// output of the initializer function for non-variable resource initialization
// will be passed on as a dependency to a new `tf.NoOp`, whose control output
// will be merged into the main function's FetchOp. The initializer functions
// will be removed.
//
// Running this pass essentially has the effect of inlining the initializer
// functions into the main graph. This is beneficial when we wish to find and

//
// This allows our def-use based island coarsening algorithm to merge
// islands that independently feed into a fetch.
void InsertDummyIslandForFetch(FetchOp fetch) {
  llvm::SmallVector<Value, 4> data_fetches;
  llvm::SmallVector<Type, 4> data_types;
  llvm::SmallVector<Value, 4> control_fetches;
  data_fetches.reserve(fetch.getFetches().size());

            TypeID::get<TF::TPUPartitionedOutputOp>(),
            TypeID::get<TF::TPUPartitionedOutputV2Op>(),
            TypeID::get<TF::TPUReplicateMetadataOp>(),
            TypeID::get<mlir::tf_executor::FetchOp>(),
            TypeID::get<TF::OutfeedEnqueueTupleOp>(),
        };
    return ops_set;
  }();
  auto abstractOp = op->getRegisteredInfo();
  if (!abstractOp) return true;

bool IsSupportedNonTFOp(Operation* op) {
  return isa<tf_device::ReturnOp, tf_device::ClusterOp, tf_device::LaunchOp,
             tf_executor::EnterOp, tf_executor::ExitOp, tf_executor::FetchOp,
             tf_executor::GraphOp, tf_executor::IslandOp,
             tf_executor::LoopCondOp, tf_executor::MergeOp,
             tf_executor::NextIterationSinkOp, tf_executor::SwitchNOp,

  // and a return operation to return the Graph results.
  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_),