code: def test_mogonet_gcn_conv_reset_parameters():
      in_channels = 2
      out_channels = 8
      conv = MogonetGCNConv(
          in_channels=in_channels, out_channels=out_channels
      )
      # Set parameters to a fixed value
      with torch.no_grad():
          for param in conv.parameters():
              param.fill_(1.0)
      # Reset the parameters
      conv.reset_parameters()
      # Check that the parameters are now different
      for param in conv.parameters():
          assert torch.any(param != 1.0)
  
file_path: pykale/tests/embed/test_mogonet.py
imports: import pytest
  import torch
  from torch_geometric.data import Data
  from torch_sparse import SparseTensor
  from kale.embed.mogonet import MogonetGCN, MogonetGCNConv
label_desc: Use image node_id 4 for calling a global function with example usage: test_mogonet_gcn_conv_reset_parameters() without return types