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)

    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,

		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()
}

		}, idx, *client.host)
	}
	return ng.Wait()
}

// DownloadProfilingData - download profiling data from all remote peers.
func (sys *NotificationSys) DownloadProfilingData(ctx context.Context, writer io.Writer) (profilingDataFound bool) {
	// Initialize a zip writer which will provide a zipped content
	// of profiling data of all nodes
	zipWriter := zip.NewWriter(writer)
	defer zipWriter.Close()

///

/// check | "Ideas inspiring **FastAPI**"

Hug inspired parts of APIStar, and was one of the tools I found most promising, alongside APIStar.

Hug helped inspiring **FastAPI** to use Python type hints to declare parameters, and to generate a schema defining the API automatically.

	resp, err := getProcInfoRPC.Call(ctx, client.gridConn(), grid.NewMSS())
	return resp.ValueOrZero(), err
}

// StartProfiling - Issues profiling command on the peer node.
func (client *peerRESTClient) StartProfiling(ctx context.Context, profiler string) error {
	values := make(url.Values)
	values.Set(peerRESTProfiler, profiler)

		HTTPStatusCode: http.StatusBadRequest,
	},
	ErrAdminProfilerNotEnabled: {
		Code:           "XMinioAdminProfilerNotEnabled",
		Description:    "Unable to perform the requested operation because profiling is not enabled",
		HTTPStatusCode: http.StatusBadRequest,
	},
	ErrAdminBucketQuotaExceeded: {
		Code:           "XMinioAdminBucketQuotaExceeded",
		Description:    "Bucket quota exceeded",

	}

	err := globalIAMSys.LoadGroup(context.Background(), objAPI, group)
	if err != nil {
		return np, grid.NewRemoteErr(err)
	}

	return
}

// StartProfilingHandler - Issues the start profiling command.
func (s *peerRESTServer) StartProfilingHandler(w http.ResponseWriter, r *http.Request) {
	if !s.IsValid(w, r) {
		s.writeErrorResponse(w, errors.New("Invalid request"))
		return
	}

The assembler automatically inserts <code>BP</code> save/restore when frame size is larger than zero.
Using <code>BP</code> as a general purpose register is allowed,
however it can interfere with sampling-based profiling.
</p>

<h3 id="arm">ARM</h3>

<p>
The registers <code>R10</code> and <code>R11</code>
are reserved by the compiler and linker.
</p>

<p>