* converter.reverse().convert(converter.convert(a)).equals(a)} is always true). However, it is very
 * common (perhaps <i>more</i> common) for round-trip conversion to be <i>lossy</i>. Consider an
 * example round-trip using {@link com.google.common.primitives.Doubles#stringConverter}:
 *
 * <ol>
 *   <li>{@code stringConverter().convert("1.00")} returns the {@code Double} value {@code 1.0}

	if !is64Bit {
		return
	}

	runTestCases("64-bit", []testCase{
		0: {"-", maxInt, "out of range"},
	})
}

type RunesTest struct {
	in    string
	out   []rune
	lossy bool
}

var RunesTests = []RunesTest{
	{"", []rune{}, false},
	{" ", []rune{32}, false},
	{"ABC", []rune{65, 66, 67}, false},
	{"abc", []rune{97, 98, 99}, false},

 */
public enum HandleType {
    /**
     * No durability - standard handle
     */
    NONE(0),

    /**
     * SMB 2.1 durable handle - survives network loss
     */
    DURABLE_V1(1),

    /**
     * SMB 3.0 durable handle V2 - with timeout configuration
     */
    DURABLE_V2(2),

    /**
     * SMB 3.0 persistent handle - survives server reboot
     */

    this.max = max;
  }

  /**
   * Returns statistics over a dataset containing the given values.
   *
   * @param values a series of values, which will be converted to {@code double} values (this may
   *     cause loss of precision)
   */
  public static Stats of(Iterable<? extends Number> values) {
    StatsAccumulator accumulator = new StatsAccumulator();
    accumulator.addAll(values);
    return accumulator.snapshot();
  }

        for (long time : testTimes) {
            SMBUtil.writeTime(time, buffer, 0);
            long readTime = SMBUtil.readTime(buffer, 0);

            // Account for precision loss in conversion
            long expectedTime = ((time + SmbConstants.MILLISECONDS_BETWEEN_1970_AND_1601) * 10000L) / 10000L
                    - SmbConstants.MILLISECONDS_BETWEEN_1970_AND_1601;

        DirectoryCacheEntry entry = directoryLeaseManager.getCacheEntry(directoryPath);
        entry.updateChild("file1.txt", 1024L, 1000L, false, 0x20, 500L, 800L);
        entry.markComplete();

        // Break lease with loss of read cache
        int newState = Smb2LeaseState.SMB2_LEASE_HANDLE_CACHING; // Lost read cache
        directoryLeaseManager.handleDirectoryLeaseBreak(leaseKey, newState);

        // Cache should be invalidated

![Erasure](https://github.com/minio/minio/blob/master/docs/screenshots/erasure-code.jpg?raw=true)

## What is Bit Rot protection?

Bit Rot, also known as data rot or silent data corruption is a data loss issue faced by disk drives today. Data on the drive may silently get corrupted without signaling an error has occurred, making bit rot more dangerous than a permanent hard drive failure.

of `Policy` optionally took in a `tf.compat.v1.mixed_precision.LossScale` in the constructor, which defaulted to a dynamic loss scale for the `"mixed_float16"` policy and no loss scale for other policies. In `Model.compile`, if the model's policy had a loss scale, the optimizer would be wrapped with a `LossScaleOptimizer`. With the non-experimental `Policy`, there is no loss scale associated with the `Policy`, and `Model.compile` wraps the optimizer with a `LossScaleOptimizer` if and only if the...

        PacDataInputStream pdis = createInputStream(data);
        Date date = pdis.readFiletime();
        assertNotNull(date);
        // Allow for a small difference due to precision loss
        assertEquals(time / 1000, date.getTime() / 1000);

        // Test with null date (0x7fffffff ffffffff)

        // Step 9: Test lease break
        // Re-populate cache
        directoryLeaseManager.updateDirectoryCache(directoryPath, files);
        assertTrue(cacheEntry.isComplete());

        // Simulate lease break with loss of read cache
        directoryLeaseManager.handleDirectoryLeaseBreak(leaseKey, Smb2LeaseState.SMB2_LEASE_HANDLE_CACHING);

        // Cache should be invalidated
        assertFalse(cacheEntry.isComplete());