#include "tensorflow/c/experimental/filesystem/modular_filesystem.h"
#include "tensorflow/cc/framework/gradients.h"
#include "tensorflow/cc/framework/ops.h"
#include "tensorflow/cc/framework/scope_internal.h"
#include "tensorflow/cc/ops/while_loop.h"
#include "tensorflow/cc/saved_model/loader.h"
#include "tensorflow/core/distributed_runtime/server_lib.h"
#include "tensorflow/core/framework/logging.h"

  }

  @Override
  public <S extends Comparable<?>> Ordering<S> reverse() {
    return Ordering.natural();
  }

  // Override the min/max methods to "hoist" delegation outside loops

  @Override
  public <E extends Comparable<?>> E min(E a, E b) {
    return NaturalOrdering.INSTANCE.max(a, b);
  }

  @Override
  public <E extends Comparable<?>> E min(E a, E b, E c, E... rest) {

        original.setUrl("http://example.com");

        // Serialize
        ByteArrayOutputStream baos = new ByteArrayOutputStream();
        ObjectOutputStream oos = new ObjectOutputStream(baos);
        oos.writeObject(original);
        oos.close();

        // Deserialize
        ByteArrayInputStream bais = new ByteArrayInputStream(baos.toByteArray());
        ObjectInputStream ois = new ObjectInputStream(bais);

  @SuppressWarnings("unchecked") // how to explain?
  @Override
  public <S extends T> Ordering<S> reverse() {
    return (Ordering<S>) forwardOrder;
  }

  // Override the min/max methods to "hoist" delegation outside loops

  @Override
  public <E extends T> E min(@ParametricNullness E a, @ParametricNullness E b) {
    return forwardOrder.max(a, b);
  }

  @Override
  public <E extends T> E min(

        double overallTimeMs = (overallEnd - overallStart) / 1_000_000.0;
        double avgThreadTimeMs = totalTime.get() / (threadCount * 1_000_000.0);

        System.out.printf("Connection Pool Performance: %d ops in %.2f ms (%.2f ms avg per thread)%n", successCount.get(), overallTimeMs,
                avgThreadTimeMs);

        // Verify performance improvements

    ByteArrayOutputStream bytes = new ByteArrayOutputStream();
    ObjectOutputStream oos = new ObjectOutputStream(bytes);
    oos.writeObject(map);
    oos.flush();

    int mapSize = bytes.size();
    oos.writeObject(keySet);
    oos.writeObject(values);
    oos.close();

    int finalSize = bytes.size();

    assertThat(finalSize - mapSize).isLessThan(100);
  }

   * self-loops twice (equivalently, the number of times an edge touches {@code node}).
   *
   * <p>For directed networks, this is equal to {@code inDegree(node) + outDegree(node)}.
   *
   * <p>For undirected networks, this is equal to {@code incidentEdges(node).size()} + (number of
   * self-loops incident to {@code node}).
   *

  @SuppressWarnings("unchecked")
  <T> T serialClone(T o) {
    try {
      ByteArrayOutputStream bos = new ByteArrayOutputStream();
      ObjectOutputStream oos = new ObjectOutputStream(bos);
      oos.writeObject(o);
      oos.flush();
      oos.close();
      ObjectInputStream ois = new ObjectInputStream(new ByteArrayInputStream(bos.toByteArray()));
      T clone = (T) ois.readObject();

      ASSERT_EQ(expected[i], data[i]) << "Different data at index " << i;
    }
  }

  std::vector<TF_Output> ToOutput(const std::vector<TF_Operation*> ops) {
    std::vector<TF_Output> out;
    for (auto op : ops) {
      out.push_back({op, 0});
    }
    return out;
  }

  void Define(int num_opers, const std::vector<TF_Operation*>& opers,

        testRule.setMatchResult(false);

        // Serialize
        ByteArrayOutputStream baos = new ByteArrayOutputStream();
        ObjectOutputStream oos = new ObjectOutputStream(baos);
        oos.writeObject(testRule);
        oos.close();

        // Deserialize
        ByteArrayInputStream bais = new ByteArrayInputStream(baos.toByteArray());
        ObjectInputStream ois = new ObjectInputStream(bais);