code: def forward(self, x: Tensor) -> Tensor:
      r"""
      Args:
          x (torch.Tensor): Tensor of dimension (batch_size, num_features, input_length).
  
      Returns:
          Tensor: Predictor tensor of dimension (batch_size, number_of_classes, input_length).
      """
  
      x = self.acoustic_model(x)
      x = nn.functional.log_softmax(x, dim=1)
      return x
  
imports: from torch import nn, Tensor
label_desc: Use image node_id 2 for calling the Wav2Letter obj's underlying member method code with example usage: obj.forward(x) and returns: x