code: def test_predict_proba(dataset, datatype, parameters, client):
      n_neighbors, n_parts, batch_size = parameters
      X_train, X_test, y_train, y_test = dataset
  
      l_model = lKNNClf(n_neighbors=n_neighbors)
      l_model.fit(X_train, y_train)
      l_probas = l_model.predict_proba(X_test)
  
      X_train = generate_dask_array(X_train, n_parts)
      X_test = generate_dask_array(X_test, n_parts)
      y_train = generate_dask_array(y_train, n_parts)
  
      if datatype == "dask_cudf":
          X_train = to_dask_cudf(X_train, client)
          X_test = to_dask_cudf(X_test, client)
          y_train = to_dask_cudf(y_train, client)
  
      d_model = dKNNClf(client=client, n_neighbors=n_neighbors)
      d_model.fit(X_train, y_train)
      d_probas = d_model.predict_proba(X_test, convert_dtype=True)
      d_probas = da.compute(d_probas)[0]
  
      if datatype == "dask_cudf":
          d_probas = list(
              map(
                  lambda o: o.to_numpy()
                  if isinstance(o, DataFrame)
                  else o.to_numpy()[..., np.newaxis],
                  d_probas,
              )
          )
  
      check_probabilities(l_probas, d_probas)
  
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 6 for calling a global function with example usage: test_predict_proba(dataset, datatype, parameters, client) without return types