class_docstr: Base class for encoders.
code: def forward_non_torchscript(self, net_input: Dict[str, Tensor]):
      encoder_input = {
          k: v
          for k, v in net_input.items()
          if k != "prev_output_tokens"
      }
      return self.forward(**encoder_input)
  
file_path: fairseq/fairseq/models/fairseq_encoder.py
imports: from typing import Dict, List, NamedTuple, Optional
  import torch
  import torch.nn
  from torch import Tensor
label_desc: Use image node_id 4 for calling the FairseqEncoder obj's underlying member method code with example usage: obj.forward_non_torchscript(net_input) and returns: self