code: def test_transform_selected_2():
      """Assert _transform_selected return original X when selected is a list of False values"""
      ohe = OneHotEncoder(categorical_features=[False, False, False])
      X = _transform_selected(
          dense1,
          ohe._fit_transform,
          ohe.categorical_features,
          copy=True,
      )
      assert np.allclose(X, dense1)
  
imports: import numpy
  import scipy.sparse
  from numpy.testing import assert_array_almost_equal
  from sklearn.datasets import load_iris, load_boston
  from sklearn.linear_model import LinearRegression
  from sklearn.pipeline import make_pipeline
  from sklearn.model_selection import cross_val_score, KFold
  from nose.tools import assert_equal
  from tpot.builtins import OneHotEncoder, auto_select_categorical_features, _transform_selected
label_desc: Use image node_id 19 for calling a global function with example usage: test_transform_selected_2() without return types