code: def parse_arguments():
      parser = ArgumentParser()
      parser.add_argument(
          "--nemo_model",
          type=str,
          default=None,
          required=False,
          help="Path to .nemo file",
      )
      parser.add_argument(
          "--pretrained_model",
          type=str,
          default=None,
          required=False,
          help="Name of a pretrained NeMo file",
      )
      parser.add_argument(
          "--ts_encoder",
          type=str,
          default=None,
          required=False,
          help="Path to ts encoder model",
      )
      parser.add_argument(
          "--ts_decoder",
          type=str,
          default=None,
          required=False,
          help="Path to ts decoder + joint model",
      )
      parser.add_argument(
          "--ts_cfg",
          type=str,
          default=None,
          required=False,
          help="Path to the yaml config of the exported model",
      )
      parser.add_argument(
          "--threshold", type=float, default=0.01, required=False
      )
  
      parser.add_argument(
          "--dataset_manifest",
          type=str,
          default=None,
          required=False,
          help="Path to dataset manifest",
      )
      parser.add_argument(
          "--audio_dir",
          type=str,
          default=None,
          required=False,
          help="Path to directory of audio files",
      )
      parser.add_argument(
          "--audio_type",
          type=str,
          default="wav",
          help="File format of audio",
      )
  
      parser.add_argument(
          "--export",
          action="store_true",
          help="Whether to export the model into torchscript prior to eval",
      )
      parser.add_argument(
          "--max_symbold_per_step",
          type=int,
          default=5,
          required=False,
          help="Number of decoding steps",
      )
      parser.add_argument(
          "--batch_size", type=int, default=32, help="Batchsize"
      )
      parser.add_argument(
          "--log",
          action="store_true",
          help="Log the predictions between pytorch and torchscript",
      )
  
      args = parser.parse_args()
      return args
  
file_path: NeMo/examples/asr/export/transducer/infer_transducer_ts.py
imports: import glob
  import json
  import os
  import tempfile
  from argparse import ArgumentParser
  import torch
  from omegaconf import OmegaConf
  from tqdm import tqdm
  from nemo.collections.asr.metrics.wer import word_error_rate
  from nemo.collections.asr.models import ASRModel
  from nemo.collections.asr.parts.submodules.rnnt_greedy_decoding import TorchscriptGreedyBatchedRNNTInfer
  from nemo.utils import logging
label_desc: Use image node_id 1 for calling a global function with example usage: parse_arguments() and returns: args