code: def reset_parameters(self):
      gain = nn.init.calculate_gain("sigmoid")
      nn.init.xavier_uniform_(self.s, gain=gain)
  
imports: import argparse
  import dgl.function
  import numpy
  import torch
  from dgl.data import CiteseerGraphDataset, CoraGraphDataset, PubmedGraphDataset
  from torch import nn
  from torch.nn import functional, Parameter
  from tqdm import trange
  from utils import evaluate, generate_random_seeds, set_random_state
label_desc: Use image node_id 2 for calling the DAGNNConv obj's underlying member method code with example usage: obj.reset_parameters() without return types