return {0, 0};
  }

  return {static_cast<int32_t>(quantized_multiplier), shift};
}

// Calculates the quantized range for a given scale, zero point, minimum and
// maximum values, and quantization range.
//
// Args:
//   scale: The scale factor for the quantized values.
//   zero_point: The zero point for the quantized values.
//   rmin: The minimum value of the quantized values.

		value  int64
		max    int64
		result int64
		scale  int32
	}{
		{100, 10, 1, 2},
		{100, 10, 1, 2},
		{100, 100, 1, 1},
		{1, 10, 1, 0},
	} {
		r, s := removeInt64Factors(test.value, test.max)
		if r != test.result {
			t.Errorf("%v: unexpected result: %d", test, r)
		}
		if s != test.scale {
			t.Errorf("%v: unexpected scale: %d", test, s)
		}
	}
}

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

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.

		}
	}
	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
	}

						Namespace:   "myns",
						Verb:        "create",
						Group:       "extensions",
						Version:     "v1beta1",
						Resource:    "deployments",
						Subresource: "scale",
						Name:        "mydeployment",
					},
				},
			},
			want: authorizer.AttributesRecord{
				User: &user.DefaultInfo{
					Name: "bob",
				},
				APIGroup:        "extensions",

						"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{

<%@page pageEncoding="UTF-8" contentType="text/html; charset=UTF-8"%>
<meta content='width=device-width, initial-scale=1, maximum-scale=1, user-scalable=no' name='viewport'>
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<link href="${fe:url('/css/admin/bootstrap.min.css')}" rel="stylesheet" type="text/css" />
<link href="${fe:url('/css/admin/font-awesome.min.css')}" rel="stylesheet" type="text/css" />

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: [""]

  OutputInputSameScale,
  OutputInputFreeScale,
  CustomScale,
};

// Each kernel signature has its own specification for scales.
struct KernelSpec {
  // Scale constraint
  ScaleConstraintType type;

  // Custom function to derive the scales. Only available when the scale
  // constraint is `CustomScale`.
  ScaleFn scale_fn;
};

class KernelSpecs {
 public:
  using Signature = llvm::SmallVector<quant::AnyQuantizedType, 4>;