if forwardTo == nil {
		return nil, nil, nil
	}

	weights := []int{}
	action := []k8s.BackendRef{}
	for _, w := range forwardTo {
		wt := int(ptr.OrDefault(w.Weight, 1))
		if wt == 0 {
			continue
		}
		action = append(action, w)
		weights = append(weights, wt)
	}
	if len(weights) == 1 {
		weights = []int{0}
	}

	var invalidBackendErr *ConfigError

	{Name: string(v1.ResourceCPU), Weight: 1},
	{Name: string(v1.ResourceMemory), Weight: 1},
	{Name: string(v1.ResourcePods), Weight: 1},
	{Name: string(v1.ResourceStorage), Weight: 1},
	{Name: string(v1.ResourceEphemeralStorage), Weight: 1},
	{Name: string(extendedResourceA), Weight: 1},
	{Name: string(extendedResourceB), Weight: 1},
	{Name: string(kubernetesIOResourceA), Weight: 1},

				Route: []*networking.RouteDestination{
					{
						Destination: &networking.Destination{
							Host: "test.org",
							Port: &networking.PortSelector{
								Number: 80,
							},
						},
						Weight: 100,
					},
				},
			},
		},
	}
)

func TestInboundListenerConfig(t *testing.T) {
	for _, p := range []*model.Proxy{getProxy(), &proxyHTTP10, &dualStackProxy} {

  ASSERT_THAT(op->inputs, SizeIs(3));
  ASSERT_THAT(op->outputs, SizeIs(1));

  auto float_graph = readonly_model_->subgraphs()->Get(0);
  // Verify FC input tensor and weight are int8 quantized.
  auto float_op = float_graph->operators()->Get(0);
  ASSERT_THAT(float_graph->tensors()->Get(float_op->inputs()->Get(0))->type(),
              Eq(TensorType_FLOAT32));