}

  auto compile_op = builder->create<TF::_TPUCompileMlirOp>(
      cluster_func.getLoc(),
      /*compilation_status=*/compilation_status_type, /*program=*/
      llvm::SmallVector<Type, 8>(num_cores_per_replica, program_type),
      compile_op_operands, txt_module, txt_metadata);

  return tensorflow::WrapOpInLaunch(builder, compile_op.getLoc(), compile_op,

  Operation* tpu_compile_successor = nullptr;
  func_op->walk([&](TF::_TPUCompileMlirOp compile_op) {
    if (compile_op->getParentOp() == nullptr ||
        !isa<tf_device::LaunchOp>(compile_op->getParentOp()))
      return WalkResult::advance();
    Operation* compile_launch_op = compile_op->getParentOp();

    if (compile_launch_op->getBlock() == preprocess_or_launch->getBlock() &&

  TF_SavedModel* saved_model =
      TF_LoadSavedModel(model_dir.c_str(), ctx, status);

  EXPECT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);
  TF_ConcreteFunction* compute_fn =
      TF_GetSavedModelConcreteFunction(saved_model, "compute", status);
  EXPECT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);

  std::vector<TFE_TensorHandle*> compute_fn_inputs;