[Feature Request] independently configurable learning rates for actor and critic

[stheid]

🚀 Feature

independently configurable learning rates for actor and critic in AC-style algorithms

Motivation

In literature the actor is often configured to learn slower, such that the critics responses are more reliable. At least it would be nice if i could allow my hyperparameter optimizer to decide which learning rates he wants to use for actor or critic.

Pitch

https://github.com/DLR-RM/stable-baselines3/blob/65100a4b040201035487363a396b84ea721eb027/stable_baselines3/ddpg/ddpg.py#L12-L26

Additional context

https://spinningup.openai.com/en/latest/algorithms/ddpg.html#documentation-pytorch-version