code: def test_onehot_inverse_transform(client, drop):
      df = DataFrame({"g": ["M", "F", "F"], "i": [1, 3, 2]})
      X = dask_cudf.from_cudf(df, npartitions=2)
  
      enc = OneHotEncoder(drop=drop)
      ohe = enc.fit_transform(X)
      inv = enc.inverse_transform(ohe)
      assert_frame_equal(
          inv.compute().to_pandas().reset_index(drop=True),
          df.to_pandas(),
      )
  
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 2 for calling a global function with example usage: test_onehot_inverse_transform(client, drop) without return types