class_docstr: Container module with an encoder, a recurrent module, and a decoder.
code: def init_hidden(self, bsz):
      weight = next(self.parameters()).data
      if self.rnn_type == "LSTM":
          return (
              Variable(
                  weight.new(self.nlayers, bsz, self.nhid).zero_()
              ),
              Variable(
                  weight.new(self.nlayers, bsz, self.nhid).zero_()
              ),
          )
      else:
          return Variable(
              weight.new(self.nlayers, bsz, self.nhid).zero_()
          )
  
file_path: skorch/examples/word_language_model/model.py
imports: import torch.nn
  from torch.autograd import Variable
label_desc: Use image node_id 4 for calling the RNNModel obj's underlying member method code with example usage: obj.init_hidden(bsz) and returns: Variable,  Variable, Variable