code: def parse_args():
      parser = argparse.ArgumentParser(
          description="Computing TFLite accuracy"
      )
      parser.add_argument(
          "--model",
          required=True,
          help="Path to the model (protocol buffer binary file)",
      )
      parser.add_argument(
          "--scorer",
          required=True,
          help="Path to the external scorer file",
      )
      parser.add_argument(
          "--csv", required=True, help="Path to the CSV source file"
      )
      parser.add_argument(
          "--proc",
          required=False,
          default=cpu_count(),
          type=int,
          help="Number of processes to spawn, defaulting to number of CPUs",
      )
      parser.add_argument(
          "--dump",
          required=False,
          help='Path to dump the results as text file, with one line for each wav: "wav transcription".',
      )
      args, unknown = parser.parse_known_args()
      # Reconstruct argv for absl.flags
      sys.argv = [sys.argv[0]] + unknown
      return args
  
file_path: DeepSpeech/evaluate_tflite.py
imports: from __future__ import absolute_import, division, print_function
  import absl.app
  import argparse
  import numpy
  import wave
  import csv
  import os
  import sys
  from deepspeech import Model
  from deepspeech_training.util.evaluate_tools import calculate_and_print_report
  from deepspeech_training.util.flags import create_flags
  from functools import partial
  from multiprocessing import JoinableQueue, Process, cpu_count, Manager
  from six.moves import zip, range
label_desc: Use image node_id 3 for calling a global function with example usage: parse_args() and returns: args