}
}

// Borrowed from mutex_test.go
func HammerMutex(m *DRWMutex, loops int, cdone chan bool) {
	for range loops {
		m.Lock(id, source)
		m.Unlock(context.Background())
	}
	cdone <- true
}

// Borrowed from mutex_test.go
func TestMutex(t *testing.T) {
	loops := 200
	if testing.Short() {
		loops = 5
	}
	c := make(chan bool)
	m := NewDRWMutex(ds, "test")
	for range 10 {

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

   * 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}).
   *

  // TODO(user): Some Strings used in the subclasses can be added as static Strings
  // here too.
  static final String ERROR_MODIFIABLE_SET = "Set returned is unexpectedly modifiable";
  static final String ERROR_SELF_LOOP = "self-loops are not allowed";
  static final String ERROR_ADDED_SELF_LOOP = "Should not be allowed to add a self-loop edge.";

  /** Creates and returns an instance of the graph to be tested. */
  abstract Graph<Integer> createGraph();

	}

	// Not necessarily needed but it ensures to the readers
	// eyes that we prefer a sorted setCount slice for the
	// subsequent function to figure out the right common
	// divisor, it avoids loops.
	slices.Sort(setCounts)

	return setCounts
}

// getSetIndexes returns list of indexes which provides the set size
// on each index, this function also determines the final set size

  // TODO(user): Some Strings used in the subclasses can be added as static Strings
  // here too.
  static final String ERROR_MODIFIABLE_SET = "Set returned is unexpectedly modifiable";
  static final String ERROR_SELF_LOOP = "self-loops are not allowed";
  static final String ERROR_ADDED_SELF_LOOP = "Should not be allowed to add a self-loop edge.";

  /** Creates and returns an instance of the graph to be tested. */
  abstract Graph<Integer> createGraph();

   *   <li>{@code ImmutableList.of(2, "C")}
   * </ul>
   *
   * <p>The result is guaranteed to be in the "traditional", lexicographical order for Cartesian
   * products that you would get from nesting for loops:
   *
   * {@snippet :
   * for (B b0 : sets.get(0)) {
   *   for (B b1 : sets.get(1)) {
   *     ...
   *     ImmutableList<B> tuple = ImmutableList.of(b0, b1, ...);
   *     // operate on tuple

  private static final String ERROR_PARALLEL_EDGE = "connected by a different edge";
  private static final String ERROR_NEGATIVE_COUNT = "is non-negative";
  static final String ERROR_SELF_LOOP = "self-loops are not allowed";

  @Test
  public void transitiveClosure_directedGraph_addSelfLoopsAlways() {
    MutableGraph<Integer> directedGraph = GraphBuilder.directed().allowsSelfLoops(false).build();

                           TF_Status* status) {
#if defined(IS_MOBILE_PLATFORM) || defined(IS_SLIM_BUILD)
  status->status = tensorflow::errors::Unimplemented(
      "Creating while loops is not supported on mobile. File a bug at "
      "https://github.com/tensorflow/tensorflow/issues if this feature is "
      "important to you");
  return EmptyWhileParams();
#else
  if (ninputs == 0) {

        scaling with distribution strategy and custom training loops. `AUTO`
        indicates that the reduction option will be determined by the usage
        context. For almost all cases this defaults to `SUM_OVER_BATCH_SIZE`.
        When used in distribution strategy scope, outside of built-in training
        loops such as `tf.keras` `compile` and `fit`, we expect reduction value