code: def normalize(
      x: paddle.Tensor,
      global_mean: paddle.Tensor = None,
      global_std: paddle.Tensor = None,
  ):
      for i in range(x.shape[0]):  # (B, ...)
          if global_mean is None and global_std is None:
              mean, std = compute_stats(x[i])
              x[i] = (x[i] - mean) / std
          else:
              x[i] = (x[i] - global_mean) / global_std
      return x
  
file_path: PaddleHub/modules/audio/language_identification/ecapa_tdnn_common_language/feature.py
imports: import paddle
  import paddleaudio
  from paddleaudio.features.spectrum import hz_to_mel
  from paddleaudio.features.spectrum import mel_to_hz
  from paddleaudio.features.spectrum import power_to_db
  from paddleaudio.features.spectrum import Spectrogram
  from paddleaudio.features.window import get_window
label_desc: Use image node_id 4 for calling a global function with example usage: normalize(x, global_mean, global_std) and returns: x