class_docstr: The base class for audio classifier models.
code: def training_step(self, batch: List[paddle.Tensor], batch_idx: int):
      if self.task == "sound-cls":
          predictions, avg_loss, metric = self(
              feats=batch[0], labels=batch[1]
          )
      else:
          raise NotImplementedError
  
      self.metric.reset()
      return {"loss": avg_loss, "metrics": metric}
  
file_path: PaddleHub/paddlehub/module/audio_module.py
imports: from collections import OrderedDict
  from typing import List, Tuple
  import numpy
  import paddle
  from paddlehub.module.module import RunModule, runnable, serving
  from paddlehub.utils.utils import extract_melspectrogram
label_desc: Use image node_id 2 for calling the AudioClassifierModule obj's underlying member method code with example usage: obj.training_step(batch, batch_idx) and returns: dict