if len(disks) < er.setDriveCount/2 {
			return fmt.Errorf("not enough drives (found=%d, healing=%d, total=%d) are available to heal `%s`", len(disks), healing, er.setDriveCount, tracker.disk.String())
		}

		rand.Shuffle(len(disks), func(i, j int) {
			disks[i], disks[j] = disks[j], disks[i]
		})

		expectedDisks := len(disks)/2 + 1
		fallbackDisks := disks[expectedDisks:]
		disks = disks[:expectedDisks]

      misses.add("INVALID");
    }

    List<String> sampleDataList = new ArrayList<>();
    sampleDataList.addAll(hits);
    sampleDataList.addAll(misses);
    Collections.shuffle(sampleDataList);
    sampleData = sampleDataList.toArray(new String[sampleDataList.size()]);
  }

  // Since we can't pass a concrete SomeEnum.class directly, we need to use a raw type.
  @SuppressWarnings("unchecked")

      misses.add("INVALID");
    }

    List<String> sampleDataList = new ArrayList<>();
    sampleDataList.addAll(hits);
    sampleDataList.addAll(misses);
    Collections.shuffle(sampleDataList);
    sampleData = sampleDataList.toArray(new String[sampleDataList.size()]);
  }

  // Since we can't pass a concrete SomeEnum.class directly, we need to use a raw type.
  @SuppressWarnings("unchecked")

			NextCycle: oldCache.Info.NextCycle,
		},
		Cache: make(map[string]dataUsageEntry, len(oldCache.Cache)),
	}

	// Put all buckets into channel.
	bucketCh := make(chan BucketInfo, len(buckets))

	// Shuffle buckets to ensure total randomness of buckets, being scanned.
	// Otherwise same set of buckets get scanned across erasure sets always.
	// at any given point in time. This allows different buckets to be scanned

pkg math, func RoundToEven(float64) float64
pkg math/big, const MaxBase = 62
pkg math/big, method (*Float) Sqrt(*Float) *Float
pkg math/big, method (*Int) CmpAbs(*Int) int
pkg math/rand, func Shuffle(int, func(int, int))
pkg math/rand, method (*Rand) Shuffle(int, func(int, int))
pkg net, method (*TCPListener) SyscallConn() (syscall.RawConn, error)
pkg net, method (*UnixListener) SyscallConn() (syscall.RawConn, error)

		askDisks = len(disks) // use all available drives
	}

	// However many we ask, versions must exist on ~50%
	listingQuorum := (askDisks + 1) / 2

	if askDisks > 0 && len(disks) > askDisks {
		rand.Shuffle(len(disks), func(i, j int) {
			disks[i], disks[j] = disks[j], disks[i]
		})
		fallbackDisks = disks[askDisks:]
		disks = disks[:askDisks]
	}

	// How to resolve results.

 * randomly ordered data (the probability decreases faster than exponentially in N), but if you are
 * passing in unsanitized user data then a malicious user could force it. A light shuffle of the
 * data using an unpredictable seed should normally be enough to thwart this attack.
 *
 * <p>The time taken to compute multiple quantiles on the same dataset using {@link Scale#indexes

		// Run for a number of times, shuffling the input to ensure that output is consistent.
		for i := 0; i < 10; i++ {
			t.Run(fmt.Sprintf("test-%d-%s-run-%d", testID, tt.name, i), func(t *testing.T) {
				if i > 0 {
					rng.Shuffle(len(tt.m), func(i, j int) {
						tt.m[i], tt.m[j] = tt.m[j], tt.m[i]
					})
				}
				gotSelected, gotOk := tt.m.resolve(&tt.r)
				if gotOk != tt.wantOk {

	if seed != -1 {
		rand.Seed(seed)
	}
	return rand.Intn(max-min) + min
}

// Randomizes the order of bytes in the byte array
// using Knuth Fisher-Yates shuffle algorithm.
func randomizeBytes(s []byte, seed int64) []byte {
	// special value -1 means no explicit seeding.
	if seed != -1 {
		rand.Seed(seed)
	}
	n := len(s)
	var j int

    *   `tf.data.Dataset.zip` now supports Python-style zipping, i.e. `Dataset.zip(a, b, c)`.
    * `tf.data.Dataset.shuffle` now supports `tf.data.UNKNOWN_CARDINALITY` When doing a "full shuffle" using  `dataset = dataset.shuffle(dataset.cardinality())`. But remember, a "full shuffle" will load the full dataset into memory so that it can be shuffled, so make sure to only use this with small datasets or datasets of small objects (like filenames).

*   `tf.math`