code: def check_probabilities(l_probas, d_probas):
      assert len(l_probas) == len(d_probas)
      for i in range(len(l_probas)):
          assert l_probas[i].shape == d_probas[i].shape
          assert np.mean(l_probas[i] == d_probas[i]) > 0.95
  
file_path: cuml/python/cuml/tests/dask/test_dask_kneighbors_classifier.py
imports: from cuml.internals.safe_imports import gpu_only_import
  from cuml.internals.safe_imports import cpu_only_import
  import pytest
  from cuml.testing.utils import unit_param, quality_param, stress_param
  from cuml.neighbors import KNeighborsClassifier
  from cuml.dask.neighbors import KNeighborsClassifier
  from sklearn.datasets import make_multilabel_classification
  from sklearn.datasets import make_classification
  from sklearn.model_selection import train_test_split
  import dask.array
  import dask.dataframe
  from cuml.dask.common.dask_arr_utils import to_dask_cudf
  from cuml.internals.safe_imports import gpu_only_import_from
label_desc: Use image node_id 4 for calling a global function with example usage: check_probabilities(l_probas, d_probas) without return types