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 _init_weights(self):
      # NOTE: original init in pytorch/examples
      # initrange = 0.1
      # self.encoder.weight.data.uniform_(-initrange, initrange)
      # self.decoder.bias.data.zero_()
      # self.decoder.weight.data.uniform_(-initrange, initrange)
      # NOTE: our default.py:RNNLM init
      for param in self.parameters():
          param.data.uniform_(-0.1, 0.1)
  
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 4 for calling the SequentialRNNLM obj's underlying member method code with example usage: obj._init_weights() without return types