)

// +genclient
// +genclient:method=GetScale,verb=get,subresource=scale,result=k8s.io/api/autoscaling/v1.Scale
// +genclient:method=UpdateScale,verb=update,subresource=scale,input=k8s.io/api/autoscaling/v1.Scale,result=k8s.io/api/autoscaling/v1.Scale
// +genclient:method=ApplyScale,verb=apply,subresource=scale,input=k8s.io/api/autoscaling/v1.Scale,result=k8s.io/api/autoscaling/v1.Scale
// +k8s:deepcopy-gen:interfaces=k8s.io/apimachinery/pkg/runtime.Object

  OutputInputSameScale,
  OutputInputFreeScale,
  CustomScale,
};

// Each kernel signature has its own specification for scales.
struct KernelSpec {
  // Scale constraint
  ScaleConstraintType type;

  // Custom function to derive the scales. Only available when the scale
  // constraint is `CustomScale`.
  ScaleFn scale_fn;
};

class KernelSpecs {
 public:
  using Signature = llvm::SmallVector<quant::AnyQuantizedType, 4>;

						{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"}}},
					},
				},
			},

// Converts tf.FusedBatchNormV3 into a sequence of more primitive arithmetic
// operations. Specifically, performs the following calculation:
//
//   (x - mean) * scale / sqrt(variance + epsilon) + offset
//
// Let multiplier = scale / sqrt(variance + epsilon),
// to compute
//   (x - mean) * scale / sqrt(variance + epsilon) + offset,
// is then to compute
//   (x * multiplier) + (offset - mean * multiplier).
//

### Creating the Scale-out Backup Repository

- Under the Backup Infrastructure view, click on Scale-out Repositories and click the Add Scale-out Repository button on the ribbon.

- Follow the on screen wizard

	// we don't use cached discovery because DiscoveryScaleKindResolver does its own caching,
	// so we want to re-fetch every time when we actually ask for it
	scaleKindResolver := scale.NewDiscoveryScaleKindResolver(hpaClient.Discovery())
	scaleClient, err := scale.NewForConfig(hpaClientConfig, controllerContext.RESTMapper, dynamic.LegacyAPIPathResolverFunc, scaleKindResolver)
	if err != nil {
		return nil, false, err
	}

# CHECK-NEXT:          scale: [ 0.015686 ],
# CHECK-NEXT:          zero_point: [ 128 ]
# CHECK-NEXT:        },
# CHECK-NEXT:        has_rank: true
# CHECK-NEXT:      }, {
# CHECK-NEXT:        shape: [ 4 ],
# CHECK-NEXT:        type: UINT8,
# CHECK-NEXT:        buffer: 2,
# CHECK-NEXT:        name: "input1",
# CHECK-NEXT:        quantization: {
# CHECK-NEXT:          scale: [ 0.023529 ],

							{
								Type:    metav1.CauseTypeFieldManagerConflict,
								Message: `conflict with "foo" with subresource "scale" using v1 at 2001-02-03T04:05:06Z`,
								Field:   ".spec.replicas",
							},
						},
					},
					Message: `Apply failed with 1 conflict: conflict with "foo" with subresource "scale" using v1 at 2001-02-03T04:05:06Z: .spec.replicas`,
				},
			},
		},
	}
	for _, tc := range testCases {

  // 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