// scaleTargetRef points to the target resource to scale, and is used to the pods for which metrics
	// should be collected, as well as to actually change the replica count.
	ScaleTargetRef CrossVersionObjectReference `json:"scaleTargetRef" protobuf:"bytes,1,opt,name=scaleTargetRef"`
	// minReplicas is the lower limit for the number of replicas to which the autoscaler
	// can scale down.  It defaults to 1 pod.  minReplicas is allowed to be 0 if the

// CHECK-NEXT:        scale: [ 0.021827 ],
// CHECK-NEXT:        zero_point: [ 151 ]
// CHECK-NEXT:      },
// CHECK-NEXT:      has_rank: true
// CHECK-NEXT:    }, {
// CHECK-NEXT:      shape: [ 32 ],
// CHECK-NEXT:      type: INT32,
// CHECK-NEXT:      buffer: 5,
// CHECK-NEXT:      name: "tfl.pseudo_qconst1",
// CHECK-NEXT:      quantization: {
// CHECK-NEXT:        scale: [ 0.000171 ],

    verbs:
    - create
  - apiGroups:
    - apps
    resources:
    - daemonsets
    - deployments
    - deployments/rollback
    - deployments/scale
    - replicasets
    - replicasets/scale
    - statefulsets
    - statefulsets/scale
    verbs:
    - create
    - delete
    - deletecollection
    - patch
    - update
  - apiGroups:
    - autoscaling
    resources:

						{Name: "v1", Served: true, Storage: true, Subresources: &apiextensions.CustomResourceSubresources{Scale: &apiextensions.CustomResourceSubresourceScale{SpecReplicasPath: "spec.replicas1"}}},
						{Name: "v2", Served: false, Storage: false, Subresources: &apiextensions.CustomResourceSubresources{Scale: &apiextensions.CustomResourceSubresourceScale{SpecReplicasPath: "spec.replicas2"}}},
					},
				},
			},

  // contain zero scale for zero values.
  llvm::SmallVector<double> scales;
  for (float scale : quant_params.scale) {
    if (scale == 0) {
      scales.push_back(std::numeric_limits<float>::min());
      continue;
    }
    scales.push_back(scale);
  }

  // Scale size can't be zero as it is checked before.
  if (quant_params.scale.size() != 1) {

// CHECK-DAG: %[[SCALE:.*]] = "tf.Const"() <{value = dense<0.00866141729> : tensor<f32>}> : () -> tensor<f32>

// CHECK-LABEL: func private @composite_dequantize_uniform_
// CHECK-DAG: %[[SCALE:.*]] = "tf.Const"() <{value = dense<0.00866141729> : tensor<f32>}> : () -> tensor<f32>

// CHECK-LABEL: func private @composite_dequantize_uniform

// +k8s:prerelease-lifecycle-gen:deprecated=1.8
// +k8s:prerelease-lifecycle-gen:removed=1.16
// +k8s:prerelease-lifecycle-gen:replacement=autoscaling,v1,Scale

// Scale represents a scaling request for a resource.
type Scale struct {
	metav1.TypeMeta `json:",inline"`
	// Standard object metadata; More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#metadata.
	// +optional

				})
			}
			if subresources != nil && subresources.Scale != nil {
				apiResourceDiscovery.Subresources = append(apiResourceDiscovery.Subresources, apidiscoveryv2.APISubresourceDiscovery{
					Subresource: "scale",
					ResponseKind: &metav1.GroupVersionKind{
						Group:   autoscaling.GroupName,
						Version: "v1",
						Kind:    "Scale",
					},
					Verbs: metav1.Verbs([]string{"get", "patch", "update"}),

// `key2` with given values.

module {

  // Note: following functions won't handle per-channel quantization for now.
  func.func private @internal_quantize_i8(%input : tensor<*xf32>, %scale : tensor<*xf32>, %zp : tensor<*xi32>) -> tensor<*xi8> {
    // Uses tf.floor(x + 0.5) instead of tf.round(x) since tf.round generates
    // a very expensive pattern.

      } else {
        new_output_types.push_back(result.getType());
      }
    }

    // Remove this rescale op.
    rewriter.replaceOp(op, {pre_quantized});

    // Replace the output scale of the preceding op.
    rewriter.setInsertionPointAfter(def);
    OperationState new_state(def->getLoc(), def->getName().getStringRef(),
                             def->getOperands(), new_output_types,