code: def main(_):
      counts = 0.0
      sum_feats = None
      square_sum_feats = None
  
      idx = 0
      with open(FLAGS.path_file, "r") as fin:
          for idx, path in enumerate(fin, 1):
              path = path.strip()
              feat = np.load(path)
              if sum_feats is None and square_sum_feats is None:
                  feat_shape = feat.shape[1:]
                  logging.info(f"feat_shape: {feat_shape}")
                  # Accumulate in double precision
                  sum_feats = np.zeros(feat_shape, dtype=np.float64)
                  square_sum_feats = np.zeros(
                      feat_shape, dtype=np.float64
                  )
  
              counts += feat.shape[0]
              sum_feats += feat.sum(axis=0)
              square_sum_feats += np.sum(np.power(feat, 2), axis=0)
  
      logging.info(f"sums: {sum_feats}")
      logging.info(f"square: {square_sum_feats}")
      logging.info(f"counts: {counts}")
      mean = sum_feats / counts
      var = square_sum_feats / counts - np.power(mean, 2)
  
      np.save(FLAGS.cmvn_path, (mean, var))
  
imports: import numpy
  from absl import logging
  from absl import app
  from absl import flags
label_desc: Use image node_id 1 for calling a global function with example usage: main(_) without return types