code: def test_classification(self):
      self._test_classification(roc_auc_score, True)
      self._test_classification(roc_auc_score, False)
  
      self._test_classification(average_precision_score, True)
      self._test_classification(average_precision_score, False)
  
      two_skl_metrics = [roc_auc_score, average_precision_score]
      self._test_classification(two_skl_metrics, True)
      self._test_classification(two_skl_metrics, False)
  
file_path: poutyne/tests/framework/metrics/test_sklearn_metrics.py
imports: from itertools import repeat
  from unittest import TestCase, skipIf
  import numpy
  import torch
  from torch.utils.data import DataLoader
  from poutyne import SKLearnMetrics, TensorDataset
label_desc: Use image node_id 3 for calling the SKLearnMetricsTest obj's underlying member method code with example usage: obj.test_classification() without return types