}
            roundFloor = toX(roundFloorAsDouble, RoundingMode.FLOOR);
          }

          X deltaToFloor = minus(x, roundFloor);
          X deltaToCeiling = minus(roundCeiling, x);
          int diff = deltaToFloor.compareTo(deltaToCeiling);
          if (diff < 0) { // closer to floor
            return roundFloorAsDouble;
          } else if (diff > 0) { // closer to ceiling

// CHECK: %[[arg1_add:.*]] = "tf.AddV2"(%[[arg1_div]]
// CHECK: %[[arg1_floor:.*]] = "tf.Floor"(%[[arg1_add]]
// CHECK: %[[arg1_clip:.*]] = "tf.ClipByValue"(%[[arg1_floor]]
// CHECK: %[[arg1_cast:.*]] = "tf.Cast"(%[[arg1_clip]]

// CHECK: %[[arg0_div:.*]] = "tf.Div"(%arg0
// CHECK: %[[arg0_add:.*]] = "tf.AddV2"(%[[arg0_div]]
// CHECK: %[[arg0_floor:.*]] = "tf.Floor"(%[[arg0_add]]
// CHECK: %[[arg0_clip:.*]] = "tf.ClipByValue"(%[[arg0_floor]]

  }

  @Override
  @CheckForNull
  public E floor(@ParametricNullness E e) {
    return delegate().floor(e);
  }

  /**
   * A sensible definition of {@link #floor} in terms of the {@code descendingIterator} method of
   * {@link #headSet(Object, boolean)}. If you override {@link #headSet(Object, boolean)}, you may
   * wish to override {@link #floor} to forward to this implementation.
   */
  @CheckForNull

    do {
      result = randomNonNegativeBigInteger(numBits);
    } while (result.signum() == 0);
    return result;
  }

  /**
   * Generates a number in [0, 2^numBits) with an exponential distribution. The floor of the log2 of
   * the result is chosen uniformly at random in [0, numBits), and then the result is chosen in that
   * range uniformly at random. Zero is treated as having log2 == 0.
   */

  }

  @Override
  @CheckForNull
  public E floor(@ParametricNullness E e) {
    return delegate().floor(e);
  }

  /**
   * A sensible definition of {@link #floor} in terms of the {@code descendingIterator} method of
   * {@link #headSet(Object, boolean)}. If you override {@link #headSet(Object, boolean)}, you may
   * wish to override {@link #floor} to forward to this implementation.
   */
  @CheckForNull

// supports float types. tf.round with integer input type will become an
// identity op, so we will never face an mhlo.floor with an integer input type.
// The pattern matched executes the following computation:
// frac = x - floor(x)
// to_even = (floor(x) - 2 * floor(0.5 * x)) == 1
// if frac > 0.5 || (frac == 0.5 && to_even)
//   return floor(x) + 1
// else
//   return floor(x)

  const float kern_size = pool.kh * pool.kw;

  // LEMMA 1: Changing the rounding mode from floor to ceil will increase an
  // output dimension by at most 1 (see `ComputeSpatialOutDim`). This is because
  // for any `x`, `ceil(x) - floor(x) <= 1`.

  // Consider that we pad the input of a average pool with floor rounding to the
  // appropriate size and switch the rounding mode to ceil. When computing the

            panels: sanitizePanels(sanePanel.panels, std.length(sanePanel.panels)),
          }
          else sanePanel + {
            gridPos+: {
              h: panelHeight,
              w: std.floor(gridWidth/row),
            },
          }
        ),
      ps
    );
    local sanitizedPanels = sanitizePanels(panels, 0);

    local grouped = panelUtil.groupPanelsInRows(sanitizedPanels);

  @CheckForNull
  public E lower(E element) {
    return forward.higher(element);
  }

  @Override
  @CheckForNull
  public E floor(E element) {
    return forward.ceiling(element);
  }

  @Override
  @CheckForNull
  public E ceiling(E element) {
    return forward.floor(element);
  }

  @Override
  @CheckForNull
  public E higher(E element) {
    return forward.lower(element);
  }

  @CheckForNull
  public E lower(E element) {
    return forward.higher(element);
  }

  @Override
  @CheckForNull
  public E floor(E element) {
    return forward.ceiling(element);
  }

  @Override
  @CheckForNull
  public E ceiling(E element) {
    return forward.floor(element);
  }

  @Override
  @CheckForNull
  public E higher(E element) {
    return forward.lower(element);
  }