Is it ok to directly wrap the gym env in `create_single_env` in local_evaluation.py when evaluating the model in aicrowd?

[CH_do]

Thanks for your reply.
Some feature processing methods like stacking the recent k frames need to clear some historical data when the env is reset. However, in the current evaluation framework, it is hard to do this. This problem can be solved if another parameter, such as a bool variable is_first_obs indicating whether the env is reset, is allowed to be passed into agent.act.