o c²“iPã@sDddlZddlmZddlmZddlmZeGdd„deƒƒZdS)éN)ÚOptional)Ú OldAPIStack)Ú EnvConfigDictcs®eZdZdZ    ddedededed eed ef d d „Z      ddeedeedeedeed eed eed dfdd„Z de d dfdd„Z ‡fdd„Z ‡Z S)Ú EnvContextaKWraps env configurations to include extra rllib metadata. These attributes can be used to parameterize environments per process. For example, one might use `worker_index` to control which data file an environment reads in on initialization. RLlib auto-sets these attributes when constructing registered envs. rFNÚ env_configÚ worker_indexÚ vector_indexÚremoteÚ num_workersÚrecreated_workercCs.t ||¡||_||_||_||_||_dS)aInitializes an EnvContext instance. Args: env_config: The env's configuration defined under the "env_config" key in the Algorithm's config. worker_index: When there are multiple workers created, this uniquely identifies the worker the env is created in. 0 for local worker, >0 for remote workers. vector_index: When there are multiple envs per worker, this uniquely identifies the env index within the worker. Starts from 0. remote: Whether individual sub-environments (in a vectorized env) should be @ray.remote actors or not. num_workers: The total number of (remote) workers in the set. 0 if only a local worker exists. recreated_worker: Whether the worker that holds this env is a recreated one. This means that it replaced a previous (failed) worker when `restart_failed_env_runners=True` in the Algorithm's config. N)ÚdictÚ__init__rrr r r ©Úselfrrrr r r ©rúM/home/ubuntu/.local/lib/python3.10/site-packages/ray/rllib/env/env_context.pyr s  zEnvContext.__init__ÚreturncCslt|dur t |¡n||dur|n|j|dur|n|j|dur!|n|j|dur)|n|j|dur2|ƒS|jƒS)a]Returns a copy of this EnvContext with some attributes overridden. Args: env_config: Optional env config to use. None for not overriding the one from the source (self). worker_index: Optional worker index to use. None for not overriding the one from the source (self). vector_index: Optional vector index to use. None for not overriding the one from the source (self). remote: Optional remote setting to use. None for not overriding the one from the source (self). num_workers: Optional num_workers to use. None for not overriding the one from the source (self). recreated_worker: Optional flag, indicating, whether the worker that holds the env is a recreated one. This means that it replaced a previous (failed) worker when `restart_failed_env_runners=True` in the Algorithm's config. Returns: A new EnvContext object as a copy of self plus the provided overrides. N)rÚcopyÚdeepcopyrrr r r rrrrÚcopy_with_overrides9s úúzEnvContext.copy_with_overridesÚdefaultscCs&| ¡D] \}}||vr|||<qdS)a›Sets missing keys of self to the values given in `defaults`. If `defaults` contains keys that already exist in self, don't override the values with these defaults. Args: defaults: The key/value pairs to add to self, but only for those keys in `defaults` that don't exist yet in self. .. testcode:: :skipif: True from ray.rllib.env.env_context import EnvContext env_ctx = EnvContext({"a": 1, "b": 2}, worker_index=0) env_ctx.set_defaults({"a": -42, "c": 3}) print(env_ctx) .. testoutput:: {"a": 1, "b": 2, "c": 3} N)Úitems)rrÚkeyÚvaluerrrÚ set_defaultsas €þzEnvContext.set_defaultsc s:tƒ ¡dd…d|j›d|j›d|j›d|j›dS)Néÿÿÿÿz , worker=ú/z , vector_idx=z , remote=Ú})ÚsuperÚ__str__rr rr )r©Ú __class__rrr{sÿÿÿþÿzEnvContext.__str__)rFNF)NNNNNN)Ú__name__Ú __module__Ú __qualname__Ú__doc__rÚintÚboolrr rr rrÚ __classcell__rrr rrsT ùþýüûú ù(ùþýüûúù ø(r) rÚtypingrÚray.rllib.utils.annotationsrÚray.rllib.utils.typingrr rrrrrÚs