code: def main():
      parser = get_parser()
      args = parser.parse_args()
  
      print("Reading features")
      x = []
      with open(args.data, "r") as fp:
          for line in fp.readlines():
              utt_id, feats_path = line.split()
              feats = np.load(feats_path)
              x.append(feats)
  
      x = np.vstack(x)
  
      print("Computing PCA")
      pca = faiss.PCAMatrix(x.shape[-1], args.dim, args.eigen_power)
      pca.train(x)
      b = faiss.vector_to_array(pca.b)
      A = faiss.vector_to_array(pca.A).reshape(pca.d_out, pca.d_in)
  
      os.makedirs(args.output, exist_ok=True)
  
      prefix = str(args.dim)
      if args.eigen_power != 0:
          prefix += f"_{args.eigen_power}"
  
      np.save(osp.join(args.output, f"{prefix}_pca_A"), A.T)
      np.save(osp.join(args.output, f"{prefix}_pca_b"), b)
  
imports: import argparse
  import os
  import os.path
  import faiss
  import numpy
label_desc: Use image node_id 2 for calling a global function with example usage: main() without return types