def test_view_of_view_modification():
    adata = ad.AnnData(np.zeros((10, 10)))
    adata[0, :][:, 5:].X = np.ones(5)
    assert np.all(adata.X[0, 5:] == np.ones(5))
    adata[[1, 2], :][:, [1, 2]].X = np.ones((2, 2))
    assert np.all(adata.X[1:3, 1:3] == np.ones((2, 2)))

    adata.X = sparse.csr_matrix(adata.X)
    adata[0, :][:, 5:].X = np.ones(5) * 2
    assert np.all(asarray(adata.X)[0, 5:] == np.ones(5) * 2)
    adata[[1, 2], :][:, [1, 2]].X = np.ones((2, 2)) * 2
    assert np.all(asarray(adata.X)[1:3, 1:3] == np.ones((2, 2)) * 2)
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))