def test_not_set_subset_X(matrix_type, subset_func):
    adata = ad.AnnData(matrix_type(asarray(sparse.random(20, 20))))
    init_hash = joblib.hash(adata)
    orig_X_val = adata.X.copy()
    while True:
        subset_idx = slice_subset(adata.obs_names)
        if len(adata[subset_idx, :]) > 2:
            break
    subset = adata[subset_idx, :]

    subset = adata[:, subset_idx]

    internal_idx = _normalize_index(
        subset_func(np.arange(subset.X.shape[1])), subset.var_names
    )
    assert subset.is_view
    subset.X[:, internal_idx] = 1
    assert not subset.is_view
    assert not np.any(asarray(adata.X != orig_X_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()