code: def _get_parser(use_v2_converter):
      """Returns an ArgumentParser for tflite_convert.
  
      Args:
        use_v2_converter: Indicates which converter to return.
      Return: ArgumentParser.
      """
      parser = argparse.ArgumentParser(
          description=(
              "Command line tool to run TensorFlow Lite Converter."
          )
      )
  
      # Output file flag.
      parser.add_argument(
          "--output_file",
          type=str,
          help="Full filepath of the output file.",
          required=True,
      )
  
      if use_v2_converter:
          _get_tf2_flags(parser)
      else:
          _get_tf1_flags(parser)
  
      parser.add_argument(
          "--experimental_new_converter",
          action=_ParseBooleanFlag,
          nargs="?",
          default=True,
          help=(
              "Experimental flag, subject to change. Enables MLIR-based "
              "conversion instead of TOCO conversion. (default True)"
          ),
      )
  
      parser.add_argument(
          "--experimental_new_quantizer",
          action=_ParseBooleanFlag,
          nargs="?",
          help=(
              "Experimental flag, subject to change. Enables MLIR-based "
              "quantizer instead of flatbuffer conversion. (default True)"
          ),
      )
      return parser
  
imports: import argparse
  import os
  import sys
  import warnings
  from absl import app
  import tensorflow
  from tensorflow.lite.python import lite
  from tensorflow.lite.python.convert import register_custom_opdefs
  from tensorflow.lite.toco import toco_flags_pb2
  from tensorflow.lite.toco.logging import gen_html
  from tensorflow.python import tf2
  from tensorflow.python.framework import dtypes
  from tensorflow.python.platform import gfile
  from tensorflow.python.util import keras_deps
label_desc: Use image node_id 11 for calling a global function with example usage: _get_parser(use_v2_converter) and returns: parser