}

// Scale represents a scaling request for a resource.
message Scale {
  // Standard object metadata; More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#metadata.
  // +optional
  optional .k8s.io.apimachinery.pkg.apis.meta.v1.ObjectMeta metadata = 1;

  // +optional
  optional CustomResourceSubresourceStatus status = 1;

  // scale indicates the custom resource should serve a `/scale` subresource that returns an `autoscaling/v1` Scale object.
  // +optional
  optional CustomResourceSubresourceScale scale = 2;
}

// CustomResourceValidation is a list of validation methods for CustomResources.
message CustomResourceValidation {

		maxValue = int64(float64(maxValue) * r)
	}

	_, minUnit := measurement.Scale(minValue, o.SampleUnit, "minimum")
	_, maxUnit := measurement.Scale(maxValue, o.SampleUnit, "minimum")

	unit := minUnit
	if minUnit != maxUnit && minValue*100 < maxValue && o.OutputFormat != Callgrind {
		// Minimum and maximum values have different units. Scale
		// minimum by 100 to use larger units, allowing minimum value to

			isScale, err := dc.implementsScale(mapping.Resource)
			if err != nil {
				return nil, err
			}
			if !isScale {
				return nil, fmt.Errorf("%s does not implement the scale subresource", gr.String())
			}
			return nil, nil
		}
		return nil, err
	}
	if scale.UID != controllerRef.UID {
		return nil, nil
	}
	return &controllerAndScale{scale.UID, scale.Spec.Replicas}, nil
}

}

// Scale represents a scaling request for a resource.
message Scale {
  // Standard object metadata; More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#metadata.
  // +optional
  optional k8s.io.apimachinery.pkg.apis.meta.v1.ObjectMeta metadata = 1;

}

// Scale represents a scaling request for a resource.
message Scale {
  // Standard object metadata; More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#metadata.
  // +optional
  optional .k8s.io.apimachinery.pkg.apis.meta.v1.ObjectMeta metadata = 1;

	if runtime.GOOS == "dragonfly" {
		t.Skip("skipping: wait hangs on dragonfly; see https://go.dev/issue/56132")
	}

	scale := 1
	if s := os.Getenv("GO_TEST_TIMEOUT_SCALE"); s != "" {
		if sc, err := strconv.Atoi(s); err == nil {
			scale = sc
		}
	}
	pause := time.Duration(scale) * 10 * time.Millisecond

	lvl := os.Getenv("GO_TEST_TERMINAL_SIGNALS")
	switch lvl {
	case "":
		// Main test process, run code below.

        auto shape = GetAsVector(quant_tensor->shape());
        if (kUseUpdatedHybridSchemeDefault) {
          EXPECT_EQ(quant_tensor->quantization()->scale()->size(), shape[0]);
        } else {
          EXPECT_EQ(quant_tensor->quantization()->scale()->size(), 1);
        }
      } else {
        EXPECT_EQ(quant_tensor->type(), TensorType_FLOAT32);
      }
    }

		a.writeNameTo(w, abiDetail)

	case TYPE_MEM:
		a.WriteNameTo(w)
		if a.Index != REG_NONE {
			if a.Scale == 0 {
				// arm64 shifted or extended register offset, scale = 0.
				fmt.Fprintf(w, "(%v)", Rconv(int(a.Index)))
			} else {
				fmt.Fprintf(w, "(%v*%d)", Rconv(int(a.Index)), int(a.Scale))
			}
		}

	case TYPE_CONST:
		io.WriteString(w, "$")
		a.WriteNameTo(w)
		if a.Reg != 0 {

}

TFE_MonitoringBuckets* TFE_MonitoringNewExponentialBuckets(double scale,
                                                           double growth_factor,
                                                           int bucket_count) {
  return new TFE_MonitoringBuckets([scale, growth_factor, bucket_count]() {
    return tensorflow::monitoring::Buckets::Exponential(scale, growth_factor,