Training process gets killed due to OOM about lightzero

[puyuan1996]

Hello,

Thank you for your attention and inquiry.

1. The steady increase in process memory is primarily due to the continuous addition of collected data into the replay buffer, causing the memory occupation of the replay buffer to rise persistently. We can make a rough estimate: 12*96*96/1024/1024/1024*1e6 ≈ 103GB. Here, 1e6 is the default capacity/size of the replay buffer.

2. You can indeed control memory usage by modifying the configuration settings.

   • Firstly, we recommend using grayscale images, which reduces memory usage by a factor of 3. Previous experiments have shown that this change will hardly affect performance negatively.
   • Secondly, you may consider reducing the size of the replay buffer. However, please note that this may slightly decrease the performance of the algorithm, and the specific impact would depend on your environment and algorithm settings.
   • Furthermore, you can consider using a more efficient data storage format, such as converting images into strings for storage. You can add "transform2string=True, gray_scale=True," to the policy field in the configuration. However, please note that this feature is currently under development, and we highly welcome your contribution.

If the above methods cannot solve the problem, you might need to consider increasing the memory capacity of your system.

Best wishes.