this.totalCount = elemCount + totalCount(left) + totalCount(right);
    }

    private void recomputeHeight() {
      this.height = 1 + max(height(left), height(right));
    }

    private void recompute() {
      recomputeMultiset();
      recomputeHeight();
    }

    private AvlNode<E> rebalance() {
      switch (balanceFactor()) {
        case -2:

      this.totalCount = elemCount + totalCount(left) + totalCount(right);
    }

    private void recomputeHeight() {
      this.height = 1 + max(height(left), height(right));
    }

    private void recompute() {
      recomputeMultiset();
      recomputeHeight();
    }

    private AvlNode<E> rebalance() {
      switch (balanceFactor()) {
        case -2:

	return c.loadType(dtype, pos, "")
}

// loadType recursively loads the requested dtype and its dependency graph.
func (c *typeConv) loadType(dtype dwarf.Type, pos token.Pos, parent string) *Type {
	// Always recompute bad pointer typedefs, as the set of such
	// typedefs changes as we see more types.
	checkCache := true
	if dtt, ok := dtype.(*dwarf.TypedefType); ok && c.badPointerTypedef(dtt) {
		checkCache = false
	}

  //      */
  //     public abstract class CheckedRecursiveAction extends RecursiveAction {
  //         protected abstract void realCompute() throws Throwable;

  //         public final void compute() {
  //             try {
  //                 realCompute();
  //             } catch (Throwable t) {
  //                 threadUnexpectedException(t);
  //             }
  //         }
  //     }

  @MapFeature.Require({SUPPORTS_PUT, SUPPORTS_REMOVE})
  public void testCompute_absentToPresent() {
    assertEquals(
        "Map.compute(absent, functionReturningValue) should return value",
        v3(),
        getMap()
            .compute(
                k3(),
                (k, v) -> {
                  assertEquals(k3(), k);
                  assertNull(v);
                  return v3();

  @MapFeature.Require({SUPPORTS_PUT, SUPPORTS_REMOVE})
  public void testCompute_absentToPresent() {
    assertEquals(
        "Map.compute(absent, functionReturningValue) should return value",
        v3(),
        getMap()
            .compute(
                k3(),
                (k, v) -> {
                  assertEquals(k3(), k);
                  assertNull(v);
                  return v3();

  //      */
  //     public abstract class CheckedRecursiveAction extends RecursiveAction {
  //         protected abstract void realCompute() throws Throwable;

  //         public final void compute() {
  //             try {
  //                 realCompute();
  //             } catch (Throwable t) {
  //                 threadUnexpectedException(t);
  //             }
  //         }
  //     }

   * worthwhile only if the precomputed matcher is queried many thousands of times.
   *
   * <p>This method has no effect (returns {@code this}) when called in GWT: it's unclear whether a
   * precomputed matcher is faster, but it certainly consumes more memory, which doesn't seem like a
   * worthwhile tradeoff in a browser.
   */
  public CharMatcher precomputed() {
    return Platform.precomputeCharMatcher(this);

/** @author Jesse Wilson */
final class Platform {
  static CharMatcher precomputeCharMatcher(CharMatcher matcher) {
    // CharMatcher.precomputed() produces CharMatchers that are maybe a little
    // faster (and that's debatable), but definitely more memory-hungry. We're
    // choosing to turn .precomputed() into a no-op in GWT, because it doesn't
    // seem to be a worthwhile tradeoff in a browser.
    return matcher;
  }

namespace gradients {

// =============== Experimental C++ API for computing gradients ===============

// Sample gradient function:
//
// class AddGradientFunction : public GradientFunction {
//  public:
//   Status Compute(Context* ctx,
//                  absl::Span<AbstractTensorHandle* const> grad_inputs,
//                  absl::Span<AbstractTensorHandle*> grad_outputs) override {
//     grad_outputs[0] = grad_inputs[0];