class_docstr: Container module with an encoder, a recurrent module, and a decoder.
class_docstr_tok: ["Container","module","with","an","encoder",",","a","recurrent","module",",","and","a","decoder","."]
code: def init_weights(self):
      initrange = 0.1
      self.encoder.weight.data.uniform_(-initrange, initrange)
      self.decoder.bias.data.fill_(0)
      self.decoder.weight.data.uniform_(-initrange, initrange)
  
file_path: pytorch/test/onnx/model_defs/word_language_model.py
imports: from typing import Optional, Tuple
  import torch
  import torch.nn
  from torch import Tensor
label_desc: Use image node_id 3 for calling the RNNModel obj's underlying member method code with example usage: obj.init_weights() without return types