pm.addPass(createQuantizeCompositeFunctionsPass(options));

  // Add an inliner pass to inline quantized StableHLO functions.
  pm.addPass(createInlinerPass());
  if (pipeline_config.unpack_quantized_types()) {
    AddStablehloQuantToIntPasses(pm);
  }
}

void AddXlaCallModuleOpDeserializationPasses(OpPassManager& pm) {
  pm.addPass(TF::CreateXlaCallModuleDeserializationPass());

      tf_executor::CreateTFExecutorIslandCoarseningPass());
  pm.addPass(TF::CreateTFFunctionalControlFlowToRegions());
  pm.addPass(mlir::createInlinerPass());
  pm.addPass(mlir::createSymbolDCEPass());
  pm.addPass(mlir::createCanonicalizerPass());
  pm.addPass(mlir::TF::CreateTFShapeInferencePass());
  pm.addPass(mlir::createCanonicalizerPass());
  pm.addPass(mlir::TF::CreateTensorListOpsDecompositionPass());

                           llvm::ArrayRef<std::string> device_specs) {
  pass_manager->addPass(mlir::TFL::tac::CreateTargetAnnotationPass(this));
  pass_manager->addPass(mlir::TFL::tac::CreateRaiseTargetSubgraphsPass());
  pass_manager->addPass(mlir::TFL::tac::CreateFoldConstantsToSubgraphPass(
      /*fold_all_constants=*/false));
  pass_manager->addPass(
      mlir::TFL::tac::CreateAlternativeSubgraphPass(device_specs));

      toco_flags.tf_quantization_mode().empty()) {
    pass_manager->addPass(mlir::TFL::CreatePrepareCompositeFunctionsPass());
  }

  pass_manager->addPass(mlir::createInlinerPass());
  pass_manager->addPass(mlir::createSymbolDCEPass());

  if (pass_config.legalize_custom_tensor_list_ops) {
    pass_manager->addPass(mlir::TFL::CreateLegalizeTensorListPass());
  }

  if (pass_config.lower_tensor_list_ops &&

      quantization_options.enable_legacy_weight_only(), mlir_dump_file_prefix));
  pm.addPass(mlir::createSymbolDCEPass());
  pm.addPass(mlir::TF::CreateTFShapeInferencePass());

  // TODO: b/264637396 - Deprecate TF opset
  if (quantization_options.op_set() != OpSet::TF) {
    pm.addPass(mlir::createInlinerPass());
    pm.addPass(mlir::TF::CreateTFShapeInferencePass());

  pm.addPass(mlir::TF::CreateTFFunctionalControlFlowToRegions());
  pm.addPass(mlir::createInlinerPass());
  pm.addPass(mlir::createSymbolDCEPass());
  pm.addPass(mlir::createCanonicalizerPass());
  // Propagates shapes on the TensorFlow graph.
  pm.addPass(mlir::TF::CreateTFShapeInferencePass(input_arg_shapes));
  pm.addPass(mlir::createCanonicalizerPass());

      /*add_passes_func=*/
      [](mlir::PassManager &pm) {
        pm.addPass(mlir::quant::CreateInsertRestoreOpPass());
        pm.addPass(mlir::quant::CreateInsertSaveOpPass());
        // Initialization by `tf.ConstOp` is no longer required as there is
        // a `tf.RestoreV2Op` now.
        pm.addPass(
            mlir::quant::CreateRemoveVariableInitializationByConstPass());
      },
      ctx, module_op);

        when:
        renderer.showDetail(true)
        renderer.addDefaultTasks(testDefaultTasks)
        renderer.startTaskGroup('group')
        renderer.addTask(task1)
        renderer.addTask(task2)
        renderer.addTask(task3)
        renderer.completeTasks()
        renderer.addRule(rule1)
        renderer.addRule(rule2)

        then:
        writer.value == '''Default tasks: task1, task2

namespace {

void AddTfDialectToExecutorPasses(OpPassManager &pm) {
  auto add_pass = [&](std::unique_ptr<Pass> pass) {
    pm.addNestedPass<FuncOp>(std::move(pass));
    pm.addPass(mlir::CreateBreakUpIslandsPass());
  };

  pm.addPass(mlir::tf_executor::CreateTFExecutorTPUV1IslandInliningPass());
  // There are cases where we don't consume all compilation and
  // replication attributes like we do for the V2 pipeline, so we need to

  pm.addPass(createPrepareQuantizePass(options));

  QuantizePassOptions quantize_options;
  quantize_options.enable_per_channel_quantized_weight_ =
      enable_per_channel_quantized_weight_;

  // QuantizePass modifies FuncOps referenced outside of its given scope
  // and therefore requires a module-level context.
  pm.addPass(createQuantizePass(quantize_options));