Run different transformation on tensorflow model

transform_graph.py

import tensorflow as tf
from tensorflow.tools.graph_transforms import TransformGraph

def transform_graph(input_graph, output_graph):
    """ Use to run different transform function on the input graph and generate a output graph. """
    with tf.gfile.GFile(input_graph, 'rb') as fid:
        od_graph_def = tf.GraphDef()
        serialized_graph = fid.read()
        od_graph_def.ParseFromString(serialized_graph)
        od_graph_def = TransformGraph(od_graph_def, ['input_placeholder/input_image'], ['predicated_output'], 
            ['strip_unused_nodes(type=float, shape="1,28,28,1")', 'remove_nodes(op=Identity, op=CheckNumerics, op=Switch)', 
            'fold_constants(ignore_errors=true)', 'fold_batch_norms', 'fold_old_batch_norms', 'sort_by_execution_order'])

        tf.io.write_graph(od_graph_def, "", output_graph, as_text=False)


if __name__ == '__main__':
    frozen_graph = "/Users/dibyaranjan/Python/Projects/LicensePlate/OCR_Model/AlphaDigitAdam30Epochs36Classes_V2/frozen_inference_graph.pb"
    output_transform_graph = "/Users/dibyaranjan/Python/Projects/LicensePlate/OCR_Model/AlphaDigitAdam30Epochs36Classes_V2/transformed_graph.pb"
    transform_graph(frozen_graph, output_transform_graph)