type PB struct {
	globalN *atomic.Uint64 // shared between all worker goroutines iteration counter
	grain   uint64         // acquire that many iterations from globalN at once
	cache   uint64         // local cache of acquired iterations
	bN      uint64         // total number of iterations to execute (b.N)
}

// Next reports whether there are more iterations to execute.
func (pb *PB) Next() bool {
	if pb.cache == 0 {

        root {
            'common.gradle'('println "poke"')
        }

        when:
        def allCompileOperations = 0
        def iterations = 3
        def builder = root
        iterations.times { n ->
            createJarWithProperties("foo${n}.jar", [value: n])
            new File(root.baseDir, 'build.gradle').delete()
            builder {
                'build.gradle'("""

	seenSources := sets.New[string](TestSource)
	var wg sync.WaitGroup
	const iterations = 100
	wg.Add(2)

	go func() {
		ctx, cancel := context.WithCancel(tCtx)
		defer cancel()
		defer wg.Done()
		for i := 0; i < iterations; i++ {
			config.Channel(ctx, strconv.Itoa(i))
		}
	}()
	go func() {
		defer wg.Done()
		for i := 0; i < iterations; i++ {
			config.SeenAllSources(seenSources)
		}
	}()

) -> rd.RepresentativeDataset:
  """Logs the sample number for calibration.

  If in debug logging level, the "sample number / total num samples" is logged
  for every 5 iterations.

  This is often useful when tracking the progress of the calibration step which
  is often slow and may look stale if there's no logs being printed.

  Args:

			c = 0
			ng = nng
		}
		if c >= 100 {
			// The same value 100 times in a row is good enough.
			return ng
		}
		runtime.Gosched()
	}
	panic("failed to stabilize NumGoroutine after 1000 iterations")
}

func TestPullDoubleNext(t *testing.T) {
	next, _ := Pull(doDoubleNext())
	nextSlot = next
	next()
	if nextSlot != nil {
		t.Fatal("double next did not fail")
	}
}

	MOVD y+48(FP), R4	// R4 = y = c
	MOVD z_len+8(FP), R11	// R11 = z_len

	CMP   R11, $0		// If z_len is zero, return
	BEQ   done

	// We will process the first iteration out of the loop so we capture
	// the value of c. In the subsequent iterations, we will rely on the
	// value of CA set here.
	MOVD  0(R8), R20	// R20 = x[i]
	ADD   $-1, R11		// R11 = z_len - 1
	ADDC  R20, R4, R6	// R6 = x[i] + c

	}

	tries++ // tried already once

	// Wait on each try for an update.
	ticker := time.NewTicker(1 * time.Second)
	defer ticker.Stop()

	for {
		// Only log once every 10 iterations, then reset the tries count.
		verbose = tries >= 10
		if verbose {
			tries = 1
		}

  let summary = "Asynchronously execution of while op for tf_mlrt";
  let description = [{
    cond: The boolean to control whether the first iteration should be executed.
    arguments: the last $immutable_size elements are invariants between iterations.
    results: a list of futures.

// RUN: tf-tfrt-opt -tf-to-tfrt="enable-while-parallel-iterations=true" %s | FileCheck %s --dump-input=fail

// CHECK-LABEL: func @cond_false(%arg0: !tfrt.chain, %arg1: !tfrt_fallback.tf_tensor) -> (!tfrt.chain, !tfrt_fallback.tf_tensor)
func.func @cond_false(%arg0: tensor<i32>) -> tensor<i32> {
  %0 = "tf.Const"() {device = "/device:CPU:0", value = dense<-1> : tensor<i32>} : () -> tensor<i32>

func MergePackageFiles(pkg *Package, mode MergeMode) *File {
	// Count the number of package docs, comments and declarations across
	// all package files. Also, compute sorted list of filenames, so that
	// subsequent iterations can always iterate in the same order.
	ndocs := 0
	ncomments := 0
	ndecls := 0
	filenames := make([]string, len(pkg.Files))
	var minPos, maxPos token.Pos
	i := 0
	for filename, f := range pkg.Files {