code: def compute_stats(
      x: paddle.Tensor,
      mean_norm: bool = True,
      std_norm: bool = False,
      eps: float = 1e-10,
  ):
      if mean_norm:
          current_mean = paddle.mean(x, axis=0)
      else:
          current_mean = paddle.to_tensor([0.0])
  
      if std_norm:
          current_std = paddle.std(x, axis=0)
      else:
          current_std = paddle.to_tensor([1.0])
  
      current_std = paddle.maximum(
          current_std, eps * paddle.ones_like(current_std)
      )
  
      return current_mean, current_std
  
file_path: PaddleHub/modules/audio/speaker_recognition/ecapa_tdnn_voxceleb/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 3 for calling a global function with example usage: compute_stats(x, mean_norm, std_norm, eps) and returns: current_mean,  current_std