code: def test_no_crash_on_empty_bisections(algorithm):
      # Non-regression test for:
      # https://github.com/scikit-learn/scikit-learn/issues/27081
      rng = np.random.RandomState(0)
      X_train = rng.rand(3000, 10)
      bkm = BisectingKMeans(n_clusters=10, algorithm=algorithm).fit(
          X_train
      )
  
      # predict on scaled data to trigger pathologic case
      # where the inner mask leads to empty bisections.
      X_test = 50 * rng.rand(100, 10)
      labels = bkm.predict(X_test)  # should not crash with idiv by 0
      assert np.isin(np.unique(labels), np.arange(10)).all()
  
file_path: scikit-learn/sklearn/cluster/tests/test_bisect_k_means.py
imports: import numpy
  import pytest
  from sklearn.cluster import BisectingKMeans
  from sklearn.metrics import v_measure_score
  from sklearn.utils._testing import assert_allclose, assert_array_equal
  from sklearn.utils.fixes import CSR_CONTAINERS
label_desc: Use image node_id 8 for calling a global function with example usage: test_no_crash_on_empty_bisections(algorithm) without return types