TF_EXCLUSIVE_LOCKS_REQUIRED(fn_body->mu) {
  input_tensors->reserve(ninputs);
  for (int i = 0; i < ninputs; ++i) {
    Node* node = inputs[i].oper ? &inputs[i].oper->node : nullptr;
    int idx = inputs[i].index;

    TF_RETURN_WITH_CONTEXT_IF_ERROR(
        fn_body->graph.IsValidOutputTensor(node, idx),
        "Encountered while processing input ", i, " into function '", fn_name,
        "'");

  // The first one will the function's output
  std::vector<TF_Output> outputs;

  // Add while loop to func_graph_
  {
    // The inputs to the while loop
    std::vector<TF_Output> inputs = {{feed1, 0}, {feed2, 0}};
    std::unique_ptr<TF_WhileParams> params(new TF_WhileParams(
        TF_NewWhile(func_graph_, &inputs[0], inputs.size(), s_)));

// GetSubSys - extracts subssystem info from given config string
func GetSubSys(s string) (subSys string, inputs []string, tgt string, e error) {
	tgt = Default
	if len(s) == 0 {
		return subSys, inputs, tgt, Errorf("input arguments cannot be empty")
	}
	inputs = strings.SplitN(s, KvSpaceSeparator, 2)

	subSystemValue := strings.SplitN(inputs[0], SubSystemSeparator, 2)
	subSys = subSystemValue[0]
	if !SubSystems.Contains(subSys) {

		var err error
		inputs, err = filepathx.Glob(flag.Args()[0])
		fatalErr(err)
		if len(inputs) == 0 {
			fmt.Println("Usage: No input found")
		}
	default:
		flag.Usage()
		fatalIf(true, "Only 1 file can be decrypted")
		os.Exit(1)
	}
	for _, input := range inputs {
		processFile(input, privateKeys)
	}
}

func processFile(inputFileName string, privateKeys [][]byte) {

jobs:
  cherrypick:
    name: Cherrypick to ${{ github.event.inputs.release_branch}} - ${{ github.event.inputs.git_commit }}
    runs-on: ubuntu-latest
    if: github.repository == 'tensorflow/tensorflow' # Don't do this in forks
    steps:
    - name: Checkout code
      uses: actions/checkout@1af3b93b6815bc44a9784bd300feb67ff0d1eeb3 # v6.0.0
      with:
        ref: ${{ github.event.inputs.release_branch }}

//          automatic skipping of dummy input operations is performed.
//  ninputs - number of elements in `inputs` array
//  inputs - array of TF_Outputs that specify the inputs to the function.
//           If `ninputs` is zero (the function takes no inputs), `inputs`
//           can be null. The names used for function inputs are normalized

	testCases := []struct {
		args       []string
		totalSizes []uint64
		indexes    [][]uint64
		success    bool
	}{
		// Invalid inputs.
		{
			[]string{"data{1...17}/export{1...52}"},
			[]uint64{14144},
			nil,
			false,
		},
		// Valid inputs.
		{
			[]string{"data{1...3}"},
			[]uint64{3},
			[][]uint64{{3}},
			true,
		},
		{

            TaskInputs inputs = task.getInputs();
            inputs.files(extension.getCssFiles())
                .withPropertyName("manual")
                .withPathSensitivity(PathSensitivity.RELATIVE);
            inputs.dir("src/main/resources")
                .withPropertyName("resources")
                .withPathSensitivity(PathSensitivity.RELATIVE);
            inputs.dir(extension.getUserManual().getSnippets())

void TF_AddInput(TF_OperationDescription* desc, TF_Output input) {
  desc->node_builder.Input(&input.oper->node, input.index);
}

void TF_AddInputList(TF_OperationDescription* desc, const TF_Output* inputs,
                     int num_inputs) {
  std::vector<NodeBuilder::NodeOut> input_list;
  input_list.reserve(num_inputs);
  for (int i = 0; i < num_inputs; ++i) {
    input_list.emplace_back(&inputs[i].oper->node, inputs[i].index);
  }

      TF_AddGradientsWithPrefix(graph_, prefix, outputs, noutputs, inputs,
                                ninputs, grad_inputs, s_, grad_outputs);
    } else {
      TF_AddGradientsWithPrefix(graph_, prefix, outputs, noutputs, inputs,
                                ninputs, nullptr, s_, grad_outputs);
    }
  }

  void BuildErrorGraph(TF_Output* inputs, TF_Output* outputs) {