class_docstr: Container module with an encoder, a recurrent module, and a decoder.
code: def forward(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: skorch/examples/word_language_model/model.py
imports: import torch.nn
  from torch.autograd import Variable
label_desc: Use image node_id 3 for calling the RNNModel obj's underlying member method code with example usage: obj.forward(input, hidden) and returns: decoded,  hidden