code: def get_parser():
      parser = argparse.ArgumentParser(description="apply clusters")
      # fmt: off
      parser.add_argument('data', help='location of tsv files')
      parser.add_argument('--split', help='split to process', required=True)
      parser.add_argument('--labels', help='split to process', default="phn")
      parser.add_argument('--path', help='path to pca and centroids', required=True)
      parser.add_argument('--checkpoint', type=str, help='checkpoint for wav2vec model (if using wav2vec features)', required=True)
      parser.add_argument('--layer', '-l', type=int, help='which layer to read', default=14)
      parser.add_argument('--max-tsz', type=int, help='batch kmeans up to this much', default=14)
      # fmt: on
  
      return parser
  
file_path: fairseq/examples/wav2vec/unsupervised/scripts/wav2vec_apply_cluster_faiss.py
imports: import argparse
  import os
  import os.path
  import numpy
  import tqdm
  import torch
  import sys
  import faiss
  import torch.nn.functional
  from wav2vec_cluster_faiss import parse_faiss_specs, Wav2VecFeatureReader
label_desc: Use image node_id 1 for calling a global function with example usage: get_parser() and returns: parser