if int64(nextpc) == int64(len(d.ldr.Data(fn))) {
				nextpc--
				if nextpc < pcsp.PC {
					continue
				}
			}

			spdelta := int64(pcsp.Value)
			if !haslr {
				// Return address has been pushed onto stack.
				spdelta += int64(d.arch.PtrSize)
			}

			if haslr && !fi.TopFrame() {
				// TODO(bryanpkc): This is imprecise. In general, the instruction

		frame.lr = 0
	} else if flag&abi.FuncFlagSPWrite != 0 && (!innermost || u.flags&(unwindPrintErrors|unwindSilentErrors) != 0) {
		// The function we are in does a write to SP that we don't know
		// how to encode in the spdelta table. Examples include context
		// switch routines like runtime.gogo but also any code that switches
		// to the g0 stack to run host C code.
		// We can't reliably unwind the SP (we might not even be on

		before int32
		i      int32
		after  int32
	}
	x.before = magic32
	x.after = magic32
	var j int32
	for delta := int32(1); delta+delta > delta; delta += delta {
		k := SwapInt32(&x.i, delta)
		if x.i != delta || k != j {
			t.Fatalf("delta=%d i=%d j=%d k=%d", delta, x.i, j, k)
		}
		j = delta
	}
	if x.before != magic32 || x.after != magic32 {

				//    if delta < 0 and x+delta cannot underflow, then x > w
				// This is useful for loops with bounds "len(slice)-K" (delta = -K)
				if delta < 0 && !underflow {
					ft.update(parent, x, w, signed, r)
				}
			} else {
				// With w,delta constants, we want to derive: x+delta > w  ⇒  x > w-delta
				//
				// We compute (using integers of the correct size):
				//    min = w - delta
				//    max = MaxInt - delta
				//

    // CHECK: [[ONE_MINUS_BETA2:%.*]] = "tf.Sub"([[ONE]], [[BETA2]])
    // CHECK: [[GRAD_SQUARE:%.*]] = "tf.Square"([[GRAD]])
    // CHECK: [[V_DELTA:%.*]] = "tf.Mul"([[ONE_MINUS_BETA2]], [[GRAD_SQUARE]])
    // CHECK: [[NEW_V:%.*]] = "tf.AddV2"([[BETA2_OLD_V]], [[V_DELTA]])
    // CHECK: [[ALPHA_NEW_M:%.*]] = "tf.Mul"([[ALPHA]], [[NEW_M]])
    // CHECK: [[SQRT_NEW_V:%.*]] = "tf.Sqrt"([[NEW_V]])

                                      TensorShape({1000}));

  // We update the weights by adding delta to them (to "simulate" a
  // ResourceApplyGradientDescent and similar things).
  Output delta = ops::Placeholder(scope.WithOpName("delta"), DT_FLOAT);

  ops::AssignAddVariableOp increment_op(
      scope.WithOpName("IncrementIteration"), iter,

				// Compute additional distance for the edge.
				// Note: delta must be at least 1 to distinguish the control
				// value use from the first user in a successor block.
				delta := int32(normalDistance)
				if len(p.Succs) == 2 {
					if p.Succs[0].b == b && p.Likely == BranchLikely ||
						p.Succs[1].b == b && p.Likely == BranchUnlikely {
						delta = likelyDistance
					}

//   %start = "tf.Const"() {value = dense<0> : tensor<i32>}
//   %limit = "tf.Const"() {value = dense<5> : tensor<i32>}
//   %delta = "tf.Const"() {value = dense<1> : tensor<i32>}
//   %updates = "tf.Range"(%start, %limit, %delta) :
//     (tensor<i32>, tensor<i32>, tensor<i32>) -> tensor<5xi32>
//   %shape = "tf.Const"() {value = dense<[5, 1]> : tensor<2xi32>}

		if newSec := notMonoTime.Unix(); newSec != sec+i && newSec+UnixToInternal != maxInt64 {
			t.Fatalf("time ext: %d overflows with positive delta, overflow threshold: %d", newSec, maxInt64)
		}
	}

	// Test it with negative delta.
	maxInt64 = -maxInt64
	notMonoTime = NotMonoNegativeTime
	for i := int64(0); i > -100; i-- {
		sec := notMonoTime.Unix()
		notMonoTime = notMonoTime.Add(Duration(i * 1e9))

    val startNanos = System.nanoTime()
    assertFailsWith<InterruptedIOException> {
      stream.takeHeaders()
    }
    val elapsedNanos = System.nanoTime() - startNanos
    awaitWatchdogIdle()
    // 200ms delta
    assertThat(TimeUnit.NANOSECONDS.toMillis(elapsedNanos).toDouble())
      .isCloseTo(500.0, 200.0)
    assertThat(connection.openStreamCount()).isEqualTo(0)

    // Verify the peer received what was expected.