code: def test_validate_explanation(data):
      explanation = create_random_explanation(data)
      explanation.validate(raise_on_error=True)
  
      with pytest.raises(ValueError, match="with 5 nodes"):
          explanation = create_random_explanation(
              data, node_mask_type="object"
          )
          explanation.x = torch.randn(5, 5)
          explanation.validate(raise_on_error=True)
  
      with pytest.raises(ValueError, match="with 4 features"):
          explanation = create_random_explanation(data, "attributes")
          explanation.x = torch.randn(4, 4)
          explanation.validate(raise_on_error=True)
  
      with pytest.raises(ValueError, match="with 7 edges"):
          explanation = create_random_explanation(
              data, edge_mask_type="object"
          )
          explanation.edge_index = torch.randint(0, 4, (2, 7))
          explanation.validate(raise_on_error=True)
  
file_path: pytorch_geometric/test/explain/test_explanation.py
imports: import os.path
  from typing import Optional, Union
  import pytest
  import torch
  from torch_geometric.data import Data
  from torch_geometric.explain import Explanation
  from torch_geometric.explain.config import MaskType
  from torch_geometric.testing import withPackage
label_desc: Use image node_id 3 for calling a global function with example usage: test_validate_explanation(data) without return types