def test_featurize_data(): """ Test that the featurize_data model correctly outputs the features of a toy network on a toy tensor """ # Create the checked array init_array = np.ones((5, 5, 5, 3)) for i in range(5): init_array[i] = init_array[i] * i # Check the prediction vs. the saved array check_array = np.load('tests/data_featurizing_testing/array_testing/check_featurize.npy') assert np.allclose(featurize_data(MODEL, init_array), check_array, atol=ATOL)
def test_featurize_data_bad_array(): """Test errors with a badly formatted array""" error_array = np.ones((5, 5, 10)) with pytest.raises(ValueError): featurize_data(MODEL, error_array)