code: def forward(self, x):
      if len(x.shape) == 1:
          x = x.unsqueeze(0)
  
      fbank = compute_log_fbank(
          x
      )  # x: waveform tensors with (B, T) shape
      norm_fbank = normalize(fbank)
      logits = self.model(norm_fbank).squeeze(1)
  
      return logits
  
file_path: PaddleHub/modules/audio/language_identification/ecapa_tdnn_common_language/module.py
imports: import os
  import re
  from typing import List
  from typing import Union
  import numpy
  import paddle
  import paddleaudio
  from .ecapa_tdnn import Classifier
  from .ecapa_tdnn import ECAPA_TDNN
  from .feature import compute_log_fbank
  from .feature import normalize
  from paddlehub.module.module import moduleinfo
  from paddlehub.utils.log import logger
label_desc: Use image node_id 4 for calling the LanguageIdentification obj's underlying member method code with example usage: obj.forward(x) and returns: logits