q3.SetScaled(item.value, item.scale)
		if q.Cmp(*q3) != 0 {
			t.Errorf("Expected %v and %v to be equal", q, q3)
		}
	}
}

func TestScaledValue(t *testing.T) {
	table := []struct {
		fromScale Scale
		toScale   Scale
		expected  int64
	}{
		{Nano, Nano, 1},
		{Nano, Micro, 1},
		{Nano, Milli, 1},
		{Nano, 0, 1},
		{Micro, Nano, 1000},
		{Micro, Micro, 1},

)

// +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

		if subresources.Scale.LabelSelectorPath != nil && len(*subresources.Scale.LabelSelectorPath) > 0 {
			if errs := validateSimpleJSONPath(*subresources.Scale.LabelSelectorPath, fldPath.Child("scale.labelSelectorPath")); len(errs) > 0 {
				allErrs = append(allErrs, errs...)
			} else if !strings.HasPrefix(*subresources.Scale.LabelSelectorPath, ".spec.") && !strings.HasPrefix(*subresources.Scale.LabelSelectorPath, ".status.") {

        in_y);
    auto out_w_f32 = rewriter.create<CastOp>(
        loc, tensorflow::GetTypeFromTFTensorShape({}, rewriter.getF32Type()),
        out_y);

    Value y_scale = rewriter.create<DivOp>(
        loc, tensorflow::GetTypeFromTFTensorShape({}, rewriter.getF32Type()),
        in_y_f32, out_w_f32);

    Value zero_f32 = rewriter.create<ConstOp>(

	for _, successCase := range successCases {
		if errs := ValidateScale(&successCase); len(errs) != 0 {
			t.Errorf("expected success: %v", errs)
		}
	}

	errorCases := []struct {
		scale autoscaling.Scale
		msg   string
	}{{
		scale: autoscaling.Scale{
			ObjectMeta: metav1.ObjectMeta{
				Name:      "frontend",
				Namespace: metav1.NamespaceDefault,
			},
			Spec: autoscaling.ScaleSpec{
				Replicas: -1,
			},
		},

//              scale * rsqrt(variance + epsilon)
// CHECK:  %[[MUL1:.*]] = "tf.Mul"(%[[ARG1:.*]], %[[RSQRT]])
//              x * scale * rsqrt(variance + epsilon)
// CHECK:  %[[MUL2:.*]] = "tf.Mul"(%[[ARG0:.*]], %[[MUL1]])
//              mean * scale * rsqrt(variance + epsilon)
// CHECK:  %[[MUL3:.*]] = "tf.Mul"(%[[ARG3:.*]], %[[MUL1]])
//              offset - mean * scale * rsqrt(variance + epsilon)

// 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

  //
  // For example:
  // 'pods' means pods.
  // 'pods/log' means the log subresource of pods.
  // '*' means all resources, but not subresources.
  // 'pods/*' means all subresources of pods.
  // '*/scale' means all scale subresources.
  // '*/*' means all resources and their subresources.
  //
  // If wildcard is present, the validation rule will ensure resources do not
  // overlap with each other.
  //

- Kube-controller-manager: the `horizontal-pod-autoscaler-upscale-delay` and `horizontal-pod-autoscaler-downscale-delay` flags have been removed (deprecated and non-functional since v1.12) ([#124948](https://github.com/kubernetes/kubernetes/pull/124948), [@SataQiu](https://github.com/SataQiu)) [SIG API Machinery,...

          'same_scale_op': (
              'reshape',  # This corresponds to stablehlo.dynamic_reshape
              'slice',  # This corresponds to stablehlo.dynamic_slice.
              # TODO: b/326242075 - Support other same-scale ops.
          ),
          'dim_sizes': (([None, 1024], [1024, 3]),),
      }])
  )
  @test_util.run_in_graph_and_eager_modes
  def test_matmul_and_same_scale_ptq_model_dynamic(
      self,