code: def get_features(self, x):
      x = x.to(self.device)
      if self.should_normalize:
          x = F.layer_norm(x, x.shape)
      x = x.view(1, -1)
  
      feat = []
      for start in range(0, x.size(1), self.max_chunk):
          x_chunk = x[:, start : start + self.max_chunk]
          feat_chunk, _ = self.model.extract_features(
              source=x_chunk,
              padding_mask=None,
              mask=False,
              output_layer=self.layer,
          )
          feat.append(feat_chunk)
      return torch.cat(feat, 1).squeeze(0).cpu()
  
file_path: textlesslib/textless/data/hubert_feature_reader.py
imports: import torch
  import fairseq
  import torch.nn.functional
label_desc: Use image node_id 7 for calling the HubertFeatureReader obj's underlying member method code with example usage: obj.get_features(x) and returns: torch