code: def test_get_prediction(data):
      model = DummyModel()
      assert model.training
  
      explainer = Explainer(
          model,
          algorithm=DummyExplainer(),
          explanation_type="phenomenon",
          node_mask_type="object",
          model_config=dict(
              mode="regression",
              task_level="graph",
          ),
      )
      pred = explainer.get_prediction(data.x, data.edge_index)
      assert model.training
      assert pred.size() == (1,)
  
file_path: pytorch_geometric/test/explain/test_explainer.py
imports: import pytest
  import torch
  from torch_geometric.explain import DummyExplainer, Explainer, Explanation
  from torch_geometric.explain.config import ExplanationType
label_desc: Use image node_id 1 for calling a global function with example usage: test_get_prediction(data) without return types