builder_.setInsertionPointToEnd(&graph_op.getBody().front());
  builder_.create<mlir::tf_executor::FetchOp>(graph_op.getLoc(),
                                              inst_to_return);
  builder_.setInsertionPointToEnd(bb);
  builder_.create<mlir::func::ReturnOp>(mlir::UnknownLoc::get(context_),
                                        graph_op.getResults());

  func.setAllArgAttrs(

  }
  return changed;
}

bool ShapeInference::InferShapeForNonTFDialectOperation(Operation* op) {
  if (auto graph_op = dyn_cast<tf_executor::GraphOp>(op)) {
    return ForceTypeForPassThroughOperands(graph_op.GetFetch(),
                                           graph_op.GetFetch().getFetches(),
                                           op->getResults());
  }

}

def ExecutorIslandCoarseningPass : Pass<"tf-executor-island-coarsening", "mlir::func::FuncOp"> {
  let summary = "Walks tf_executor::GraphOp and merges individual tf_executor::IslandOps.";
  let description = [{
    This pass performs whole graph analysis for a graph encapsulated into tf_executor::GraphOp.
    The analysis identifies all IslandOps within the graph which could be merged together.
    The goal is to merge as many islands as possible.