google-deepmind / google-deepmind/lab2d
Request: Support for vectorised environments #253
Open
- Dominant language
- C++
- Stars
- 442
- Forks
- 58
- PR merge metrics
- No merged PRs in 30d
Description
Hi All
Is it possible to run DMLab2d with vectorised environments? I am using CleanRL + Shimmy to run MeltingPot but when I try to use `concat_vec_envs_v1` I get error: `TypeError: cannot pickle dmlab2d.dmlab2d_pybind.Lab2d object`. Is there any other way? I need to train faster as I have limited compute walltime and the easiest way is vectorised environments. Any other methods for optimisation?
Contributor guide
Assessment
This issue has not been assessed yet.