code: def forward(self, x):
      if len(x.shape) == 1:  # x: waveform tensors with (B, T) shape
          x = x.unsqueeze(0)
  
      mfcc = compute_mfcc(x).unsqueeze(1)  # (B, C, n_mels, L)
      logits = self.model(mfcc).squeeze(1)
  
      return logits
  
file_path: PaddleHub/modules/audio/keyword_spotting/kwmlp_speech_commands/module.py
imports: import os
  import numpy
  import paddle
  import paddleaudio
  from .feature import compute_mfcc
  from .kwmlp import KW_MLP
  from paddlehub.module.module import moduleinfo
  from paddlehub.utils.log import logger
label_desc: Use image node_id 4 for calling the KWS obj's underlying member method code with example usage: obj.forward(x) and returns: logits