def test_layers_view():
    X = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
    L = np.array([[10, 11, 12], [13, 14, 15], [16, 17, 18]])
    real_adata = ad.AnnData(X)
    real_adata.layers["L"] = L
    view_adata = real_adata[1:, 1:]
    real_hash = joblib.hash(real_adata)
    view_hash = joblib.hash(view_adata)

    assert view_adata.is_view

    with pytest.raises(ValueError):
        view_adata.layers["L2"] = L + 2

    assert view_adata.is_view  # Failing to set layer item makes adata not view
    assert real_hash == joblib.hash(real_adata)
    assert view_hash == joblib.hash(view_adata)

    view_adata.layers["L2"] = L[1:, 1:] + 2

    assert not view_adata.is_view
    assert real_hash == joblib.hash(real_adata)
    assert view_hash != joblib.hash(view_adata)
def test_make_gym_venv_nostack(name, num_envs, state_shape, reward_scale):
    seed = 0
    frame_op = None
    frame_op_len = None
    venv = make_gym_venv(name, num_envs, seed, frame_op=frame_op, frame_op_len=frame_op_len, reward_scale=reward_scale)
    venv.reset()
    for i in range(5):
        state, reward, done, info = venv.step([venv.action_space.sample()] * num_envs)

    assert isinstance(state, np.ndarray)
    assert state.shape == (num_envs,) + state_shape
    assert isinstance(reward, np.ndarray)
    assert reward.shape == (num_envs,)
    assert isinstance(done, np.ndarray)
    assert done.shape == (num_envs,)
    assert len(info) == num_envs
    venv.close()