code: def test_float32_float64_equivalence(csr_container):
      """Check that the results are the same between float32 and float64."""
      rng = np.random.RandomState(0)
      X = rng.rand(10, 2)
  
      if csr_container is not None:
          X[X < 0.8] = 0
          X = csr_container(X)
  
      km64 = BisectingKMeans(n_clusters=3, random_state=0).fit(X)
      km32 = BisectingKMeans(n_clusters=3, random_state=0).fit(
          X.astype(np.float32)
      )
  
      assert_allclose(km32.cluster_centers_, km64.cluster_centers_)
      assert_array_equal(km32.labels_, km64.labels_)
  
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 7 for calling a global function with example usage: test_float32_float64_equivalence(csr_container) without return types