*       instance of {@code BiMap}.
 *   <dt>{@link Table}
 *   <dd>A new type, which is similar to {@link java.util.Map}, but which indexes its values by an
 *       ordered pair of keys, a row key and column key.
 *   <dt>{@link Multiset}
 *   <dd>An extension of {@link java.util.Collection} that may contain duplicate values like a

						<em class="fa fa-cog">
						<la:message key="labels.advance" />
					</la:link>
				</div>
			</div>
		</div>
		<main class="container">
			<div class="row">
				<div class="col text-center searchFormBox">
					<h1 class="mainLogo">
						<img src="${fe:url('/images/logo.png')}"
							alt="<la:message key="labels.index_title" />" />
					</h1>

pkg crypto/x509, type RevocationList struct, ThisUpdate time.Time
pkg database/sql, method (*DB) SetConnMaxIdleTime(time.Duration)
pkg database/sql, method (*Row) Err() error
pkg database/sql, type DBStats struct, MaxIdleTimeClosed int64
pkg database/sql/driver, type Validator interface { IsValid }
pkg database/sql/driver, type Validator interface, IsValid() bool

    return Fingerprint2011.FINGERPRINT_2011;
  }

  /**
   * Assigns to {@code hashCode} a "bucket" in the range {@code [0, buckets)}, in a uniform manner
   * that minimizes the need for remapping as {@code buckets} grows. That is, {@code
   * consistentHash(h, n)} equals:
   *
   * <ul>
   *   <li>{@code n - 1}, with approximate probability {@code 1/n}
   *   <li>{@code consistentHash(h, n - 1)}, otherwise (probability {@code 1 - 1/n})

						<em class="fa fa-cog">
						<la:message key="labels.advance" />
					</la:link>
				</div>
			</div>
		</div>
		<main class="container">
			<div class="row">
				<div class="col text-center searchFormBox">
					<h1 class="mainLogo">
						<img src="${fe:url('/images/logo.png')}"
							alt="<la:message key="labels.index_title" />" />
					</h1>

				return
			}
		}
		// Once is set and we are here means error was already
		// printed once.
		if once {
			return
		}
		// once not set, check if same error occurred 3 times in
		// a row, then make sure we print it to call attention.
		if m[err.Error()] > 2 {
			peersLogAlwaysIf(ctx, fmt.Errorf("Following error has been printed %d times.. %w", m[err.Error()], err))

    *   Added L2 unit normalization layer `tf.keras.layers.UnitNormalization`.
    *   Added `tf.keras.regularizers.OrthogonalRegularizer`, a new regularizer
        that encourages orthogonality between the rows (or columns) or a weight
        matrix.
    *   Added `tf.keras.layers.RandomBrightness` layer for image preprocessing.
    *   Added APIs for switching between interactive logging and absl logging.

    return Fingerprint2011.FINGERPRINT_2011;
  }

  /**
   * Assigns to {@code hashCode} a "bucket" in the range {@code [0, buckets)}, in a uniform manner
   * that minimizes the need for remapping as {@code buckets} grows. That is, {@code
   * consistentHash(h, n)} equals:
   *
   * <ul>
   *   <li>{@code n - 1}, with approximate probability {@code 1/n}
   *   <li>{@code consistentHash(h, n - 1)}, otherwise (probability {@code 1 - 1/n})

78f4738947 title: 'Mastering Soft Delete: Advanced SQLAlchemy Techniques' - author: Shubhendra Kushwaha author_link: https://www.linkedin.com/in/theshubhendra/ link: https://theshubhendra.medium.com/role-based-row-filtering-advanced-sqlalchemy-techniques-733e6b1328f6 title: 'Role based row filtering: Advanced SQLAlchemy Techniques' German: - author: Marcel Sander (actidoo) author_link: https://www.actidoo.com link: https://www.actidoo.com/de/blog/python-fastapi-domain-driven-design title: Domain-driven...

        HashFunction hashFunction = (HashFunction) method.invoke(Hashing.class);
        assertTrue(
            "There should be at least 3 entries in KNOWN_HASHES for " + hashFunction,
            KNOWN_HASHES.row(hashFunction).size() >= 3);
      }
    }
  }

  public void testKnownUtf8Hashing() {
    for (Cell<HashFunction, String, String> cell : KNOWN_HASHES.cellSet()) {
      HashFunction func = cell.getRowKey();