code: def reset_parameters(self):
      gain = nn.init.calculate_gain("relu")
      nn.init.xavier_normal_(self.fc.weight, gain=gain)
      nn.init.xavier_normal_(self.p, gain=gain)
      nn.init.xavier_normal_(self.attn_l, gain=gain)
      nn.init.xavier_normal_(self.attn_r, gain=gain)
      if self.residual:
          nn.init.xavier_normal_(self.residual_module.weight, gain=gain)
  
file_path: dgl/examples/pytorch/hardgat/hgao.py
imports: from functools import partial
  import dgl
  import dgl.function
  import torch
  import torch.nn
  import torch.nn.functional
  from dgl.base import DGLError
  from dgl.nn.pytorch import edge_softmax
  from dgl.nn.pytorch.utils import Identity
  from dgl.sampling import select_topk
label_desc: Use image node_id 2 for calling the HardGAO obj's underlying member method code with example usage: obj.reset_parameters() without return types