code: def test_precision_recall(dummy_classifier):
      sklearn = pytest.importorskip("sklearn")
      from pkg_resources import parse_version
  
      # note: sklearn fixed the calculation of precision and recall see: https://github.com/scikit-learn/scikit-learn/issues/23213
      *_, y_test, _, y_probas = dummy_classifier
      pr = precision_recall(y_test, y_probas)
  
      assert (
          pr.value.data[0] == [0, 1.0, 1.0]
          if parse_version(sklearn.__version__) < parse_version("1.1")
          else [0, 0.5, 1.0]
      )
  
file_path: wandb/tests/pytest_tests/unit_tests/test_plots.py
imports: import pytest
  from sklearn.naive_bayes import MultinomialNB
  from wandb.plots.heatmap import heatmap
  from wandb.plots.precision_recall import precision_recall
  from wandb.plots.roc import roc
label_desc: Use image node_id 3 for calling a global function with example usage: test_precision_recall(dummy_classifier) without return types