def test_negative_scalar_index(adata, index: int, obs: bool):
    pos_index = index + (adata.n_obs if obs else adata.n_vars)

    if obs:
        adata_pos_subset = adata[pos_index]
        adata_neg_subset = adata[index]
    else:
        adata_pos_subset = adata[:, pos_index]
        adata_neg_subset = adata[:, index]

    np.testing.assert_array_equal(
        adata_pos_subset.obs_names, adata_neg_subset.obs_names
    )
    np.testing.assert_array_equal(
        adata_pos_subset.var_names, adata_neg_subset.var_names
    )
def cumsum(X):
        """
        Y[i] = sum(X[:i])
        """
        (m,) = X.shape
        s_state = te.placeholder((m + 1,), dtype="int32", name="state")
        s_init = te.compute((1,), lambda _: tvm.tir.const(0, "int32"))
        s_update = te.compute((m + 1,), lambda l: s_state[l - 1] + X[l - 1])
        return tvm.te.scan(s_init, s_update, s_state, inputs=[X], name="cumsum")