tfr.func @tf__my_requantize(%input: !tfr.tensor) -> !tfr.tensor {
  %raw_data = tfr.quant_raw_data(%input) : (!tfr.tensor) -> !tfr.tensor
  %scale, %zp = tfr.quant_qparam(%input) : (!tfr.tensor) -> (!tfr.tensor, !tfr.tensor)
  %result = tfr.call @tf__requantize(%raw_data, %scale, %zp) : (!tfr.tensor, !tfr.tensor, !tfr.tensor) -> !tfr.tensor
  tfr.return %result : !tfr.tensor
}

// CHECK-LABEL: @tf__intermediate

// Package-wide variables from generator "generated".
option go_package = "k8s.io/api/autoscaling/v2beta1";

// ContainerResourceMetricSource indicates how to scale on a resource metric known to
// Kubernetes, as specified in requests and limits, describing each pod in the
// current scale target (e.g. CPU or memory).  The values will be averaged
// together before being compared to the target.  Such metrics are built in to

    x_shape = [label_to_size.get(x_label) for x_label in x_labels]
    y_shape = [label_to_size.get(y_label) for y_label in y_labels]
    bias_shape = None
    if use_bias:
      bias_shape = [label_to_size.get(out_label) for out_label in out_labels]
      bias_shape = bias_shape[-1:]
    contracting_dims = set()

    x_signature = list(x_shape)
    y_signature = list(y_shape)

// CHECK-NEXT:        scale: [ 0.021827 ],
// CHECK-NEXT:        zero_point: [ 151 ]
// CHECK-NEXT:      },
// CHECK-NEXT:      has_rank: true
// CHECK-NEXT:    }, {
// CHECK-NEXT:      shape: [ 32 ],
// CHECK-NEXT:      type: INT32,
// CHECK-NEXT:      buffer: 5,
// CHECK-NEXT:      name: "tfl.pseudo_qconst1",
// CHECK-NEXT:      quantization: {
// CHECK-NEXT:        scale: [ 0.000171 ],

1. [Standalone Deployment](#standalone-deployment)
2. [Distributed Deployment](#distributed-deployment)
3. [Cloud Scale Deployment](#cloud-scale-deployment)

## 1. Standalone Deployment

To host multiple tenants on a single machine, run one MinIO Server per tenant with a dedicated HTTPS port, configuration, and data directory.

    verbs:
    - create
  - apiGroups:
    - apps
    resources:
    - daemonsets
    - deployments
    - deployments/rollback
    - deployments/scale
    - replicasets
    - replicasets/scale
    - statefulsets
    - statefulsets/scale
    verbs:
    - create
    - delete
    - deletecollection
    - patch
    - update
  - apiGroups:
    - autoscaling
    resources:

		}
	}
	return false
}

// Scale a measurement from a unit to a different unit and returns
// the scaled value and the target unit. The returned target unit
// will be empty if uninteresting (could be skipped).
func Scale(value int64, fromUnit, toUnit string) (float64, string) {
	// Avoid infinite recursion on overflow.
	if value < 0 && -value > 0 {
		v, u := Scale(-value, fromUnit, toUnit)
		return -v, u
	}

						"com.example.stable.v1.CRD1":                      {},
						"com.example.stable.v1.CRD2":                      {},
					},
				},
			},
		},
		{
			name: "two CRDs with scale",
			specs: []*spec3.OpenAPI{{
				Paths: &spec3.Paths{
					Paths: map[string]*spec3.Path{
						"/apis/stable.example.com/v1/crd1": {},
					},
				},
				Components: &spec3.Components{

)

// +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

rules:
  - apiGroups: [""]
    resources: ["nodes"]
    verbs: ["list", "watch"]
  - apiGroups: [""]
    resources: ["replicationcontrollers/scale"]
    verbs: ["get", "update"]
  - apiGroups: ["apps"]
    resources: ["deployments/scale", "replicasets/scale"]
    verbs: ["get", "update"]
# Remove the configmaps rule once below issue is fixed:
# kubernetes-incubator/cluster-proportional-autoscaler#16
  - apiGroups: [""]