ResponseKind *v1.GroupVersionKind `json:"responseKind,omitempty" protobuf:"bytes,2,opt,name=responseKind"`
	// scope indicates the scope of a resource, either Cluster or Namespaced
	Scope ResourceScope `json:"scope" protobuf:"bytes,3,opt,name=scope"`
	// singularResource is the singular name of the resource.  This allows clients to handle plural and singular opaquely.

	c.SyncFrequency.Duration = 10 * time.Second
	c.EvictionPressureTransitionPeriod.Duration = 5 * time.Minute
	c.MaxPods = int32(opt.MaxPods)
	c.PodsPerCore = int32(opt.PodsPerCore)
	c.ClusterDNS = []string{}
	c.ImageGCHighThresholdPercent = 90
	c.ImageGCLowThresholdPercent = 80
	c.ProviderID = fmt.Sprintf("kubemark://%v", opt.NodeName)
	c.VolumeStatsAggPeriod.Duration = time.Minute
	c.CgroupRoot = ""
	c.CPUCFSQuota = true

	// and is immutable.
	Handler string `json:"handler" protobuf:"bytes,2,opt,name=handler"`

	// overhead represents the resource overhead associated with running a pod for a
	// given RuntimeClass. For more details, see
	//  https://kubernetes.io/docs/concepts/scheduling-eviction/pod-overhead/
	// +optional
	Overhead *Overhead `json:"overhead,omitempty" protobuf:"bytes,3,opt,name=overhead"`

/**
 * The private [KaAllowProhibitedAnalyzeFromWriteAction] opt-in forces users of [allowAnalysisFromWriteAction] to specify an opt-in not only
 * in the code (via [KaAllowAnalysisFromWriteAction]), but also from the command line:
 *
 * ```
 * -opt-in=org.jetbrains.kotlin.analysis.api.permissions.KaAllowProhibitedAnalyzeFromWriteAction
 * ```
 *
 * This results in a double layer of opt-ins which makes it harder to abuse [allowAnalysisFromWriteAction].

	// Label (RFC 1123) validation.
	// +optional
	Hostname *string `json:"hostname,omitempty" protobuf:"bytes,3,opt,name=hostname"`

	// targetRef is a reference to a Kubernetes object that represents this
	// endpoint.
	// +optional
	TargetRef *v1.ObjectReference `json:"targetRef,omitempty" protobuf:"bytes,4,opt,name=targetRef"`

	// deprecatedTopology contains topology information part of the v1beta1

            }

            else -> {
                profilerParam("async-profiler")
                param("env.FG_HOME_DIR", "/opt/FlameGraph")
                param("env.PATH", "%env.PATH%:/opt/swift/4.2.3/usr/bin:/opt/swift/4.2.4-RELEASE-ubuntu18.04/usr/bin")
                param("env.HP_HOME_DIR", "/opt/honest-profiler")
            }
        }

        param("env.PERFORMANCE_DB_PASSWORD_TCAGENT", "%performance.db.password.tcagent%")

        "Linux",
        androidHome = "/opt/android/sdk",
        jprofilerHome = "/opt/jprofiler/jprofiler11.1.4"
    ),
    WINDOWS(
        "Windows",
        androidHome = """C:\Program Files\android\sdk""",
        jprofilerHome = """C:\Program Files\jprofiler\jprofiler11.1.4""",
        perfTestWorkingDir = "P:/",
    ),
    MACOS(
        "Mac",
        androidHome = "/opt/android/sdk",

// embedded configs. Forcing consumers to use these defaults would be problematic
// as defaulting in the scheme is done as part of the conversion, and there would
// be no easy way to opt-out. Instead, if you want to use this defaulting method
// run it in your wrapper struct of this type in its `SetDefaults_` method.

#include "tensorflow/compiler/mlir/lite/quantization/lite/quantize_model.h"
#include "tensorflow/compiler/mlir/lite/schema/schema_generated.h"
#include "tensorflow/lite/c/c_api_types.h"

using llvm::cl::opt;

// NOLINTNEXTLINE
static opt<std::string> inputFileName(llvm::cl::Positional,
                                      llvm::cl::desc("<input file>"),
                                      llvm::cl::init("-"));

namespace mlir {

	ReadinessEndpoint  = "/readyz"
	ReadinessPort      = "8000"
	ServiceAccountPath = "/var/run/secrets/kubernetes.io/serviceaccount"
)

// Exposed for testing "constants"
var (
	CNIBinDir     = "/opt/cni/bin"
	HostCNIBinDir = "/host/opt/cni/bin"
	// Well-known subpath we will mount any needed host-mounts under,
	// to preclude shadowing or breaking any pod-internal mounts
	HostMountsPath = "/host"