I am new in ray and currently experimenting with it. I’ve written already some similar functions like ray has and try to migrate my framework to ray. Basically I would like to copy the same environment and run them parallel for which ray seems to be quite suitable according to the documentation. I manage to initilaize ray and also create one actor per environment. But when I start iterating over the episode and use .remote() execute one function in the environments and use ray.get() to retrieve the values Ray fully all my RAM and my linux will be dead. I tried to limit the max RAM ray can use in it’s config but it seems not to work.
So my question is after some days of reading the document and debugging if:
- anybody can give a hint why the memory is eaten away (it should be freed up after each step, but is seems ray might not free up the memory - without ray I had no issues)
- do I get something wrong with the concept of .remote()?
- how to limit ray’s max RAM usage (RAM means: not the GPU but the RAM accessible for CPU)
Also I tired to experiment with RLLib examples (copy-paste the ones that exist on Ray’s page but the example I’ve tried does not work and has an error). Can anybody recommend a working example to experiment with Ray/RLLib?