return WalkResult::advance();
  });
  if (result.wasInterrupted()) signalPassFailure();
}
}  // end anonymous namespace

std::unique_ptr<OperationPass<func::FuncOp>>
CreateExecutorDialectToFunctionalConversionPass() {
  return std::make_unique<ExecutorDialectToFunctionalConversion>();
}

  // functionalization is ran before import. Ops can be lifted out of
  // tf_executor dialect islands/graphs.
  pm.addNestedPass<FuncOp>(
      mlir::CreateExecutorDialectToFunctionalConversionPass());
  // Guarantee all functions have one use, which enables more exact shape
  // inference.
  pm.addPass(mlir::TF::CreateGuaranteeAllFuncsOneUsePass());

    : tfr_module_(tfr_module), pm_(tfr_module_.getContext()) {
  mlir::OpPassManager& func_pm = pm_.nest<mlir::func::FuncOp>();

  // Prepare the imported graph.
  func_pm.addPass(mlir::CreateExecutorDialectToFunctionalConversionPass());

  // Run TFR lowering, inlining and raising to tf.
  func_pm.addPass(mlir::TFR::CreateDecomposeTFOpsPass(tfr_module_));
  func_pm.addPass(mlir::TFR::CreateRaiseToTFOpsPass(

// Creates a pass that lifts inner ops of tf_executor.island ops in
// tf_executor.graph into the same block as the tf_executor.graph.
std::unique_ptr<OperationPass<func::FuncOp>>
CreateExecutorDialectToFunctionalConversionPass();

namespace TF {
// Creates a pass that canonicalizes legacy compilation and replication
// attributes.
std::unique_ptr<OperationPass<func::FuncOp>>

      return %identity, %identity_n#0 : tensor<i32>, tensor<i32>
    }
    ```
  }];

  let constructor = "CreateExecutorDialectToFunctionalConversionPass()";
}

def ExecutorIslandCoarseningPass : Pass<"tf-executor-island-coarsening", "mlir::func::FuncOp"> {
  let summary = "Walks tf_executor::GraphOp and merges individual tf_executor::IslandOps.";

  SetCrashReproducer(pm);
  pm.addNestedPass<mlir::func::FuncOp>(
      mlir::tf_executor::CreateTFExecutorGraphPruningPass());
  pm.addNestedPass<mlir::func::FuncOp>(
      mlir::CreateExecutorDialectToFunctionalConversionPass());
  if (!include_variables_in_initializers) {
    pm.addPass(
        mlir::tf_saved_model::CreateRemoveVariablesInSessionInitializerPass());
  }
  pm.addNestedPass<mlir::func::FuncOp>(