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How to evaluate actors trained in custom environments in rllib (Ray)?
How to draw pixels for ray-tracing in C++?LWJGL - How to trace a ray effectively and efficiently?How to do a Ray/Direction 2D system?How large data can Python Ray handle?Ray: How to run many actors on one GPU?How to do the inference on carla after training on Ray cluster?How to make an actor do two things simultaneously?How to set up ray project autoscaling on GCPHow can I use the python logging in Ray?Should I set `inter_op_parallelism_threads` and `intra_op_parallelism_threads` to 1 when I use ray to create a actor?
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Following the SimpleCorridor example I can create my own env and train a model! nice. But when I try to evaluate this trained model, rllib does not recognize my custom env.
How can I evaluate a trained model on a custom environment?
When I use rllib rollout ... like its suggested here it does not recognize my env because it's custom one. I was hoping to have a function like run_experiments but like evaluate_experiment so I can call it on my project inside one of my files.
Thats the issue.
If you want to see my custon_env is this one
Right now I'm having to copy my environment and paste it inside the gym/envs/ package directory and register it in the __init__.py file.
Would be good to see another way to do this
Thanks
ray
asked Mar 26 at 13:05
Lucas DraichiLucas Draichi
14 bronze badges
add a comment |
Following the SimpleCorridor example I can create my own env and train a model! nice. But when I try to evaluate this trained model, rllib does not recognize my custom env.
How can I evaluate a trained model on a custom environment?
When I use rllib rollout ... like its suggested here it does not recognize my env because it's custom one. I was hoping to have a function like run_experiments but like evaluate_experiment so I can call it on my project inside one of my files.
Thats the issue.
If you want to see my custon_env is this one
Right now I'm having to copy my environment and paste it inside the gym/envs/ package directory and register it in the __init__.py file.
Would be good to see another way to do this
Thanks
ray
asked Mar 26 at 13:05
Lucas DraichiLucas Draichi
14 bronze badges
add a comment |
Following the SimpleCorridor example I can create my own env and train a model! nice. But when I try to evaluate this trained model, rllib does not recognize my custom env.
How can I evaluate a trained model on a custom environment?
When I use rllib rollout ... like its suggested here it does not recognize my env because it's custom one. I was hoping to have a function like run_experiments but like evaluate_experiment so I can call it on my project inside one of my files.
Thats the issue.
If you want to see my custon_env is this one
Right now I'm having to copy my environment and paste it inside the gym/envs/ package directory and register it in the __init__.py file.
Would be good to see another way to do this
Thanks
ray
asked Mar 26 at 13:05
Lucas DraichiLucas Draichi
14 bronze badges
Following the SimpleCorridor example I can create my own env and train a model! nice. But when I try to evaluate this trained model, rllib does not recognize my custom env.
How can I evaluate a trained model on a custom environment?
When I use rllib rollout ... like its suggested here it does not recognize my env because it's custom one. I was hoping to have a function like run_experiments but like evaluate_experiment so I can call it on my project inside one of my files.
Thats the issue.
If you want to see my custon_env is this one
Right now I'm having to copy my environment and paste it inside the gym/envs/ package directory and register it in the __init__.py file.
Would be good to see another way to do this
Thanks
ray
ray
asked Mar 26 at 13:05
Lucas DraichiLucas Draichi
14 bronze badges
asked Mar 26 at 13:05
Lucas DraichiLucas Draichi
14 bronze badges
asked Mar 26 at 13:05
Lucas DraichiLucas Draichi
14 bronze badges
asked Mar 26 at 13:05
Lucas DraichiLucas Draichi
14 bronze badges
asked Mar 26 at 13:05
Lucas DraichiLucas Draichi
14 bronze badges
14 bronze badges
add a comment |
add a comment |
1 Answer
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You can copy the rollout.py script and modify it to register any custom envs or models in the start of the script. That will allow it to work with any envs not on gym already.
answered Mar 26 at 21:43
EricEric
16
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You can copy the rollout.py script and modify it to register any custom envs or models in the start of the script. That will allow it to work with any envs not on gym already.
answered Mar 26 at 21:43
EricEric
16
add a comment |
You can copy the rollout.py script and modify it to register any custom envs or models in the start of the script. That will allow it to work with any envs not on gym already.
answered Mar 26 at 21:43
EricEric
16
add a comment |
You can copy the rollout.py script and modify it to register any custom envs or models in the start of the script. That will allow it to work with any envs not on gym already.
answered Mar 26 at 21:43
EricEric
16
You can copy the rollout.py script and modify it to register any custom envs or models in the start of the script. That will allow it to work with any envs not on gym already.
answered Mar 26 at 21:43
EricEric
16
answered Mar 26 at 21:43
EricEric
16
answered Mar 26 at 21:43
EricEric
16
answered Mar 26 at 21:43
EricEric
16
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