code: def get_parser():
      parser = argparse.ArgumentParser()
      parser.add_argument("--km_path", type=str, required=True)
      parser.add_argument("--n_clusters", type=int, required=True)
      parser.add_argument("--seed", default=0, type=int)
      parser.add_argument(
          "--percent",
          default=-1,
          type=float,
          help="sample a subset; -1 for all",
      )
      parser.add_argument("--init", default="k-means++")
      parser.add_argument("--max_iter", default=100, type=int)
      parser.add_argument("--batch_size", default=10000, type=int)
      parser.add_argument("--tol", default=0.0, type=float)
      parser.add_argument("--max_no_improvement", default=100, type=int)
      parser.add_argument("--n_init", default=20, type=int)
      parser.add_argument(
          "--reassignment_ratio", default=0.0, type=float
      )
  
      parser.add_argument(
          "--in_filetype",
          type=str,
          default="sound",
          choices=["mat", "hdf5", "sound.hdf5", "sound"],
          help="Specify the file format for the rspecifier. "
          '"mat" is the matrix format in kaldi',
      )
      parser.add_argument(
          "rspecifier",
          type=str,
          nargs="+",
          help="Read specifier for feats. e.g. ark:some.ark",
      )
      return parser
  
file_path: espnet/egs2/kiritan/svs1/pyscripts/utils/learn_kmeans.py
imports: import argparse
  import logging
  import os
  import random
  import sys
  import joblib
  import numpy
  from sklearn.cluster import MiniBatchKMeans
  from espnet.utils.cli_readers import file_reader_helper
label_desc: Use image node_id 1 for calling a global function with example usage: get_parser() and returns: parser