Comments (1)
If you check RLlib docs on the comparison of the old and new stack here, you'll see it uses gym.vector.Env
to vectorize environments. So the answer to the future support for VectorEnv is likely no.
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Related Issues (20)
- RPC issues with changing network topology
- CI test windows://python/ray/tests:test_actor_state_metrics is consistently_failing HOT 10
- [core][experimental] Remove separate asyncio path for accelerated DAGs
- Ray Serve: Fail to create Serve applications HOT 1
- [Data] Remove `InputBuffer` op from exported metrics / dashboard / Jobs page view
- CI test linux://rllib:learning_tests_multi_agent_cartpole_appo_multi_gpu is consistently_failing HOT 5
- [core] Cancelling tasks who is waiting for dependencies hangs result objects
- CI test linux://rllib:learning_tests_multi_agent_cartpole_appo_gpu is consistently_failing HOT 6
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- [Ray Data] Improve the design and of `_MapWorker`
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- CI test linux://rllib:learning_tests_multi_agent_cartpole_appo_multi_cpu is flaky
- [core][experimental] Accelerated DAG should execute work on actor's main thread
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- CI test linux://rllib:examples/offline_rl/pretrain_bc_single_agent_evaluate_as_multi_agent is flaky HOT 1
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