code: def forward(self, inputs):
      dvecs = []
      for wav in inputs:
          mel = self.get_mel(wav)
          if mel.dim() == 3:
              mel = mel.squeeze(0)
          dvecs += [self.embedder(mel)]
      dvecs = torch.stack(dvecs)
  
      dvec = torch.mean(dvecs, dim=0)
      dvec = dvec / torch.norm(dvec)
  
      return dvec
  
file_path: fairseq/examples/speech_synthesis/preprocessing/speaker_embedder/__init__.py
imports: import librosa
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.utils.data
  import torchaudio
label_desc: Use image node_id 3 for calling the SpkrEmbedder obj's underlying member method code with example usage: obj.forward(inputs) and returns: dvec