// clear absent
    assertFalse(segment.clearValueForTesting(key, hash, valueRef));

    segment.setTableEntryForTesting(0, entry);
    // don't increment count; this is used during computation
    assertTrue(segment.clearValueForTesting(key, hash, valueRef));
    // no notification sent with clearValue
    assertEquals(0, segment.count);
    assertThat(table.get(0)).isNull();

    // clear absent
    assertFalse(segment.clearValueForTesting(key, hash, valueRef));

    segment.setTableEntryForTesting(0, entry);
    // don't increment count; this is used during computation
    assertTrue(segment.clearValueForTesting(key, hash, valueRef));
    // no notification sent with clearValue
    assertEquals(0, segment.count);
    assertThat(table.get(0)).isNull();

 *       SMALL_DELAY_MS}, {@code MEDIUM_DELAY_MS}, {@code LONG_DELAY_MS}. The idea here is that a
 *       SHORT is always discriminable from zero time, and always allows enough time for the small
 *       amounts of computation (creating a thread, calling a few methods, etc) needed to reach a
 *       timeout point. Similarly, a SMALL is always discriminable as larger than SHORT and smaller

    *   oneDNN optimizations can yield slightly different numerical results compared to when oneDNN optimizations are disabled due to floating-point round-off errors from
 different computation approaches and orders.
    *   To verify if oneDNN optimizations are on, look for a message with *"oneDNN custom operations are on"* in the log. If the exact phrase is not there, it means they are off.

        .isEqualTo(EntryFactory.WEAK_WRITE);
    assertThat(EntryFactory.getFactory(Strength.WEAK, true, true))
        .isEqualTo(EntryFactory.WEAK_ACCESS_WRITE);
  }

  // computation tests

  public void testCompute() throws ExecutionException {
    CountingLoader loader = new CountingLoader();
    LocalCache<Object, Object> map = makeLocalCache(createCacheBuilder());

        .isEqualTo(EntryFactory.WEAK_WRITE);
    assertThat(EntryFactory.getFactory(Strength.WEAK, true, true))
        .isEqualTo(EntryFactory.WEAK_ACCESS_WRITE);
  }

  // computation tests

  public void testCompute() throws ExecutionException {
    CountingLoader loader = new CountingLoader();
    LocalCache<Object, Object> map = makeLocalCache(createCacheBuilder());

   * segments, each governed by its own write lock. The segment lock is taken once for each explicit
   * write, and twice for each cache loading computation (once prior to loading the new value, and
   * once after loading completes). Much internal cache management is performed at the segment
   * granularity. For example, access queues and write queues are kept per segment when they are

// - export functions to set Config fields

// --------------------------------------------------------------------------
// The new graph construction API, still under development.

// Represents a computation graph.  Graphs may be shared between sessions.
// Graphs are thread-safe when used as directed below.
typedef struct TF_Graph TF_Graph;

// Return a new graph object.
TF_CAPI_EXPORT extern TF_Graph* TF_NewGraph(void);

     * expected</i>, but not absolutely required, to have the following properties:
     *
     * <ul>
     *   <li>Its execution does not cause any observable side effects.
     *   <li>The computation is <i>consistent with equals</i>; that is, {@link Objects#equals
     *       Objects.equals}{@code (k1, k2) &&} {@link Objects#equals Objects.equals}{@code (v1,

     * expected</i>, but not absolutely required, to have the following properties:
     *
     * <ul>
     *   <li>Its execution does not cause any observable side effects.
     *   <li>The computation is <i>consistent with equals</i>; that is, {@link Objects#equals
     *       Objects.equals}{@code (k1, k2) &&} {@link Objects#equals Objects.equals}{@code (v1,