// The values will be averaged together before being compared to the target
// value.
type PodsMetricSource struct {
	// metricName is the name of the metric in question
	MetricName string `json:"metricName" protobuf:"bytes,1,name=metricName"`

	// targetAverageValue is the target value of the average of the
	// metric across all relevant pods (as a quantity)

	// +optional
	Selector *metav1.LabelSelector `json:"selector,omitempty" protobuf:"bytes,2,name=selector"`
}

// MetricTarget defines the target value, average value, or average utilization of a specific metric
type MetricTarget struct {
	// type represents whether the metric type is Utilization, Value, or AverageValue
	Type MetricTargetType `json:"type" protobuf:"bytes,1,name=type"`

| `minio_node_cpu_avg_load5`           | CPU load average 5min.                     |
| `minio_node_cpu_avg_load5_avg`       | CPU load average 5min (avg).               |
| `minio_node_cpu_avg_load5_max`       | CPU load average 5min (max).               |
| `minio_node_cpu_avg_load5_perc`      | CPU load average 5min (percentage).        |

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

  // for any `x`, `ceil(x) - floor(x) <= 1`.

  // Consider that we pad the input of a average pool with floor rounding to the
  // appropriate size and switch the rounding mode to ceil. When computing the
  // average of a given window, the elements which exist in the newly padded
  // zones will be counted as present elements. Therefore in some windows we

		cpuNice:           "CPU nice time",
		cpuLoad1:          "CPU load average 1min",
		cpuLoad5:          "CPU load average 5min",
		cpuLoad15:         "CPU load average 15min",
		cpuLoad1Perc:      "CPU load average 1min (perentage)",
		cpuLoad5Perc:      "CPU load average 5min (percentage)",
		cpuLoad15Perc:     "CPU load average 15min (percentage)",
	}
	resourceMetricsGroups = []*MetricsGroupV2{

// AVERAGE-MIN-MAX-CHECK-NEXT:  "tf.AddV2"
// AVERAGE-MIN-MAX-CHECK-NEXT:  return

// AVERAGE-MIN-MAX-CHECK: func @composite_conv2d_with_relu6_fn
// AVERAGE-MIN-MAX-CHECK-NEXT:  "tf.Conv2D"
// AVERAGE-MIN-MAX-CHECK-NEXT:  "tf.Relu6"
// AVERAGE-MIN-MAX-CHECK-NEXT:  return

// CalibrationOptions(
//   calibration_method=CALIBRATION_METHOD_HISTOGRAM_PERCENTILE,

		allDriveLabels...)
	driveWaitingIOMD = NewGaugeMD(driveWaitingIO,
		"Total waiting I/O operations on a drive", allDriveLabels...)
	driveAPILatencyMD = NewGaugeMD(driveAPILatencyMicros,
		"Average last minute latency in µs for drive API storage operations",
		append(allDriveLabels, apiL)...)
	driveHealthMD = NewGaugeMD(driveHealth,
		"Drive health (0 = offline, 1 = healthy, 2 = healing)", allDriveLabels...)