return RegisterDefaults(scheme)
}

func SetDefaults_ResourceList(obj *v1.ResourceList) {
	for key, val := range *obj {
		// TODO(#18538): We round up resource values to milli scale to maintain API compatibility.
		// In the future, we should instead reject values that need rounding.
		const milliScale = -3
		val.RoundUp(milliScale)

		(*obj)[v1.ResourceName(key)] = val
	}
}

//
// It uses a brute-force recursive approach to enumerate all objects
// defined by dependencies of pkg, so that it can learn the set of
// package paths that may be mentioned in the fact encoding. This does
// not scale well; use [NewDecoderFunc] where possible.
func NewDecoder(pkg *types.Package) *Decoder {
	// Compute the import map for this package.
	// See the package doc comment.
	m := importMap(pkg.Imports())

	p1, err := collectProfile(p)
	if err != nil {
		serveError(w, http.StatusInternalServerError, "failed to collect profile")
		return
	}
	ts := p1.TimeNanos
	dur := p1.TimeNanos - p0.TimeNanos

	p0.Scale(-1)

	p1, err = profile.Merge([]*profile.Profile{p0, p1})
	if err != nil {
		serveError(w, http.StatusInternalServerError, "failed to compute delta")
		return
	}

// Bias tensor's scale is input scale * filter scale.

	// owner: @arjunrn @mwielgus @josephburnett @sanposhiho
	// kep: https://kep.k8s.io/1610
	// alpha: v1.20
	// beta:  v1.27
	// GA:  v1.30
	//
	// Add support for the HPA to scale based on metrics from individual containers
	// in target pods
	HPAContainerMetrics featuregate.Feature = "HPAContainerMetrics"

	// owner: @dxist
	// alpha: v1.16
	//

// RUN: tf-opt %s -tfl-prepare-quantize="quantize-signed=true post-training-quantize=true" -cse | FileCheck %s
// RUN: tf-opt %s -tfl-prepare-quantize="quantize-signed=true post-training-quantize=true legacy-float-scale=true" -cse| FileCheck --check-prefix=Legacy %s

// CHECK-LABEL: QuantizeLstmCellInput
func.func @QuantizeLstmCellInput(%arg0: tensor<1x28x28xf32>) -> tensor<1x28x20xf32> {
    %cst_2 = "tfl.no_value"() {value = unit} : () -> none

	}
	// match: (LEAQ2 [off] {sym} x (MOVQconst [scale]))
	// cond: is32Bit(int64(off)+int64(scale)*2)
	// result: (LEAQ [off+int32(scale)*2] {sym} x)
	for {
		off := auxIntToInt32(v.AuxInt)
		sym := auxToSym(v.Aux)
		x := v_0
		if v_1.Op != OpAMD64MOVQconst {
			break
		}
		scale := auxIntToInt64(v_1.AuxInt)
		if !(is32Bit(int64(off) + int64(scale)*2)) {
			break
		}
		v.reset(OpAMD64LEAQ)

			if postIndex < 0 {
				return ErrInvalidLengthGenerated
			}
			if postIndex > l {
				return io.ErrUnexpectedEOF
			}
			if m.Scale == nil {
				m.Scale = &CustomResourceSubresourceScale{}
			}
			if err := m.Scale.Unmarshal(dAtA[iNdEx:postIndex]); err != nil {
				return err
			}
			iNdEx = postIndex
		default:
			iNdEx = preIndex

#### Endpoints

Endpoints have an optimized code path, as they are by far the most frequently updated resource - in a steady cluster, this will often be the *only* change, caused by scale up/down.

As a result, they do not go through `PushContext`, and changes do not trigger a `PushContext` recomputation. Instead, the current state is incrementally computed based on events from `ServiceDiscovery`.

#### Conclusion

API rule violation: names_match,k8s.io/apimachinery/pkg/api/resource,Quantity,i
API rule violation: names_match,k8s.io/apimachinery/pkg/api/resource,Quantity,s
API rule violation: names_match,k8s.io/apimachinery/pkg/api/resource,int64Amount,scale
API rule violation: names_match,k8s.io/apimachinery/pkg/api/resource,int64Amount,value
API rule violation: names_match,k8s.io/apimachinery/pkg/apis/meta/v1,APIResourceList,APIResources