* Stop the service. This method is invoked on the execution thread.
   *
   * <p>By default this method does nothing.
   */
  // TODO: consider supporting a TearDownTestCase-like API
  protected void shutDown() throws Exception {}

  /**
   * Invoked to request the service to stop.
   *
   * <p>By default this method does nothing.
   *

   *
   * <p>Like {@link BufferedReader#readLine()}, this method considers a line to be a sequence of
   * text that is terminated by (but does not include) one of {@code \r\n}, {@code \r} or {@code
   * \n}. If the source's content does not end in a line termination sequence, it is treated as if
   * it does.
   *
   * @throws IOException if an I/O error occurs while reading from this source
   */
  @CheckForNull

   * edges().contains(endpoints)}.
   *
   * <p>Unlike the other {@code EndpointPair}-accepting methods, this method does not throw if the
   * endpoints are unordered and the graph is directed; it simply returns {@code false}. This is for
   * consistency with the behavior of {@link Collection#contains(Object)} (which does not generally
   * throw if the object cannot be present in the collection), and the desire to have this method's

   *
   * <ul>
   *   <li>Its execution does not cause any observable side effects.
   *   <li>The computation is <i>consistent with equals</i>; that is, {@link Objects#equal
   *       Objects.equal}{@code (a, b)} implies that {@code predicate.apply(a) ==
   *       predicate.apply(b))}.
   * </ul>
   *
   * @throws NullPointerException if {@code input} is null and this predicate does not accept null
   *     arguments
   */

   
   
   *TensorFlow release binaries version 1.6 and higher are prebuilt with AVX instruction sets.*
   
   
   Therefore on any CPU that does not have these instruction sets, either CPU or GPU version of TF will fail to load.
   
   Apparently, your CPU model does not support AVX instruction sets. You can still use TensorFlow with the alternatives given below:
   
      * Try Google Colab to use TensorFlow.

    return AllEqualOrdering.INSTANCE;
  }

  /**
   * Returns an ordering that compares objects by the natural ordering of their string
   * representations as returned by {@code toString()}. It does not support null values.
   *
   * <p>The comparator is serializable.
   *
   * <p><b>Java 8+ users:</b> Use {@code Comparator.comparing(Object::toString)} instead.
   */
  @GwtCompatible(serializable = true)

   * href="http://en.wikipedia.org/wiki/Memoization">memoization</a>
   *
   * <p>The returned supplier is thread-safe. The supplier's serialized form does not contain the
   * cached value, which will be recalculated when {@code get()} is called on the reserialized
   * instance. The actual memoization does not happen when the underlying delegate throws an
   * exception.
   *

# Deployment

Deploying a **FastAPI** application is relatively easy.

## What Does Deployment Mean

To **deploy** an application means to perform the necessary steps to make it **available to the users**.

For a **web API**, it normally involves putting it in a **remote machine**, with a **server program** that provides good performance, stability, etc, so that your **users** can **access** the application efficiently and without interruptions or problems.

  }

  /**
   * Returns the {@code b} to the {@code k}th power, provided it does not overflow.
   *
   * <p>{@link #pow} may be faster, but does not check for overflow.
   *
   * @throws ArithmeticException if {@code b} to the {@code k}th power overflows in signed {@code
   *     int} arithmetic
   */
  public static int checkedPow(int b, int k) {
    checkNonNegative("exponent", k);
    switch (b) {

            // ```
            // when {
            //   true, false -> {}
            // }
            // ```
            // `false` does not have a corresponding elements on the FIR side and hence the containing `FirWhenBranch` is returned. In this
            // case, we simply report null since FIR does not know about it.
            else -> null
        }
    }