def test_set_obsm_key(adata):
    init_hash = joblib.hash(adata)

    orig_obsm_val = adata.obsm["o"].copy()
    subset_obsm = adata[:50]
    assert subset_obsm.is_view
    subset_obsm.obsm["o"] = np.ones((50, 20))
    assert not subset_obsm.is_view
    assert np.all(adata.obsm["o"] == orig_obsm_val)

    assert init_hash == joblib.hash(adata)
def _read_16bits_png_with_flow_and_valid_mask(file_name):

    flow_and_valid = _read_png_16(file_name).to(torch.float32)
    flow, valid_flow_mask = flow_and_valid[:2, :, :], flow_and_valid[2, :, :]
    flow = (flow - 2 ** 15) / 64  # This conversion is explained somewhere on the kitti archive
    valid_flow_mask = valid_flow_mask.bool()

    # For consistency with other datasets, we convert to numpy
    return flow.numpy(), valid_flow_mask.numpy()