def METHOD_NAME(executor_kind):
    def verify_topk(k, axis, ret_type, is_ascend, dtype, in_dtype="float32"):
        shape = (20, 100)
        x = relay.var("x", relay.TensorType(shape, in_dtype))
        out = relay.topk(x, k, axis, ret_type, is_ascend, dtype)
        if isinstance(out, relay.expr.TupleWrapper):
            out = out.astuple()
        func = relay.Function([x], out)
        np_data = np.random.uniform(size=shape).astype(in_dtype)
        if is_ascend:
            np_indices = np.argsort(np_data, axis=axis, kind="stable")
        else:
            np_indices = np.argsort(-np_data, axis=axis, kind="stable")
        kk = k if k >= 1 else shape[axis]
        if axis == 0:
            np_indices = np_indices[:kk, :]
            np_values = np.zeros(np_indices.shape).astype(in_dtype)
            for i in range(shape[1]):
                np_values[:, i] = np_data[np_indices[:, i], i]
        else:
            np_indices = np_indices[:, :kk]
            np_values = np.zeros(np_indices.shape).astype(in_dtype)
            for i in range(shape[0]):
                np_values[i, :] = np_data[i, np_indices[i, :]]
        np_indices = np_indices.astype(dtype)
        for target, dev in tvm.testing.enabled_targets():
            op_res = relay.create_executor(executor_kind, device=dev, target=target).evaluate(func)(
                np_data
            )
            if ret_type == "both":
                tvm.testing.assert_allclose(op_res[0].numpy(), np_values)
                tvm.testing.assert_allclose(op_res[1].numpy(), np_indices)
            elif ret_type == "values":
                tvm.testing.assert_allclose(op_res.numpy(), np_values)
            else:
                tvm.testing.assert_allclose(op_res.numpy(), np_indices)
    np.random.seed(0)
    for k in [0, 1, 5]:
        for axis in [0, -1, 1]:
            for ret_type in ["both", "values", "indices"]:
                verify_topk(k, axis, ret_type, True, "int64")
                verify_topk(k, axis, ret_type, False, "float32")
                verify_topk(k, axis, ret_type, False, "int64", "float16")