code: def init_weights(self):
      for name, p in self.named_parameters():
          if "bias" in name:
              torch.nn.init.zeros_(p)
          elif "fc1" in name or "fc2" in name:
              torch.nn.init.kaiming_normal_(
                  p, a=0, mode="fan_in", nonlinearity="leaky_relu"
              )
          elif "context" in name:
              torch.nn.init.xavier_uniform_(p)
  
imports: from typing import Dict, List, Optional, Tuple, Union
  import torch
  import torch.nn
  import torch.nn.functional
  from darts.logging import get_logger
  from darts.utils.torch import MonteCarloDropout
label_desc: Use image node_id 2 for calling the _GatedResidualNetwork obj's underlying member method code with example usage: obj.init_weights() without return types