// start
        AccessTimeoutTarget accessTimeoutTarget = null;
        TimeoutTask accessTimeoutTask = null;
        if (accessTimeout != null) {
            accessTimeoutTarget = new AccessTimeoutTarget(Thread.currentThread());
            accessTimeoutTask = TimeoutManager.getInstance().addTimeoutTarget(accessTimeoutTarget, accessTimeout, false);
        }

        try {
            return processHttpMethod(url, httpRequest);

    /** The key of the message: Name */
    public static final String LABELS_NAME = "{labels.name}";

    /** The key of the message: Number of Threads */
    public static final String LABELS_NUM_OF_THREAD = "{labels.numOfThread}";

    /** The key of the message: Duplicate Host Name */
    public static final String LABELS_DUPLICATE_HOST_NAME = "{labels.duplicateHostName}";

   * values.
   *
   * <p>Elements are copied from the argument collection as if by {@code collection.toArray()}.
   * Calling this method is as thread-safe as calling that method.
   *
   * <p><b>Note:</b> consider representing the collection as a {@link java.util.BitSet} instead.
   *
   * @param collection a collection of {@code Boolean} objects

			yBytes := Repeat(y, growLen)
			allocs := testing.AllocsPerRun(100, func() {
				buf.Grow(growLen)
				buf.Write(yBytes)
			})
			// Check no allocation occurs in write, as long as we're single-threaded.
			if allocs != 0 {
				t.Errorf("allocation occurred during write")
			}
			// Check that buffer has correct data.
			if !Equal(buf.Bytes()[0:startLen-readBytes], xBytes[readBytes:]) {

 * }
 *
 * <p>Instances of {@link ImmutableGraph} do not implement {@link MutableGraph} (obviously!) and are
 * contractually guaranteed to be unmodifiable and thread-safe.
 *
 * <p>The Guava User Guide has <a
 * href="https://github.com/google/guava/wiki/GraphsExplained#building-graph-instances">more
 * information on (and examples of) building graphs</a>.
 *

// Usually this happens automatically in TF_SessionRun. After this is called,
// TF_SessionRun will no longer extend the session on every call.
//
// We expose this here to allow fine-grained synchronization in multi-threaded
// workloads, which is required since the Python implementation depends on the
// above mutation methods. This allows us to prevent modifications to nodes in
// the graph after the session has been made aware of them.

## Bug Fixes and Other Changes

*   Use threadsafe version of `lgamma` function.
*   Fix `tf.sqrt` handling of negative arguments.
*   Fixed bug causing incorrect number of threads to be used for multi-threaded
    benchmarks.
*   Performance optimizations for `batch_matmul` on multi-core CPUs.
*   Improve trace, `matrix_set_diag`, `matrix_diag_part` and their gradients to
    work for rectangular matrices.

     * @param initialCapacity the initial capacity
     * @param loadFactor the load factor threshold for resizing
     * @param concurrencyLevel the estimated number of threads for concurrent updates
     * @return a new instance of {@link ConcurrentHashMap}
     * @see ConcurrentHashMap#ConcurrentHashMap(int, float, int)
     */

  public abstract int size();

  /**
   * Returns the stripes that correspond to the passed objects, in ascending (as per {@link
   * #getAt(int)}) order. Thus, threads that use the stripes in the order returned by this method
   * are guaranteed to not deadlock each other.
   *
   * <p>It should be noted that using a {@code Striped<L>} with relatively few stripes, and {@code

   * allow in normal conditions. This is enforced by "throttling" incoming requests as needed. For
   * example, we could compute the appropriate throttle time for an incoming request, and make the
   * calling thread wait for that time.
   *
   * The simplest way to maintain a rate of QPS is to keep the timestamp of the last granted
   * request, and ensure that (1/QPS) seconds have elapsed since then. For example, for a rate of