}

        // Simple heuristic based on data entropy
        // In practice, this would be more sophisticated
        int uniqueBytes = countUniqueBytes(data);
        double entropy = (double) uniqueBytes / 256.0;

        // Estimate compression ratio based on entropy
        // Lower entropy = better compression
        return 0.3 + (entropy * 0.6); // Range from 30% to 90%
    }

    @Override

            uniqueCounters.add(bytesToHex(counter));
        }

        // All nonces should be unique (high entropy from SecureRandom)
        assertEquals(sampleSize, uniqueCounters.size(), "All nonces should have unique values");

        // Verify that nonces have good entropy (not predictable)
        // With SecureRandom + counter XOR, they should all be different
        Set<String> uniqueNonces = new HashSet<>();

        `tf.initializers = tf.keras.initializers` & `tf.optimizers =
        tf.keras.optimizers`.
    *   Updates binary cross entropy logic in Keras when input is probabilities.
        Instead of converting probabilities to logits, we are using the cross
        entropy formula for probabilities.
    *   Added public APIs for `cumsum` and `cumprod` keras backend functions.

      int expectedEntrySetHash = 0;
      for (Entry<K, V> entry : entrySet) {
        assertTrue(map.containsKey(entry.getKey()));
        assertTrue(map.containsValue(entry.getValue()));
        int expectedHash =
            (entry.getKey() == null ? 0 : entry.getKey().hashCode())
                ^ (entry.getValue() == null ? 0 : entry.getValue().hashCode());
        assertEquals(expectedHash, entry.hashCode());

    }

    /**
     * Get cache entry for a directory
     *
     * @param directoryPath directory path
     * @return cache entry or null
     */
    public DirectoryCacheEntry getCacheEntry(String directoryPath) {
        DirectoryCacheEntry entry = directoryCache.get(directoryPath);

        // Check if cache entry is valid
        if (entry != null && entry.needsRefresh()) {

        private final Entry<K, V> entry;

        private Map1(K key, V value) {
            this.entry = new SimpleImmutableEntry<>(key, value);
        }

        @Override
        public Set<Entry<K, V>> entrySet() {
            return new AbstractImmutableSet<>() {
                @Override
                public Iterator<Entry<K, V>> iterator() {

  public @Nullable Entry<E> pollFirstEntry() {
    Iterator<Entry<E>> entryIterator = entryIterator();
    if (entryIterator.hasNext()) {
      Entry<E> result = entryIterator.next();
      result = Multisets.immutableEntry(result.getElement(), result.getCount());
      entryIterator.remove();
      return result;
    }
    return null;
  }

  @Override
  public @Nullable Entry<E> pollLastEntry() {

    /**
     * Adds user attributes to the LDAP entry for user creation.
     *
     * @param entry the BasicAttributes to add user attributes to
     * @param user the user object containing attribute values
     */
    protected void addUserAttributes(final BasicAttributes entry, final User user) {
        entry.put(new BasicAttribute("cn", user.getName()));

func (o *listPathOptions) shouldSkip(ctx context.Context, entry metaCacheEntry) (yes bool) {
	if !o.IncludeDirectories && (entry.isDir() || (!o.Versioned && entry.isObjectDir() && entry.isLatestDeletemarker())) {
		return true
	}
	if o.Marker != "" && entry.name < o.Marker {
		return true
	}
	if !strings.HasPrefix(entry.name, o.Prefix) {
		return true
	}

    /**
     * construct a single vertex
     */
    public MetadataGraph(MetadataGraphVertex entry) throws MetadataResolutionException {
        checkVertex(entry);
        checkVertices(1);

        entry.setCompareVersion(versionedVertices);
        entry.setCompareScope(scopedVertices);

        vertices.add(entry);
        this.entry = entry;
    }
    // ------------------------------------------------------------------------