CreateLayoutOptimizationPipeline(pm.nest<func::FuncOp>(),
                                   layout_optimization_options);

  // Prepare IR for exporting.
  pm.addPass(CreateBreakUpIslandsPass());

  // In case of failure, the `diag_handler` converts MLIR errors emitted to the
  // MLIRContext into a tensorflow::Status.
  StatusScopedDiagnosticHandler diag_handler(module.getContext());

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

      tfr_module_, /*materialize_derived_attrs=*/true));

  // Prepare to be exported.
  func_pm.addPass(mlir::CreateFunctionalToExecutorDialectConversionPass());
  pm_.addPass(mlir::CreateBreakUpIslandsPass());
}

void TFRDecomposeContext::Destroy() { tfr_module_.erase(); }

absl::StatusOr<FunctionDef> ExpandNode(const NodeDef& node_def,
                                       StringPiece func_name) {

  pm.addPass(mlir::quant::CreateLiftHashTableOpsAsArgsPass());
  pm.addNestedPass<mlir::func::FuncOp>(
      mlir::CreateFunctionalToExecutorDialectConversionPass());
  pm.addPass(mlir::CreateBreakUpIslandsPass());
  pm.addPass(mlir::quant::CreateMergeInitializerFunctionOpsToMainPass());
  pm.addPass(mlir::quant::CreateMergeSaveFunctionOpsToMainPass());
  pm.addNestedPass<mlir::func::FuncOp>(

  manager.addPass(mlir::TF::CreateTFShapeInferencePass());
  manager.addNestedPass<mlir::func::FuncOp>(
      mlir::CreateFunctionalToExecutorDialectConversionPass());
  manager.addPass(mlir::CreateBreakUpIslandsPass());

  mlir::StatusScopedDiagnosticHandler diag_handler(module.getContext());

  if (VLOG_IS_ON(2)) {
    llvm::StringRef module_name = llvm::StringRef();
    constexpr const char* kDebugGroupBridgePhase2 =

    std::get<0>(item).replaceAllUsesWith(std::get<1>(item));
  island_op.erase();
}

}  // namespace

std::unique_ptr<OperationPass<ModuleOp>> CreateBreakUpIslandsPass() {
  return std::make_unique<BreakUpIslands>();
}

  }
  PassManager pm(func_.getContext());
  ::tensorflow::applyTensorflowAndCLOptions(pm);
  pm.addNestedPass<func::FuncOp>(
      CreateFunctionalToExecutorDialectConversionPass());
  pm.addPass(CreateBreakUpIslandsPass());

  // In case of failure, the `diag_handler` converts MLIR errors emitted to
  // the MLIRContext into a tensorflow::Status.
  StatusScopedDiagnosticHandler diag_handler(func_.getContext());

namespace mlir {

// Creates a pass that breaks up an island with multiple ops into multiple
// islands, each with a single op.
std::unique_ptr<OperationPass<ModuleOp>> CreateBreakUpIslandsPass();

// Creates a pass that converts mlir functions consisting of mlir ops into a
// tf_executor dialect as a single island.
std::unique_ptr<OperationPass<func::FuncOp>>

}

def BreakUpIslandsPass : Pass<"tf-executor-break-up-islands", "mlir::func::FuncOp"> {
  let summary = "Transform from TF control dialect to TF executor dialect.";
  let constructor = "CreateBreakUpIslandsPass()";
  let dependentDialects = ["mlir::tf_executor::TensorFlowExecutorDialect"];
}

def SplitIntoIslandPerOpPass : Pass<"tf-executor-split-into-island-per-op", "mlir::func::FuncOp"> {