within a machine across multiple computational devices, including multicore CPUs, general purpose GPUs, and custom-designed ASICs known as Tensor Processing Units (TPUs). This architecture gives flexibility to the application developer, whereas in previous “parameter server” designs the management of shared state is built into the system, TensorFlow enables developers to experiment with novel optimizations and training algorithms. TensorFlow supports a variety of applications, with a focus on training...

         * processes one artifact at a time and hence cannot associate the artifacts from the same project to use the
         * same version index. Allowing the caller to pass in metadata from a previous deployment allows to re-establish
         * the association between the artifacts of the same project.
         */
        for (Iterator<? extends Metadata> it = metadatas.iterator(); it.hasNext(); ) {

         * @return the total page count
         */
        public int getAllPageCount() {
            return allPageCount;
        }

        /**
         * Checks if a previous page exists.
         *
         * @return true if there is a previous page, false otherwise
         */
        public boolean isExistPrePage() {
            return currentPageNumber != 1;
        }

        /**

}

// Entry is an LRU Entry
type Entry[K comparable, V any] struct {
	// Next and previous pointers in the doubly-linked list of elements.
	// To simplify the implementation, internally a list l is implemented
	// as a ring, such that &l.root is both the next element of the last
	// list element (l.Back()) and the previous element of the first list
	// element (l.Front()).
	next, prev *Entry[K, V]

         * processes one artifact at a time and hence cannot associate the artifacts from the same project to use the
         * same timestamp+buildno for the snapshot versions. Allowing the caller to pass in metadata from a previous
         * deployment allows to re-establish the association between the artifacts of the same project.
         */
        for (Metadata metadata : request.getMetadata()) {

	if globalServiceFreezeCnt <= 0 {
		// Set to a nil channel.
		var _ch chan struct{}
		if val := globalServiceFreeze.Swap(_ch); val != nil {
			if ch, ok := val.(chan struct{}); ok && ch != nil {
				// Close previous non-nil channel.
				xioutil.SafeClose(ch)
			}
		}
		globalServiceFreezeCnt = 0 // Don't risk going negative.
	}
	globalServiceFreezeMu.Unlock()

         * processes one artifact at a time and hence cannot associate the artifacts from the same project to use the
         * same version index. Allowing the caller to pass in metadata from a previous deployment allows to re-establish
         * the association between the artifacts of the same project.
         */
        for (Iterator<? extends Metadata> it = metadatas.iterator(); it.hasNext(); ) {

    assertEquals(0, runCalled.get());
    okayToRun.countDown();
    thread1.join();
    thread2.join();
    assertEquals(1, runCalled.get());
  }

  public void testAddAfterRun() throws Exception {
    // Run the previous test
    testRunOnPopulatedList();

    // If it passed, then verify an Add will be executed without calling run
    CountDownLatch countDownLatch = new CountDownLatch(1);

	"github.com/minio/minio/internal/kms"
)

const (
	minioConfigPrefix = "config"
	minioConfigBucket = minioMetaBucket + SlashSeparator + minioConfigPrefix
	kvPrefix          = ".kv"

	// Captures all the previous SetKV operations and allows rollback.
	minioConfigHistoryPrefix = minioConfigPrefix + "/history"

	// MinIO configuration file.
	minioConfigFile = "config.json"
)

     * @param securityMode
     *            the security mode flags for the session
     * @param capabilities
     *            the client capabilities
     * @param previousSessionid
     *            the previous session ID for reconnection (or 0 for new session)
     * @param token
     *            the security token for authentication
     */