class_docstr: Sequential RNNLM.
  
  See also:
      https://github.com/pytorch/examples/blob/4581968193699de14b56527296262dd76ab43557/word_language_model/model.py
class_docstr_tok: ["Sequential","RNNLM",".","See","also",":","https",":","\/\/github.com\/pytorch\/examples\/blob\/4581968193699de14b56527296262dd76ab43557\/word_language_model\/model.py"]
code: def _before_loss(self, input, hidden):
      emb = self.drop(self.encoder(input))
      output, hidden = self.rnn(emb, hidden)
      output = self.drop(output)
      decoded = self.decoder(
          output.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/espnet/nets/pytorch_backend/lm/seq_rnn.py
imports: import torch
  import torch.nn
  import torch.nn.functional
  from espnet.nets.lm_interface import LMInterface
label_desc: Use image node_id 6 for calling the SequentialRNNLM obj's underlying member method code with example usage: obj._before_loss(input, hidden) and returns: decoded,  hidden