}

		if gotFair != expectFair {
			uss.t.Errorf("%s client %d last=%v expectFair=%v margin=%v got an Average of %v but the expected average was %v", uss.name, i, last, expectFair, margin, averages[i], expectedAverage)
		} else {
			uss.t.Logf("%s client %d last=%v expectFair=%v margin=%v got an Average of %v and the expected average was %v", uss.name, i, last, expectFair, margin, averages[i], expectedAverage)
		}
	}

	}

	if target.AverageUtilization == nil {
		errMsg := "invalid resource metric source: neither an average utilization target nor an average value (usage) target was set"
		return 0, nil, time.Time{}, "", condition, fmt.Errorf(errMsg)
	}

	targetUtilization := *target.AverageUtilization

}

var blockprofilerate uint64 // in CPU ticks

// SetBlockProfileRate controls the fraction of goroutine blocking events
// that are reported in the blocking profile. The profiler aims to sample
// an average of one blocking event per rate nanoseconds spent blocked.
//
// To include every blocking event in the profile, pass rate = 1.
// To turn off profiling entirely, pass rate <= 0.
func SetBlockProfileRate(rate int) {

This is the first output from tf.nn.moments,
or a saved moving average thereof.}]>:$m,

	}
}

// blockFrequentShort produces 100000 block events with an average duration of
// rate / 10.
func blockFrequentShort(rate int) {
	for i := 0; i < 100000; i++ {
		blockevent(int64(rate/10), 1)
	}
}

// blockFrequentShort produces 10000 block events with an average duration of
// rate.
func blockInfrequentLong(rate int) {
	for i := 0; i < 10000; i++ {

	// half (a quarter overall) will be SLLS; an eighth will be SLLLS, and so on.
	// Not counting the final S in each (which overlaps the first S in the next),
	// This works out to an average length 2×½ + 3×¼ + 4×⅛ + ... = 3.
	// The space we need is further reduced by the fact that many of the
	// short patterns like SLS will often be the same character sequences

	}
	c.nextSample = nextSample()
	mProf_Malloc(mp, x, size)
}

// nextSample returns the next sampling point for heap profiling. The goal is
// to sample allocations on average every MemProfileRate bytes, but with a
// completely random distribution over the allocation timeline; this
// corresponds to a Poisson process with parameter MemProfileRate. In Poisson

	"internal/goarch"
	"internal/runtime/atomic"
	"runtime/internal/math"
	"unsafe"
)

const (
	// Maximum number of key/elem pairs a bucket can hold.
	bucketCntBits = abi.MapBucketCountBits

	// Maximum average load of a bucket that triggers growth is bucketCnt*13/16 (about 80% full)
	// Because of minimum alignment rules, bucketCnt is known to be at least 8.
	// Represent as loadFactorNum/loadFactorDen, to allow integer math.

     * traverse. When nodes would otherwise be changed, new nodes are created to replace them. This
     * works well for hash tables since the bin lists tend to be short. (The average length is less
     * than two.)
     *
     * Read operations can thus proceed without locking, but rely on selected uses of volatiles to

     * traverse. When nodes would otherwise be changed, new nodes are created to replace them. This
     * works well for hash tables since the bin lists tend to be short. (The average length is less
     * than two.)
     *
     * Read operations can thus proceed without locking, but rely on selected uses of volatiles to