code: def test_data():
      x = torch.Tensor([[0.0, 0.1], [0.2, 0.3], [0.4, 0.5]])
      edge_index = torch.tensor([[0, 1, 2, 2], [1, 0, 1, 2]])
      edge_weight = torch.tensor([0.5, 0.2, 0.3, 0.4])
      adj_t = SparseTensor(
          row=edge_index[0], col=edge_index[1], value=edge_weight
      )
  
      return Data(x=x, edge_index=edge_index, adj_t=adj_t)
  
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 1 for calling a global function with example usage: test_data() and returns: Data