Created by: grygielski

In current state, MKL-DNN cache is being cleared on destruction of an Executor object. This mechanism was introduced by https://github.com/PaddlePaddle/Paddle/pull/20241 to reduce the length of hashing keys.

However, it appeared to be a problem, especially during training models with e.g. conditional_op or similar ops that create their own Executor object inside. Upon destruction of this local Executor, whole MKL-DNN cache is being cleared, thus resulting in crashes during training or slow-downs during inference.

The solution would be to somehow distinguish these 2 "types" of Executors where one is created to execute the whole program (therefore clear mkl-dnn cache on destruction) and the other is created locally in some operators (which doesn't clear mkl-dnn cache when destroyed).