code: def GetArgumentParser():
      parser = argparse.ArgumentParser(
          description="Embedding generation benchmark."
      )
  
      parser.add_argument(
          "--embedding_size",
          type=int,
          default=512,
          help="Embedding size",
      )
      parser.add_argument(
          "--batch_size", type=int, default=16, help="The batch size."
      )
      parser.add_argument(
          "--data_size",
          type=int,
          default=10000,
          help="Number of sequences to generate",
      )
      parser.add_argument(
          "--seq_length",
          type=int,
          default=128,
          help="Max sequence length",
      )
      parser.add_argument(
          "--iters_to_report",
          type=int,
          default=20,
          help="Number of iterations to report progress",
      )
      parser.add_argument(
          "--implementation",
          type=str,
          default="sinusoid",
          help="'table' or 'sinusoid'",
      )
      return parser
  
file_path: pytorch/caffe2/python/embedding_generation_benchmark.py
imports: from caffe2.proto import caffe2_pb2
  from caffe2.python import workspace, core, utils, model_helper
  import argparse
  import numpy
  import time
  import logging
label_desc: Use image node_id 6 for calling a global function with example usage: GetArgumentParser() and returns: parser