code: def _get_parser():
      import argparse
  
      parser = argparse.ArgumentParser(
          description="Convert other model file formats to IR format."
      )
  
      parser.add_argument(
          "--srcFramework",
          "-f",
          type=_text_type,
          choices=[
              "caffe",
              "caffe2",
              "cntk",
              "mxnet",
              "keras",
              "tensorflow",
              "tf",
              "torch",
              "torch7",
              "onnx",
              "darknet",
              "coreml",
              "pytorch",
          ],
          help="Source toolkit name of the model to be converted.",
      )
  
      parser.add_argument(
          "--weights",
          "-w",
          "-iw",
          type=_text_type,
          default=None,
          help="Path to the model weights file of the external tool (e.g caffe weights proto binary, keras h5 binary",
      )
  
      parser.add_argument(
          "--network",
          "-n",
          "-in",
          type=_text_type,
          default=None,
          help="Path to the model network file of the external tool (e.g caffe prototxt, keras json",
      )
  
      parser.add_argument(
          "--dstPath",
          "-d",
          "-o",
          type=_text_type,
          required=True,
          help="Path to save the IR model.",
      )
  
      parser.add_argument(
          "--inNodeName",
          "-inode",
          nargs="+",
          type=_text_type,
          default=None,
          help="[Tensorflow] Input nodes' name of the graph.",
      )
  
      parser.add_argument(
          "--dstNodeName",
          "-node",
          nargs="+",
          type=_text_type,
          default=None,
          help="[Tensorflow] Output nodes' name of the graph.",
      )
  
      parser.add_argument(
          "--inputShape",
          nargs="+",
          type=_text_type,
          default=None,
          help="[Tensorflow/MXNet/Caffe2/Torch7] Input shape of model (channel, height, width)",
      )
  
      # Caffe
      parser.add_argument(
          "--caffePhase",
          type=_text_type,
          default="TRAIN",
          help="[Caffe] Convert the specific phase of caffe model.",
      )
  
      # Darknet
      parser.add_argument(
          "--darknetStart",
          type=_text_type,
          choices=["0", "1"],
          help="[Darknet] Parse the darknet model weight file from the start.",
      )
  
      return parser
  
imports: import sys
  import google.protobuf.text_format
  from six import text_type
label_desc: Use image node_id 2 for calling a global function with example usage: _get_parser() and returns: parser