code: def test_sensitivity_specificity_support_errors():
      y_true, y_pred, _ = make_prediction(binary=True)
  
      # Bad pos_label
      with pytest.raises(ValueError):
          sensitivity_specificity_support(
              y_true, y_pred, pos_label=2, average="binary"
          )
  
      # Bad average option
      with pytest.raises(ValueError):
          sensitivity_specificity_support(
              [0, 1, 2], [1, 2, 0], average="mega"
          )
  
imports: from functools import partial
  import numpy
  import pytest
  from sklearn import datasets, svm
  from sklearn.metrics import accuracy_score, average_precision_score, brier_score_loss, cohen_kappa_score, jaccard_score, precision_score, recall_score, roc_auc_score
  from sklearn.preprocessing import label_binarize
  from sklearn.utils._testing import assert_allclose, assert_array_equal, assert_no_warnings
  from sklearn.utils.validation import check_random_state
  from imblearn.metrics import classification_report_imbalanced, geometric_mean_score, macro_averaged_mean_absolute_error, make_index_balanced_accuracy, sensitivity_score, sensitivity_specificity_support, specificity_score
label_desc: Use image node_id 7 for calling a global function with example usage: test_sensitivity_specificity_support_errors() without return types