code: def init_weights(self):
      w = (
          param.data
          for name, param in self.named_parameters()
          if "weight" in name
      )
      b = (
          param.data
          for name, param in self.named_parameters()
          if "bias" in name
      )
      nn.init.uniform_(self.word_embeds.weight.data, a=-0.5, b=0.5)
      for t in w:
          nn.init.xavier_uniform_(t)
      for t in b:
          nn.init.constant_(t, 0)
  
file_path: neuralcoref/neuralcoref/train/model.py
imports: import os
  import numpy
  import torch
  import torch.nn
  import torch.utils.data
label_desc: Use image node_id 2 for calling the Model obj's underlying member method code with example usage: obj.init_weights() without return types