def test_view_of_view(matrix_type, subset_func, subset_func2):
    adata = gen_adata((30, 15), X_type=matrix_type)
    adata.raw = adata
    if subset_func is single_subset:
        pytest.xfail("Other subset generating functions have trouble with this")
    var_s1 = subset_func(adata.var_names, min_size=4)
    var_view1 = adata[:, var_s1]
    var_s2 = subset_func2(var_view1.var_names)
    var_view2 = var_view1[:, var_s2]
    assert var_view2._adata_ref is adata
    obs_s1 = subset_func(adata.obs_names, min_size=4)
    obs_view1 = adata[obs_s1, :]
    obs_s2 = subset_func2(obs_view1.obs_names)
    assert adata[obs_s1, :][:, var_s1][obs_s2, :]._adata_ref is adata

    view_of_actual_copy = adata[:, var_s1].copy()[obs_s1, :].copy()[:, var_s2].copy()

    view_of_view_copy = adata[:, var_s1][obs_s1, :][:, var_s2].copy()

    assert_equal(view_of_actual_copy, view_of_view_copy, exact=True)
def testWrapperV2Caller(self, wrapper):
    """Tests that wrapper V2 is using the LayerRNNCell's caller."""

    with legacy_base_layer.keras_style_scope():
      base_cell = rnn_cell_impl.MultiRNNCell(
          [rnn_cell_impl.BasicRNNCell(1) for _ in range(2)])
    rnn_cell = wrapper(base_cell)
    inputs = ops.convert_to_tensor_v2_with_dispatch([[1]], dtype=dtypes.float32)
    state = ops.convert_to_tensor_v2_with_dispatch([[1]], dtype=dtypes.float32)
    _ = rnn_cell(inputs, [state, state])
    weights = base_cell._cells[0].weights
    self.assertLen(weights, expected_len=2)
    self.assertTrue(all("_wrapper" in v.name for v in weights))