class_docstr: Sequential RNNLM.
  
  See also:
      https://github.com/pytorch/examples/blob/4581968193699de14b56527296262dd76ab43557/word_language_model/model.py
code: def forward(
      self, input: torch.Tensor, hidden: torch.Tensor
  ) -> Tuple[torch.Tensor, torch.Tensor]:
      emb = self.drop(self.encoder(input))
      output, hidden = self.rnn(emb, hidden)
      output = self.drop(output)
      decoded = self.decoder(
          output.contiguous().view(
              output.size(0) * output.size(1), output.size(2)
          )
      )
      return (
          decoded.view(output.size(0), output.size(1), decoded.size(1)),
          hidden,
      )
  
file_path: espnet/espnet2/lm/seq_rnn_lm.py
imports: from typing import Tuple, Union
  import torch
  import torch.nn
  from typeguard import check_argument_types
  from espnet2.lm.abs_model import AbsLM
label_desc: Use image node_id 3 for calling the SequentialRNNLM obj's underlying member method code with example usage: obj.forward(input, hidden) and returns: decoded,  hidden