code: def test_ordinal_encoder_df(client: Client) -> None:
      X = DataFrame({"cat": ["M", "F", "F"], "int": [1, 3, 2]})
      X = dask_cudf.from_cudf(X, npartitions=2)
  
      enc = OrdinalEncoder()
      enc.fit(X)
      Xt = enc.transform(X)
  
      X_1 = DataFrame({"cat": ["F", "F"], "int": [1, 2]})
      X_1 = dask_cudf.from_cudf(X_1, npartitions=2)
  
      enc = OrdinalEncoder(client=client)
      enc.fit(X)
      Xt_1 = enc.transform(X_1)
  
      Xt_r = Xt.compute()
      Xt_1_r = Xt_1.compute()
      assert Xt_1_r.iloc[0, 0] == Xt_r.iloc[1, 0]
      assert Xt_1_r.iloc[1, 0] == Xt_r.iloc[1, 0]
      assert Xt_1_r.iloc[0, 1] == Xt_r.iloc[0, 1]
      assert Xt_1_r.iloc[1, 1] == Xt_r.iloc[2, 1]
  
      # Turn Int64Index to RangeIndex for testing equality
      inv_Xt = (
          enc.inverse_transform(Xt).compute().reset_index(drop=True)
      )
      inv_Xt_1 = (
          enc.inverse_transform(Xt_1).compute().reset_index(drop=True)
      )
  
      X_r = X.compute()
      X_1_r = X_1.compute()
  
      assert inv_Xt.equals(X_r)
      assert inv_Xt_1.equals(X_1_r)
  
      assert enc.n_features_in_ == 2
  
file_path: cuml/python/cuml/tests/dask/test_dask_ordinal_encoder.py
imports: import cupy
  import dask_cudf
  import numpy
  import pandas
  import pytest
  from cudf import DataFrame
  from cuml.dask.preprocessing import OrdinalEncoder
  from distributed import Client
label_desc: Use image node_id 1 for calling a global function with example usage: test_ordinal_encoder_df(client) without return types