code: def test_onehot_vs_skonehot(client):
      X = DataFrame(
          {"gender": ["Male", "Female", "Female"], "int": [1, 3, 2]}
      )
      skX = from_df_to_numpy(X)
      X = dask_cudf.from_cudf(X, npartitions=2)
  
      enc = OneHotEncoder(sparse=False)
      skohe = SkOneHotEncoder(sparse=False)
  
      ohe = enc.fit_transform(X)
      ref = skohe.fit_transform(skX)
  
      cp.testing.assert_array_equal(ohe.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 1 for calling a global function with example usage: test_onehot_vs_skonehot(client) without return types