code: def reset_parameters(self):
      gain = nn.init.calculate_gain("relu")
      nn.init.xavier_normal_(self.src_fc.weight, gain=gain)
      if self.dst_fc is not None:
          nn.init.xavier_normal_(self.dst_fc.weight, gain=gain)
  
      nn.init.xavier_normal_(self.attn_src_fc.weight, gain=gain)
      if self.attn_dst_fc is not None:
          nn.init.xavier_normal_(self.attn_dst_fc.weight, gain=gain)
      if self.attn_edge_fc is not None:
          nn.init.xavier_normal_(self.attn_edge_fc.weight, gain=gain)
  
      if self.bias is not None:
          nn.init.zeros_(self.bias)
  
imports: import math
  from functools import partial
  import dgl.function
  import dgl.nn.pytorch
  import torch
  import torch.nn
  import torch.nn.functional
  from dgl import function
  from dgl._ffi.base import DGLError
  from dgl.base import ALL
  from dgl.nn.pytorch.utils import Identity
  from dgl.ops import edge_softmax
  from dgl.utils import expand_as_pair
  from torch.nn import init
  from torch.utils.checkpoint import checkpoint
label_desc: Use image node_id 2 for calling the GATConv obj's underlying member method code with example usage: obj.reset_parameters() without return types