*
 * <p>Lookups by row key are often faster than lookups by column key, because the data is stored in
 * a {@code Map<R, Map<C, V>>}. A method call like {@code column(columnKey).get(rowKey)} still runs
 * quickly, since the row key is provided. However, {@code column(columnKey).size()} takes longer,
 * since an iteration across all row keys occurs.
 *

        numberOfThreads,
        () -> {
          long unused = ticker.read();
          return null;
        });

    assertEquals(incrementByNanos * numberOfThreads, ticker.read());
  }

  /** Runs {@code callable} concurrently {@code numberOfThreads} times. */
  @GwtIncompatible // concurrency
  private void runConcurrentTest(int numberOfThreads, Callable<@Nullable Void> callable)
      throws Exception {

 *
 * <p>Lookups by row key are often faster than lookups by column key, because the data is stored in
 * a {@code Map<R, Map<C, V>>}. A method call like {@code column(columnKey).get(rowKey)} still runs
 * quickly, since the row key is provided. However, {@code column(columnKey).size()} takes longer,
 * since an iteration across all row keys occurs.
 *

on:
  schedule:
    - cron: "30 1 * * *"

permissions:
  contents: read

jobs:
  close-issues:
    # Don't do this in forks
    if: github.repository == 'tensorflow/tensorflow'
    runs-on: ubuntu-latest
    permissions:
      issues: write
      pull-requests: write
    steps:
      - name: Awaiting response issues
        uses: actions/stale@997185467fa4f803885201cee163a9f38240193d # v10.1.1

  @Param boolean noWorkToDo;

  Random random;
  String testString;

  @BeforeExperiment
  void setUp() {
    random = new Random(0xdeadbeef); // fix the seed so results are comparable across runs

    int nonAlpha = size / nonAlphaRatio;
    int alpha = size - nonAlpha;

    List<Character> chars = Lists.newArrayListWithCapacity(size);
    for (int i = 0; i < alpha; i++) {
      chars.add(randomAlpha());

   *             complete, the listener runs immediately in that thread.
   *         <li>When a thread attaches a listener to a {@code ListenableFuture} that's
   *             incomplete and the {@code ListenableFuture} later completes normally, the
   *             listener runs in the thread that completes the {@code ListenableFuture}.

         */
        public MonitorThread(final Process process, final long timeout) {
            this.process = process;
            this.timeout = timeout;
        }

        /**
         * Runs the monitor thread, sleeping for the timeout duration and terminating the process if needed.
         */
        @Override
        public void run() {
            ThreadUtil.sleepQuietly(timeout);

            parameters {
                keepClassesByCoordinates = keepPatterns
            }
        }
    }
    afterEvaluate {
        // Without afterEvaluate, configurations.all runs before the configurations' roles are set.
        // This is yet another reason we need configuration factory methods.
        // workaround for https://github.com/gradle/gradle/issues/12459

   */
  public static ListeningScheduledExecutorService noOpScheduledExecutor() {
    return new NoOpScheduledExecutorService();
  }

  /**
   * Creates a scheduled executor service that runs each task in the thread that invokes {@code
   * execute/submit/schedule}, as in {@link CallerRunsPolicy}. This applies both to individually

void GetDims(const TF_Tensor* t, int64_t* out_dims) {
  int num_dims = TF_NumDims(t);
  for (int i = 0; i < num_dims; i++) {
    out_dims[i] = TF_Dim(t, i);
  }
}

// Runs model as is if output is a scalar,
// else sums the output tensor before returning.
absl::Status RunAndMaybeSum(AbstractContext* ctx, Model forward,
                            absl::Span<AbstractTensorHandle* const> inputs,