apiVersion: apps/v1beta1
kind: Scale
metadata:
  annotations:
    annotationsKey: annotationsValue
  creationTimestamp: "2008-01-01T01:01:01Z"
  deletionGracePeriodSeconds: 10
  deletionTimestamp: "2009-01-01T01:01:01Z"
  finalizers:
  - finalizersValue
  generateName: generateNameValue
  generation: 7
  labels:
    labelsKey: labelsValue
  managedFields:
  - apiVersion: apiVersionValue
    fieldsType: fieldsTypeValue

apiVersion: apps/v1beta2
kind: Scale
metadata:
  annotations:
    annotationsKey: annotationsValue
  creationTimestamp: "2008-01-01T01:01:01Z"
  deletionGracePeriodSeconds: 10
  deletionTimestamp: "2009-01-01T01:01:01Z"
  finalizers:
  - finalizersValue
  generateName: generateNameValue
  generation: 7
  labels:
    labelsKey: labelsValue
  managedFields:
  - apiVersion: apiVersionValue
    fieldsType: fieldsTypeValue

apiVersion: extensions/v1beta1
kind: Scale
metadata:
  annotations:
    annotationsKey: annotationsValue
  creationTimestamp: "2008-01-01T01:01:01Z"
  deletionGracePeriodSeconds: 10
  deletionTimestamp: "2009-01-01T01:01:01Z"
  finalizers:
  - finalizersValue
  generateName: generateNameValue
  generation: 7
  labels:
    labelsKey: labelsValue
  managedFields:
  - apiVersion: apiVersionValue
    fieldsType: fieldsTypeValue

  // +optional
  repeated MetricSpec metrics = 4;

  // behavior configures the scaling behavior of the target
  // in both Up and Down directions (scaleUp and scaleDown fields respectively).
  // If not set, the default HPAScalingRules for scale up and scale down are used.
  // +optional
  optional HorizontalPodAutoscalerBehavior behavior = 5;
}

	"scaleUp":   "scaleUp is scaling policy for scaling Up. If not set, the default value is the higher of:\n  * increase no more than 4 pods per 60 seconds\n  * double the number of pods per 60 seconds\nNo stabilization is used.",

// PerChannel-DAG: %[[q_w2:.*]] = "tf.Const"() <{value = dense<{{[0-9]+}}> : tensor<2x3x3x2xi8>}> : () -> tensor<2x3x3x2xi8>
// PerChannel-DAG: %[[scale1:.*]] = "tf.Const"() <{value = dense<{{[0-9\.Ee\+\-]+}}> : tensor<3xf32>}> : () -> tensor<3xf32>
// PerChannel-DAG: %[[scale2:.*]] = "tf.Const"() <{value = dense<{{[0-9\.Ee\+\-]+}}> : tensor<6xf32>}> : () -> tensor<6xf32>

  // Zero scales we make the minimum fp value, this is because some flatbuffers
  // 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.

				return false
			}
		}
	case source.ScaleIO != nil:
		if source.ScaleIO.SecretRef != nil {
			ns := getClaimRefNamespace(pv)
			if source.ScaleIO.SecretRef != nil && len(source.ScaleIO.SecretRef.Namespace) > 0 {
				ns = source.ScaleIO.SecretRef.Namespace
			}
			if !visitor(ns, source.ScaleIO.SecretRef.Name, true /* kubeletVisible */) {
				return false
			}
		}

	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,
			},
		},

kind: RoleBinding
metadata:
  name: fluentd-gcp-scaler-binding
  namespace: kube-system
  labels:
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
roleRef:
  apiGroup: rbac.authorization.k8s.io
  kind: Role
  name: system:fluentd-gcp-scaler
subjects:
- kind: ServiceAccount
  name: fluentd-gcp-scaler