Remove dropout block.

remove_dropout.py

import tensorflow as tf
from tensorflow.core.framework import graph_pb2
import copy

def remove_dropout(input_graph, output_graph):
    """ Remove the dropout block from the model. """
    graph_def = load_graph(input_graph)
    new_graph_def = graph_pb2.GraphDef()

    for node in graph_def.node:
        modified_node = copy.deepcopy(node)
        if node.name.startswith('dropout1') or node.name.startswith('dropout2'):
            continue

        if node.name == "fc2/fc2/batch_norm/batchnorm/mul_1":
            modified_node.input[0] = "mul"
            modified_node.input[1] = "fc2/weights"

        if node.name == "logits/logits/batch_norm/batchnorm/mul_1":
            modified_node.input[0] = "fc2/activation"
            modified_node.input[1] = "logits/weights"

        new_graph_def.node.extend([modified_node])

    # save the graph
    with tf.gfile.GFile(output_graph, "wb") as f:
        f.write(new_graph_def.SerializeToString())