code: def TransformGraph(input_graph_def, inputs, outputs, transforms):
      """Python wrapper for the Graph Transform Tool.
  
      Gives access to all graph transforms available through the command line tool.
      See documentation at https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/graph_transforms/README.md
      for full details of the options available.
  
      Args:
        input_graph_def: GraphDef object containing a model to be transformed.
        inputs: List of node names for the model inputs.
        outputs: List of node names for the model outputs.
        transforms: List of strings containing transform names and parameters.
  
      Returns:
        New GraphDef with transforms applied.
      """
  
      input_graph_def_string = input_graph_def.SerializeToString()
      inputs_string = compat.as_bytes(",".join(inputs))
      outputs_string = compat.as_bytes(",".join(outputs))
      transforms_string = compat.as_bytes(" ".join(transforms))
      output_graph_def_string = TransformGraphWithStringInputs(
          input_graph_def_string,
          inputs_string,
          outputs_string,
          transforms_string,
      )
      output_graph_def = graph_pb2.GraphDef()
      output_graph_def.ParseFromString(output_graph_def_string)
      return output_graph_def
  
imports: from tensorflow.core.framework import graph_pb2
  from tensorflow.python.util import compat
  from tensorflow.python.util._pywrap_transform_graph import TransformGraphWithStringInputs
label_desc: Use image node_id 1 for calling a global function with example usage: TransformGraph(input_graph_def, inputs, outputs, transforms) and returns: output_graph_def