code: def test_onehot_categories(client):
      X = DataFrame({"chars": ["a", "b"], "int": [0, 2]})
      X = dask_cudf.from_cudf(X, npartitions=2)
      cats = DataFrame({"chars": ["a", "b", "c"], "int": [0, 1, 2]})
      enc = OneHotEncoder(categories=cats, sparse=False)
      ref = cp.array(
          [
              [1.0, 0.0, 0.0, 1.0, 0.0, 0.0],
              [0.0, 1.0, 0.0, 0.0, 0.0, 1.0],
          ]
      )
      res = enc.fit_transform(X)
      cp.testing.assert_array_equal(res.compute(), ref)
  
file_path: cuml/python/cuml/tests/dask/test_dask_one_hot_encoder.py
imports: from cuml.internals.safe_imports import cpu_only_import_from
  from sklearn.preprocessing import OneHotEncoder
  from cuml.testing.utils import stress_param, generate_inputs_from_categories, assert_inverse_equal, from_df_to_numpy
  from cuml.dask.preprocessing import OneHotEncoder
  import dask.array
  from cuml.internals.safe_imports import cpu_only_import
  from cudf import DataFrame, Series
  import pytest
  from cuml.internals.safe_imports import gpu_only_import
label_desc: Use image node_id 3 for calling a global function with example usage: test_onehot_categories(client) without return types