TFE_Context* ctx = TFE_NewContext(opts, status);
    ASSERT_TRUE(TF_GetCode(status) == TF_OK) << TF_Message(status);
    TFE_DeleteContextOptions(opts);
    TFE_Executor* executor = TFE_NewExecutor(
        /*is_async=*/false, /*enable_streaming_enqueue=*/true,
        /*in_flight_nodes_limit=*/0);
    TFE_ContextSetExecutorForThread(ctx, executor);

    TFE_DeleteContext(ctx);

        //
        // TODO(allenl): We should have an async API that works with the
        // parallel device.
        device_(device),
        executor_(
            TFE_NewExecutor(is_async, /*enable_streaming_enqueue=*/true,
                            /*in_flight_nodes_limit=*/in_flight_nodes_limit)),
        op_(nullptr),
        thread_(tensorflow::Env::Default()->StartThread(

                                  TF_Status* status) {
  tensorflow::unwrap(op)->SetCancellationManager(
      tensorflow::unwrap(cancellation_manager));
  status->status = absl::OkStatus();
}

TFE_Executor* TFE_NewExecutor(bool is_async, bool enable_streaming_enqueue,
                              int in_flight_nodes_limit) {
  return new TFE_Executor(is_async, enable_streaming_enqueue,
                          in_flight_nodes_limit);
}

// A recommended value has not been established.
// A value of 0 removes the limit, which is the behavior of TensorFlow 2.11.
// When is_async is false, the value is ignored.
TF_CAPI_EXPORT extern TFE_Executor* TFE_NewExecutor(
    bool is_async, bool enable_streaming_enqueue, int in_flight_nodes_limit);

// Deletes the eager Executor without waiting for enqueued nodes. Please call