code: def hetero_data():
      data = HeteroData()
      data["paper"].x = torch.randn(8, 16)
      data["author"].x = torch.randn(10, 8)
  
      data["paper", "paper"].edge_index = get_random_edge_index(
          8, 8, 10
      )
      data["paper", "paper"].edge_attr = torch.randn(10, 16)
      data["paper", "author"].edge_index = get_random_edge_index(
          8, 10, 10
      )
      data["paper", "author"].edge_attr = torch.randn(10, 8)
      data["author", "paper"].edge_index = get_random_edge_index(
          10, 8, 10
      )
      data["author", "paper"].edge_attr = torch.randn(10, 8)
  
      return data
  
file_path: pytorch_geometric/test/explain/conftest.py
imports: from typing import Optional
  import pytest
  import torch
  from torch_geometric.data import Data, HeteroData
  from torch_geometric.explain import Explanation
  from torch_geometric.explain.config import MaskType
  from torch_geometric.nn import SAGEConv, to_hetero
  from torch_geometric.testing import get_random_edge_index
label_desc: Use image node_id 2 for calling a global function with example usage: hetero_data() and returns: data