Convert the input placeholders to Constant

convert_placeholders_to_constant.py

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

def load_graph(filename):
    """ Use to read the tensorflow protobuf graph file. """
    graph_def = tf.GraphDef()
    with tf.gfile.FastGFile(filename, 'rb') as f:
        graph_def.ParseFromString(f.read())
    return graph_def


def convert_to_constant(input_graph, output_graph):
    """ Use to replace the placeholders in graph with Constant nodes. """
    graph_def = load_graph(input_graph)
    keep_prob = tf.constant(1.0, dtype=tf.float32, shape=[], name='keep_prob')
    weight_factor = tf.constant(1.0, dtype=tf.float32, shape=[], name='weight_factor')
    is_training = tf.constant(False, dtype=tf.bool, shape=[], name='is_training')

    new_graph_def = graph_pb2.GraphDef()

    # Iterating over each node in the graph
    for node in graph_def.node:
        if node.name == 'keep_prob':
            new_graph_def.node.extend([keep_prob.op.node_def])

        elif node.name == 'weight_factor':
            new_graph_def.node.extend([weight_factor.op.node_def])

        elif node.name == 'is_training':
            new_graph_def.node.extend([is_training.op.node_def])

        else:
            new_graph_def.node.extend([copy.deepcopy(node)])

    # save new graph
    with tf.gfile.GFile(output_graph, "wb") as f:
        f.write(new_graph_def.SerializeToString())     
        
if __name__ == '__main__':
    output_transform_graph = "/Users/dibyaranjan/Python/Projects/LicensePlate/OCR_Model/AlphaDigitAdam30Epochs36Classes_V2/transformed_graph.pb"
    remove_placeholder_graph = "/Users/dibyaranjan/Python/Projects/LicensePlate/OCR_Model/AlphaDigitAdam30Epochs36Classes_V2/removed_placeholder_graph.pb"
    convert_to_constant(output_transform_graph, remove_placeholder_graph)