code: def test_split_dataframe_array(y_type):
      X = cudf.DataFrame({"x": range(100)})
      y = cudf.Series(([0] * (100 // 2)) + ([1] * (100 // 2)))
      if y_type == "cupy":
          X_train, X_test, y_train, y_test = train_test_split(
              X, y.values
          )
          assert isinstance(X_train, cudf.DataFrame)
          assert isinstance(X_test, cudf.DataFrame)
          assert isinstance(y_train, cp.ndarray)
          assert isinstance(y_test, cp.ndarray)
      elif y_type == "cudf":
          X_train, X_test, y_train, y_test = train_test_split(X, y)
          assert isinstance(X_train, cudf.DataFrame)
          assert isinstance(X_test, cudf.DataFrame)
          assert isinstance(y_train, cudf.Series)
          assert isinstance(y_test, cudf.Series)
  
imports: from cuml.internals.safe_imports import gpu_only_import_from
  from cuml.datasets import make_classification
  from cuml.model_selection import train_test_split
  import pytest
  from cuml.internals.safe_imports import cpu_only_import
  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_split_dataframe_array(y_type) without return types