def METHOD_NAME():
    """
    Test to check if offloading only supported operators works,
    while leaving unsupported operators computed via tvm.
    """
    Device.load("test_config.json")
    if skip_runtime_test():
        return
    device = Device()
    np.random.seed(0)
    def get_model(input_shape, var_names):
        """Return a model and any parameters it may have."""
        a = relay.var(next(var_names), shape=input_shape, dtype="float32")
        out = relay.reshape(a, (1, 1, 1000))
        out = relay.sigmoid(out)
        out = relay.reshape(out, (1, 1000))
        return out
    inputs = {"a": tvm.nd.array(np.random.uniform(-127, 128, (1, 1, 1, 1000)).astype("float32"))}
    outputs = []
    for acl in [False, True]:
        func = get_model(inputs["a"].shape, iter(inputs))
        outputs.append(
            build_and_run(
                func, inputs, 1, None, device, enable_acl=acl, tvm_ops=1, acl_partitions=2
            )[0]
        )
    verify(outputs, atol=0.002, rtol=0.01)