class CrossVersionPerformanceTestExecutionTest extends ResultSpecification {
    def result = new CrossVersionPerformanceResults(testProject: "some-project", tasks: [], cleanTasks: [])

    def "passes when average execution time for current release is smaller than average execution time for previous releases"() {
        given:
        result.baseline("1.0").results.add(operation(totalTime: 110))
        result.baseline("1.0").results.add(operation(totalTime: 100))

}

// exponentialMovingAverage calculates the exponential moving average
func exponentialMovingAverage(beta, previousAvg, incrementAvg float64) float64 {
	return (1-beta)*incrementAvg + beta*previousAvg
}

// getExpMovingAvgBytesPerSecond returns the exponential moving average for the bucket in bytes
func (m *bucketMeasurement) getExpMovingAvgBytesPerSecond() float64 {
	m.lock.Lock()

package testing

import (
	"runtime"
)

// AllocsPerRun returns the average number of allocations during calls to f.
// Although the return value has type float64, it will always be an integral value.
//
// To compute the number of allocations, the function will first be run once as
// a warm-up. The average number of allocations over the specified number of
// runs will then be measured and returned.
//

	sysCPUUser      = "user"
)

var (
	sysCPUAvgIdleMD   = NewGaugeMD(sysCPUAvgIdle, "Average CPU idle time")
	sysCPUAvgIOWaitMD = NewGaugeMD(sysCPUAvgIOWait, "Average CPU IOWait time")
	sysCPULoadMD      = NewGaugeMD(sysCPULoad, "CPU load average 1min")
	sysCPULoadPercMD  = NewGaugeMD(sysCPULoadPerc, "CPU load average 1min (percentage)")
	sysCPUNiceMD      = NewGaugeMD(sysCPUNice, "CPU nice time")

namespace tensorflow {
namespace calibrator {

using ::stablehlo::quantization::CalibrationOptions;

// AverageMinMax calibration calculates the average of min and max values.
// average of min = sum of min values / number of samples
// average of max = sum of max values / number of samples
class CalibrationStatisticsCollectorAverageMinMax
    : public CalibrationStatisticsCollectorBase {
 public:

var (
	replicationAverageActiveWorkersMD = NewGaugeMD(replicationAverageActiveWorkers,
		"Average number of active replication workers")
	replicationAverageQueuedBytesMD = NewGaugeMD(replicationAverageQueuedBytes,
		"Average number of bytes queued for replication since server start")
	replicationAverageQueuedCountMD = NewGaugeMD(replicationAverageQueuedCount,
		"Average number of objects queued for replication since server start")

| `minio_system_cpu_avg_idle`   | `gauge` | Average CPU idle time              | `server` |
| `minio_system_cpu_avg_iowait` | `gauge` | Average CPU IOWait time            | `server` |
| `minio_system_cpu_load`       | `gauge` | CPU load average 1min              | `server` |
| `minio_system_cpu_load_perc`  | `gauge` | CPU load average 1min (percentage) | `server` |

StringAttr GetAvgPoolOpPadAttr(Builder& builder, mhlo::CompositeOp op);

// Get dense attr for a matrix that corrects the over counting of divisors when
// casting an average pool with ceil mode on in terms of average pool with it
// off.
DenseFPElementsAttr GetCorrectionMatrix(Builder& builder, mhlo::CompositeOp op);

}  // namespace odml
}  // namespace mlir

  optional string name = 1;

  // targetAverageUtilization is the target value of the average of the
  // resource metric across all relevant pods, represented as a percentage of
  // the requested value of the resource for the pods.
  // +optional
  optional int32 targetAverageUtilization = 2;

  // targetAverageValue is the target value of the average of the
  // resource metric across all relevant pods, as a raw value (instead of as

	"targetAverageUtilization": "targetAverageUtilization is the target value of the average of the resource metric across all relevant pods, represented as a percentage of the requested value of the resource for the pods.",