 ─ dropout/random_uniform/sub\n39 dropout/random_uniform Add\n└─── 0 ─ dropout/random_uniform/mul\n└─── 1 ─ dropout/random_uniform/min\n40 dropout/add Add\n└─── 0 ─ keep_prob\n└─── 1 ─ dropout/random_uniform\n41 dropout/Floor Floor\n└─── 0 ─ dropout/add\n42 dropout/Div Div\n└─── 0 ─ Relu_2\n└─── 1 ─ keep_prob\n43 dropout/mul Mul\n└─── 0 ─ dropout/Div\n└─── 1 ─ dropout/Floor\n44 MatMul_1 MatMul\n└─── 0 ─ dropout/mul\n└─── 1 ─ Variable_3/read\n45 Add_1 Add\n└─── 0 ─ MatMul_1\n└─── 1 ─ Variable_7/read\n46 final_result Softmax\n└─── 0 ─ Add_1\n"
        }
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      "cell_type": "code",
      "source": "# Connect 'MatMul_1' with 'Relu_2'\ngraph.node[44].input[0] = 'Relu_2' # 44 -> MatMul_1\n# Remove dropout nodes\nnodes = graph.node[:33] + graph.node[44:] # 33 -> MatMul_1 \ndel nodes[1] # 1 -> keep_prob\n\n# Save graph\noutput_graph = graph_pb2.GraphDef()\noutput_graph.node.extend(nodes)\nwith tf.gfile.GFile('./frozen_model_without_dropout.pb', 'w') as f:\n    f.write(output_graph.SerializeToString())",
      "execution_count": 3,
      "outputs": []
    },
    {
      "metadata": {
        "collapsed": false,
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      "cell_type": "code",
      "source": "# test graph via simple test\nresult_1 = test_graph('./frozen_model.pb', use_dropout=True)\nresult_2 = test_graph('./frozen_model_without_dropout.pb', use_dropout=False)\n\nprint('with dropout:    %f' % result_1)\nprint('without dropout: %f' % result_2)",
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": "with dropout:    80.859375\nwithout dropout: 80.859375\n"
        }
      ]
    },
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