code: def get_parser():
      """Construct the parser."""
      parser = argparse.ArgumentParser(
          description=__doc__,
          formatter_class=argparse.ArgumentDefaultsHelpFormatter,
      )
      parser.add_argument(
          "--sample_rate",
          type=int,
          default=16000,
          help="Sampling rate.",
      )
      parser.add_argument(
          "--all",
          action="store_true",
          help="Plot every filter in its own plot.",
      )
      parser.add_argument(
          "--filetype",
          type=str,
          default="png",
          help="Filetype (svg, png).",
      )
      parser.add_argument(
          "--filter-key",
          type=str,
          default="preencoder.filters.f",
          help="Name of the torch module the Sinc filter parameters are stored"
          " within the model file.",
      )
      parser.add_argument(
          "--scale",
          type=str,
          default="mel",
          choices=["mel", "bark"],
          help="Filter bank initialization values.",
      )
      parser.add_argument(
          "model_path",
          type=str,
          help="Path to the trained model file (*.pth).",
      )
      parser.add_argument(
          "out_folder",
          type=Path,
          nargs="?",
          default=Path("plot_sinc_filters").absolute(),
          help="Output folder to save the plots in.",
      )
      return parser
  
file_path: espnet/egs2/mls/asr2/pyscripts/utils/plot_sinc_filters.py
imports: import argparse
  import sys
  from pathlib import Path
  import matplotlib.pyplot
  import numpy
  import torch
label_desc: Use image node_id 1 for calling a global function with example usage: get_parser() and returns: parser