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 $invariant_size elements are invariants between iterations.
    results: a list of futures.
    body_fn: input is [predicate_promise, arg0_future, arg0_promise, arg1_future, arg1_promise, ..., invariant_args] and has no returned results.

	ssc.enqueueStatefulSet(set)
	fakeWorker(ssc)
	selector, err := metav1.LabelSelectorAsSelector(set.Spec.Selector)
	if err != nil {
		return err
	}
	iterations := 0
	for (maxIterations < 0 || iterations < maxIterations) && set.Status.ReadyReplicas < *set.Spec.Replicas {
		iterations++
		pods, err := om.podsLister.Pods(set.Namespace).List(selector)
		if err != nil {
			return err
		}
		ord := len(pods) - 1

  OpPassManager pass_manager;
  llvm::StringRef device_type = "XLA_CPU_JIT";
  absl::string_view kInlinePass =
      "inline{default-pipeline=canonicalize "
      "inlining-threshold=4294967295 max-iterations=4 }";

  CreateConvertMlirToXlaHloPipeline(pass_manager, device_type,
                                    /*enable_op_fallback=*/true,
                                    /*custom_legalization_passes*/ {});

string BackPropFrameName(const string& forward_frame_name) {
  return strings::StrCat(forward_frame_name, "_backprop");
}

// Creates a loop that counts the number of iterations performed by the
// while loop associated with `while_ctx`. The returned output yields the
// iteration count.
Status AddForwardLoopCounter(WhileContext* while_ctx, const Scope& scope,
                             Output* count) {
  // Create while loop:
  //   i = 0

  context:
    cluster: foobar
    user: a name
current-context: default
`,
			wantErr: true,
		},
	}

	for _, tt := range tests {
		// Use a closure so defer statements trigger between loop iterations.
		err := func() error {
			tempfile, err := ioutil.TempFile("", "")
			if err != nil {
				return err
			}
			p := tempfile.Name()
			defer os.Remove(p)

  // defining the frame) and that they are executed once per loop iteration.
  //
  // TODO(skyewm): the control dep will be added to all nodes in the cond graph.
  // This is at best unnecessary, and at worst may prevent different parts of
  // different loop iterations from executing in parallel.
  Scope cond_scope =
      scope.NewSubScope("cond").WithControlDependencies(inputs[0]);

      // trait, then we don't need to chain resource ops accessing this resource
      // between iterations: Every iteration will create a new independent
      // resource. This enables more parallelism across iterations.
      if (!side_effect_analysis.IsUniqueResourceAllocationId(
              resource_and_device.first)) {

        # args, so each arg winds up back in the position where it started, but
        # possibly modified.
        #
        # NB: a `for` loop captures its iteration list before it begins, so
        # changing the positional parameters here affects neither the number of
        # iterations, nor the values presented in `arg`.
        shift                   # remove old arg
        set -- "$@" "$arg"      # push replacement arg
    done
fi

        # args, so each arg winds up back in the position where it started, but
        # possibly modified.
        #
        # NB: a `for` loop captures its iteration list before it begins, so
        # changing the positional parameters here affects neither the number of
        # iterations, nor the values presented in `arg`.
        shift                   # remove old arg
        set -- "\$@" "\$arg"      # push replacement arg
    done
fi

) -> 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: