/*input=*/new_filter);
    rewriter.replaceAllUsesExcept(filter_op->getResult(0), dq.getOutput(), dq);
  }

 private:
  // Returns new quantized type for weights after transpose.
  Type GetNewWeightQuantizedType(MLIRContext* context, Location location,
                                 ArrayRef<int64_t> new_shape, Type filter_type,

        // This filter goes through quantize and dequantize ops. Then we just
        // need to update the weight to the quantize op.
        filter.replaceAllUsesWith(new_filter_op);
      } else {
        // This filter doesn't go through quantize and dequantize ops, Then
        // we update the weight of the affine op directly.
        fc_op.setOperand(1, new_filter_op);
      }
    } else {

// maximum combined weight for concurrent access.
func NewWeighted(n int64) *Weighted {
	w := &Weighted{size: n}
	return w
}

// Weighted provides a way to bound concurrent access to a resource.
// The callers can request access with a given weight.
type Weighted struct {
	size    int64
	cur     int64
	mu      sync.Mutex
	waiters list.List
}

}

// The weights of all of the matched WeightedPodAffinityTerm fields are added per-node to find the most preferred node(s)
message WeightedPodAffinityTerm {
  // weight associated with matching the corresponding podAffinityTerm,
  // in the range 1-100.
  optional int32 weight = 1;

  // Required. A pod affinity term, associated with the corresponding weight.
  optional PodAffinityTerm podAffinityTerm = 2;

}

// -----

// Tests that basic convolution is properly quantized. In this example, the
// convolution is always per-tensor quantized (even if
// enable-per-channel-quantized-weights=true), according to
// `_quantization_method`.

// CHECK-LABEL: quantize_conv_fn_per_tensor
func.func @quantize_conv_fn_per_tensor(%arg0: tensor<1x3x4x3xf32>) -> tensor<1x3x4x2xf32> {

}

// The weights of all of the matched WeightedPodAffinityTerm fields are added per-node to find the most preferred node(s)
type WeightedPodAffinityTerm struct {
	// weight associated with matching the corresponding podAffinityTerm,
	// in the range 1-100.
	Weight int32 `json:"weight" protobuf:"varint,1,opt,name=weight"`

// we construct vertices representing types A, B, and T. Because of
// declaration "type T int", we construct edges T<-A and T<-B with
// weight 1; and because of instantiation "f[T, map[A]B]" we construct
// edges A<-T with weight 0, and B<-A and B<-B with weight 1.
//
// Finally, we look for any positive-weight cycles. Zero-weight cycles
// are allowed because static instantiation will reach a fixed point.

type monoGraph struct {
	vertices []monoVertex

// we construct vertices representing types A, B, and T. Because of
// declaration "type T int", we construct edges T<-A and T<-B with
// weight 1; and because of instantiation "f[T, map[A]B]" we construct
// edges A<-T with weight 0, and B<-A and B<-B with weight 1.
//
// Finally, we look for any positive-weight cycles. Zero-weight cycles
// are allowed because static instantiation will reach a fixed point.

type monoGraph struct {
	vertices []monoVertex

          },
          "weight": {
            "default": 0,
            "description": "Weight associated with matching the corresponding nodeSelectorTerm, in the range 1-100.",
            "format": "int32",
            "type": "integer"
          }
        },
        "required": [
          "weight",
          "preference"
        ],

		if route.Weight > 0 {
			clusterName := istioroute.GetDestinationCluster(route.Destination, service, port.Port)
			clusterSpecifier.WeightedClusters.Clusters = append(clusterSpecifier.WeightedClusters.Clusters, &tcp.TcpProxy_WeightedCluster_ClusterWeight{
				Name:   clusterName,
				Weight: uint32(route.Weight),
			})
		}
	}