def METHOD_NAME(length, cardinality, client):
    """Try encoding the entire df"""
    tmp = cudf.Series(np.random.choice(cardinality, (length,)))
    df = dask_cudf.from_cudf(tmp, npartitions=len(client.has_what()))
    encoded = cuml.dask.preprocessing.LabelEncoder().fit_transform(df)
    df_arr = df.compute().to_numpy()
    df_arr = _arr_to_similarity_mat(df_arr)
    encoder_arr = cp.asnumpy(encoded.compute().to_numpy())
    encoded_arr = _arr_to_similarity_mat(encoder_arr)
    assert ((encoded_arr == encoded_arr.T) == (df_arr == df_arr.T)).all()