abstract: TensorFlow is a machine learning system that operates at large scale and in heterogeneous environments. TensorFlow uses dataflow graphs to represent computation, shared state, and the operations that mutate that state. It maps the nodes of a dataflow graph across many machines in a cluster, and 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...

 *
 * @author Pete Gillin
 */
@NullUnmarked
public class QuantilesTest extends TestCase {

  /*
   * Since Quantiles provides a fluent-style API, each test covers a chain of methods resulting in
   * the computation of one or more quantiles (or in an error) rather than individual methods. The
   * tests are divided into three sections:
   * 1. Tests on a hardcoded dataset for chains starting with median(), quartiles(), and scale(10);

 *
 * @author Pete Gillin
 */
@NullUnmarked
public class QuantilesTest extends TestCase {

  /*
   * Since Quantiles provides a fluent-style API, each test covers a chain of methods resulting in
   * the computation of one or more quantiles (or in an error) rather than individual methods. The
   * tests are divided into three sections:
   * 1. Tests on a hardcoded dataset for chains starting with median(), quartiles(), and scale(10);

   * 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#equal
   *       Objects.equal}{@code (a, b)} implies that {@code predicate.apply(a) ==
   *       predicate.apply(b))}.
   * </ul>
   *

   * computation is {@linkplain java.util.concurrent.Future#isDone() complete} or, if the
   * computation is already complete, immediately.
   *
   * <p>The callback is run on {@code executor}. There is no guaranteed ordering of execution of
   * callbacks, but any callback added through this method is guaranteed to be called once the
   * computation is complete.
   *
   * <p>Example:
   *

import java.util.concurrent.atomic.AtomicReference;
import org.jspecify.annotations.Nullable;

/**
 * A step in a pipeline of an asynchronous computation. When the last step in the computation is
 * complete, some objects captured during the computation are closed.
 *
 * <p>A pipeline of {@code ClosingFuture}s is a tree of steps. Each step represents either an

///

## Resource Utilization { #resource-utilization }

Your server(s) is (are) a **resource**, you can consume or **utilize**, with your programs, the computation time on the CPUs, and the RAM memory available.

You can see more details in <a href="https://www.starlette.io/background/" class="external-link" target="_blank">Starlette's official docs for Background Tasks</a>.

## Caveat { #caveat }

   * computation is {@linkplain java.util.concurrent.Future#isDone() complete} or, if the
   * computation is already complete, immediately.
   *
   * <p>The callback is run on {@code executor}. There is no guaranteed ordering of execution of
   * callbacks, but any callback added through this method is guaranteed to be called once the
   * computation is complete.
   *

          }
        };

    recursiveCache = CacheBuilder.newBuilder().weakKeys().weakValues().build(recursiveLoader);
    cacheRef.set(recursiveCache);

    // tells the test when the computation has completed
    CountDownLatch doneSignal = new CountDownLatch(1);

    Thread thread =
        new Thread() {
          @Override
          public void run() {
            try {