("LGPL3"), the copyright holders of this Library give you permission to
convey to a third party a Combined Work that links statically or dynamically
to this Library without providing any Minimal Corresponding Source or
Minimal Application Code as set out in 4d or providing the installation
information set out in section 4e, provided that you comply with the other
provisions of LGPL3 and provided that you meet, for the Application the

		}

		// Profiling operations - deprecated API
		adminRouter.Methods(http.MethodPost).Path(adminVersion+"/profiling/start").HandlerFunc(adminMiddleware(adminAPI.StartProfilingHandler, traceAllFlag, noObjLayerFlag)).
			Queries("profilerType", "{profilerType:.*}")

                            nullable: true
                            type: boolean
                          match:
                            description: Match allows providing the scope of the override.
                            oneOf:
                            - not:
                                anyOf:
                                - required:

    text(
        "profiler",
        defaultProfiler,
        display = ParameterDisplay.PROMPT,
        allowEmpty = false,
        description = "Command line option for the performance test task to enable profiling. For example `async-profiler`, `async-profiler-heap`, `async-profiler-all` or `jfr`. Use `none` for benchmarking only."
    )
}

object AdHocPerformanceScenarioLinux : AdHocPerformanceScenario(Os.LINUX)

### SIG Scheduling

- Fixed PersistentolumeLabel providing wrong topology labels to Azure Disk PersistentVolumes when the external Azure cloud provider is used. ([#124528](https://github.com/kubernetes/kubernetes/pull/124528), [@jsafrane](https://github.com/jsafrane)) [SIG Cloud Provider]

    TFE_TensorHandle* h, TFE_Context* ctx, const char* device_name,
    TF_Status* status);

// Debugging/Profiling information for TFE_TensorHandle
//
// TFE_TensorDebugInfo contains information useful for debugging and
// profiling tensors.
typedef struct TFE_TensorDebugInfo TFE_TensorDebugInfo;

// Retrieves TFE_TensorDebugInfo for `handle`.

        during the python Dataset object creation instead doing it during
        Iterator creation time.
    *   Add support for TensorArrays to tf.data Dataset.
    *   Switching tf.data functions to use `defun`, providing an escape hatch to
        continue using the legacy `Defun`.
*   Toolchains
    *   CUDNN_INSTALL_PATH, TENSORRT_INSTALL_PATH, NCCL_INSTALL_PATH,

    * [StorageOS](http://www.storageos.com) can be used as a storage provider for Kubernetes.  With StorageOS, capacity from local or attached storage is pooled across the cluster, providing converged infrastructure for cloud-native applications.
* CRI has been moved to package `pkg/kubelet/apis/cri/v1alpha1/runtime`. ([#47113](https://github.com/kubernetes/kubernetes/pull/47113), [@feiskyer](https://github.com/feiskyer))

		p.records = make(map[string][]byte)
	}
	err := pprof.Lookup(profileType).WriteTo(&buf, debug)
	if err != nil {
		return
	}
	p.records[recordName] = buf.Bytes()
}

// Records returns the recorded profiling if any.
func (p profilerWrapper) Records() map[string][]byte {
	return p.records
}

// Stop the currently running benchmark.
func (p profilerWrapper) Stop() ([]byte, error) {
	return p.stopFn()
}