code: def collect_feats(
      self,
      text: torch.Tensor,
      text_lengths: torch.Tensor,
      **kwargs,
  ) -> Dict[str, torch.Tensor]:
      return {}
  
file_path: espnet/espnet2/lm/espnet_model.py
imports: from typing import Dict, Optional, Tuple
  import torch
  import torch.nn.functional
  from typeguard import check_argument_types
  from espnet2.lm.abs_model import AbsLM
  from espnet2.torch_utils.device_funcs import force_gatherable
  from espnet2.train.abs_espnet_model import AbsESPnetModel
  from espnet.nets.pytorch_backend.nets_utils import make_pad_mask
label_desc: Use image node_id 5 for calling the ESPnetLanguageModel obj's underlying member method code with example usage: obj.collect_feats(text, text_lengths) and returns: dict