RayOutOfMemoryError: More than 95% of the memory is used

Ray Core
4

It looks like the memory issue is probably due to having too many Agent actors running in parallel. We’re actively working on this type of problem for v2.1 and 2.2, but for now I think the best thing to try would be to run fewer agents in parallel. There are two ways you can do this:

  1. Pass fewer num_cpus to ray.init, like ray.init(num_cpus=8), even though you have 16 vCPUs available.
  2. (suggested) Modify your actor definitions to request more CPUs. You can do this by modifying this line.