def METHOD_NAME(executor_kind):
    dtype = "uint8"
    rank = 3
    shape_type = "int64"
    dyn_shape = relay.Var("shape", relay.ty.TensorType((rank,), shape_type))
    x_shape = (1,)
    x = relay.Var("x", relay.ty.TensorType(x_shape, dtype))
    z = relay.broadcast_to(x, dyn_shape)
    zz = run_infer_type(z)
    assert zz.checked_type == relay.ty.TensorType((relay.Any(),) * rank, dtype)
    func = relay.Function([x, dyn_shape], z)
    x = np.random.uniform(size=x_shape).astype(dtype)
    dyn_shape = (1,) * rank
    ref_res = np.broadcast_to(x, dyn_shape)
    for target, dev in tvm.testing.enabled_targets():
        mod = tvm.ir.IRModule.from_expr(func)
        op_res = relay.create_executor(executor_kind, mod=mod, device=dev, target=target).evaluate(
            func
        )(x, np.array(dyn_shape).astype(shape_type))
        tvm.testing.assert_allclose(op_res.numpy(), ref_res, rtol=1e-5)