[Bug]: ReplayBuffer cannot detect the real memory constraints in Kubernetes.

Bug

In stable_baselines3/common/buffers.py, around line 200, it uses psutil to determine available memories, which fails to detect the actually available memory.

# in the `__init__` of `ReplayBuffer`
if psutil is not None: 
    mem_available = psutil.virtual_memory().available

My server has over 700G memory but only 64 G available in my k8s container. I ran a training script, which is estimated to require 30 G memory. As a consequence, it is terminated silently. If warned earlier by StableBaslines3, other users may be spared of this potential problem.

To Reproduce

No response

Relevant log output / Error message

System Info

No response

Checklist

• My issue does not relate to a custom gym environment. (Use the custom gym env template instead)
• I have checked that there is no similar issue in the repo
• I have read the documentation
• I have provided a minimal and working example to reproduce the bug
• I've used the markdown code blocks for both code and stack traces.