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

              "subresources": [
                {
                  "responseKind": {
                    "group": "autoscaling",
                    "kind": "Scale",
                    "version": "v1"
                  },
                  "subresource": "scale",
                  "verbs": [
                    "get",
                    "patch",
                    "update"
                  ]
                },

		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,
			},
		},

          input_tensor: Input tensor to perform convolution on.

        Returns:
          A map of: output key -> output result.
        """
        scale = [1.0] * self.out_channel_size
        offset = [0.5] * self.out_channel_size
        mean, variance = scale, offset
        out = nn_ops.depthwise_conv2d_native(
            input_tensor,
            self.filters,
            strides=[1, 2, 2, 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)

	out.Status = (*apiextensions.CustomResourceSubresourceStatus)(unsafe.Pointer(in.Status))
	out.Scale = (*apiextensions.CustomResourceSubresourceScale)(unsafe.Pointer(in.Scale))
	return nil
}

// Convert_v1_CustomResourceSubresources_To_apiextensions_CustomResourceSubresources is an autogenerated conversion function.

	out.Status = (*apiextensions.CustomResourceSubresourceStatus)(unsafe.Pointer(in.Status))
	out.Scale = (*apiextensions.CustomResourceSubresourceScale)(unsafe.Pointer(in.Scale))
	return nil
}

// Convert_v1beta1_CustomResourceSubresources_To_apiextensions_CustomResourceSubresources is an autogenerated conversion function.