* **Machine Learning**: Normalmente exige muita multiplicação de matrizes e vetores. Pense numa grande planilha com números e em multiplicar todos eles juntos e ao mesmo tempo.

* **Deep Learning**: Esse é um subcampo do Machine Learning, então, o mesmo se aplica. A diferença é que não há apenas uma grande planilha com números para multiplicar, mas um grande conjunto delas, e em muitos casos, você utiliza um processador especial para construir e/ou usar esses modelos.

 * <i>stripes</i>, increasing the granularity of a single lock and allowing independent operations
 * to lock different stripes and proceed concurrently, instead of creating contention for a single
 * lock.
 *
 * <p>The guarantee provided by this class is that equal keys lead to the same lock (or semaphore),
 * i.e. {@code if (key1.equals(key2))} then {@code striped.get(key1) == striped.get(key2)} (assuming

Durch die Berücksichtigung dieser Konzepte können Sie die beste Variante der Bereitstellung **Ihrer eigenen APIs** **evaluieren und konzipieren**.

In den nächsten Kapiteln werde ich Ihnen mehr **konkrete Rezepte** für die Bereitstellung von FastAPI-Anwendungen geben.

    private fun invalidLengths(strings: List<String>): Nothing = throw IOException("unexpected journal line: $strings")

    /**
     * Returns a snapshot of this entry. This opens all streams eagerly to guarantee that we see a
     * single published snapshot. If we opened streams lazily then the streams could come from
     * different edits.
     */
    internal fun snapshot(): Snapshot? {
      assertLockHeld()

   * returned, containing the values of {@code array}, and zeroes in the remaining places.
   *
   * @param array the source array
   * @param minLength the minimum length the returned array must guarantee
   * @param padding an extra amount to "grow" the array by if growth is necessary
   * @throws IllegalArgumentException if {@code minLength} or {@code padding} is negative

   * returned, containing the values of {@code array}, and zeroes in the remaining places.
   *
   * @param array the source array
   * @param minLength the minimum length the returned array must guarantee
   * @param padding an extra amount to "grow" the array by if growth is necessary
   * @throws IllegalArgumentException if {@code minLength} or {@code padding} is negative

   * returned, containing the values of {@code array}, and zeroes in the remaining places.
   *
   * @param array the source array
   * @param minLength the minimum length the returned array must guarantee
   * @param padding an extra amount to "grow" the array by if growth is necessary
   * @throws IllegalArgumentException if {@code minLength} or {@code padding} is negative

   *       simply switch over to use the JDK implementation wholesale if probable hash flooding is
   *       detected, sacrificing the compactness guarantee in very rare cases in exchange for much
   *       more reliable worst-case behavior.
   *   <li>null, if no entries have yet been added to the map
   * </ul>
   */
  private transient @Nullable Object table;

   * returned, containing the values of {@code array}, and zeroes in the remaining places.
   *
   * @param array the source array
   * @param minLength the minimum length the returned array must guarantee
   * @param padding an extra amount to "grow" the array by if growth is necessary
   * @throws IllegalArgumentException if {@code minLength} or {@code padding} is negative

// names will be modified if their name already exists in the graph. If false,
// conflicting names will be treated as an error. Note that this option has no
// effect if a prefix is set, since the prefix will guarantee all names are
// unique. Defaults to false.
TF_CAPI_EXPORT extern void TF_ImportGraphDefOptionsSetUniquifyNames(
    TF_ImportGraphDefOptions* opts, unsigned char uniquify_names);