code: def test_attention_explainer_attentive_fp(check_explanation):
      model = AttentiveFP(
          3, 16, 1, edge_dim=5, num_layers=2, num_timesteps=2
      )
  
      explainer = Explainer(
          model=model,
          algorithm=AttentionExplainer(),
          explanation_type="model",
          edge_mask_type="object",
          model_config=dict(
              mode="binary_classification",
              task_level="node",
              return_type="raw",
          ),
      )
  
      explanation = explainer(
          x, edge_index, edge_attr=edge_attr, batch=batch
      )
      check_explanation(explanation, None, explainer.edge_mask_type)
  
file_path: pytorch_geometric/test/explain/algorithm/test_attention_explainer.py
imports: import pytest
  import torch
  from torch_geometric.explain import AttentionExplainer, Explainer
  from torch_geometric.explain.config import ExplanationType, MaskType
  from torch_geometric.nn import AttentiveFP, GATConv, GATv2Conv, TransformerConv
label_desc: Use image node_id 3 for calling a global function with example usage: test_attention_explainer_attentive_fp(check_explanation) without return types