code: def reset_parameters(self):
      gain = nn.init.calculate_gain("relu")
      nn.init.xavier_uniform_(self.Q.weight, gain=gain)
      nn.init.xavier_uniform_(self.W.weight, gain=gain)
      nn.init.constant_(self.Q.bias, 0)
      nn.init.constant_(self.W.bias, 0)
  
imports: import argparse
  import pickle
  import time
  import dgl
  import dgl.function
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.utils.data import DataLoader, IterableDataset
  from ..None import utils
label_desc: Use image node_id 2 for calling the WeightedSAGEConv obj's underlying member method code with example usage: obj.reset_parameters() without return types