code: def test_text_classification_introspective_rationale(notebooks, tmp):
      notebook_path = notebooks["tc_introspective_rationale"]
      pm.execute_notebook(
          notebook_path,
          OUTPUT_NOTEBOOK,
          kernel_name=KERNEL_NAME,
          parameters=dict(
              DATA_FOLDER=tmp,
              CUDA=torch.cuda.is_available(),
              QUICK_RUN=False,
              MODEL_SAVE_DIR=tmp,
          ),
      )
      result = sb.read_notebook(OUTPUT_NOTEBOOK).scraps.data_dict
      print(result)
      assert pytest.approx(result["accuracy"], 0.72, abs=ABS_TOL)
      assert pytest.approx(result["anti_accuracy"], 0.69, abs=ABS_TOL)
      assert pytest.approx(result["sparsity"], 0.17, abs=ABS_TOL)
  
imports: import pytest
  import torch
  import papermill
  import scrapbook
label_desc: Use image node_id 1 for calling a global function with example usage: test_text_classification_introspective_rationale(notebooks, tmp) without return types