Add PoolVecEnv support and update imports across the codebase

[drl-test]

Implements PoolVecEnv, which is suitable for training RL algorithms with a large batch size.

Motivation and Context

For cases where large batch sizes are needed, currently SB3 provides two VecEnv:

• DummyVecEnv: fully utilize the capabilities of a multi-core system, leading to slow performance.
• SubprocVecEnv: 1. Simulating a large(e.g., 128) number of envs use too many sub-processes and may cause OOM error, 2. subprocess-related overhead (e.g., context switches or message communications) when spawning many subprocesses.

A solution should exist that both supports large batch size and use multi-core capabilities. Although the third-party solution Envpool is suitable for this, it's C++ based. This necessitates rewriting the implementation of each environment in C++, making it less flexible when environments are already implemented in Python.

Description

PoolVecEnv is implemented here which runs N envs in M workers (M is user specified and less or equal than CPU cores).

the current implementation is bucket-base, which dispatches an (approx) equal number of envs to each subprocess. Further optimization may utilize something like threadpool when Python's new non-GIL feature is stable and extensively used.

Benchmarks

Setup: Intel.E5-2697 + 128GB Mem

(FPS is the total steps of all envs per second)

• Test1: CartPole-V1
  

• Test2: HumanoidStandup-v5
  

Types of changes

• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to change)
• Documentation (update in the documentation)

Checklist

• I've read the CONTRIBUTION guide (required)
• I have updated the changelog accordingly (required).
• My change requires a change to the documentation.
• I have updated the tests accordingly (required for a bug fix or a new feature).
• I have updated the documentation accordingly.
• I have opened an associated PR on the SB3-Contrib repository (if necessary)
• I have opened an associated PR on the RL-Zoo3 repository (if necessary)
• I have reformatted the code using make format (required)
• I have checked the codestyle using make check-codestyle and make lint (required)
• I have ensured make pytest and make type both pass. (required)
• I have checked that the documentation builds using make doc (required)

Note: You can run most of the checks using make commit-checks.