o `Û·i ã@s~ddlZddlmZmZmZddlmZddlmZddl m Z ddl Z ddl m Z ddlmZe e¡ZGdd „d eƒZdS) éN)ÚAnyÚDictÚOptional)ÚParallel)ÚMultiprocessingBackend)Ú PicklingPool)Ú usage_lib)ÚPoolcsœeZdZdZ   ddeedeedeeeeff‡fdd„ Z     dd ed ee d eed eedeeeeff ‡fd d„ Z ‡fdd„Z ‡Z S)Ú RayBackendz‡Ray backend uses ray, a system for scalable distributed computing. More info about Ray is available here: https://docs.ray.io. NÚ nesting_levelÚinner_max_num_threadsÚray_remote_argsc s,t d¡||_tƒjd||dœ|¤ŽdS)zT``ray_remote_args`` will be used to configure Ray Actors making up the pool.z util.joblib)r r N©)rÚrecord_library_usager ÚsuperÚ__init__)Úselfr r r Úkwargs©Ú __class__rúQ/home/ubuntu/vllm_env/lib/python3.10/site-packages/ray/util/joblib/ray_backend.pyrs þ ýzRayBackend.__init__éÚn_jobsÚparallelÚpreferÚrequirec  s¢tft_ |dkr7t ¡s+ddl}d|jvr"t d  |jd¡¡nt d¡t  ¡t tj j  ¡dƒ}|}tt|ƒj||||fd|durH|n|ji|¤Ž} | S) a§Make Ray Pool the father class of PicklingPool. PicklingPool is a father class that inherits Pool from multiprocessing.pool. The next line is a patch, which changes the inheritance of Pool to be from ray.util.multiprocessing.pool. ``ray_remote_args`` will be used to configure Ray Actors making up the pool. This will override ``ray_remote_args`` set during initialization. éÿÿÿÿrNÚ RAY_ADDRESSz)Connecting to ray cluster at address='{}'zStarting local ray clusterÚCPUr )r rÚ __bases__ÚrayÚis_initializedÚosÚenvironÚloggerÚinfoÚformatÚinitÚintÚ_privateÚstateÚcluster_resourcesrr Ú configurer ) rrrrrr Úmemmappingpool_argsr"Úray_cpusÚ eff_n_jobsrrrr,)s8 ÿÿ  üÿùø zRayBackend.configurecs4tt|ƒ |¡}|dkrttjj ¡dƒ}|}|S)Nrr)rr Úeffective_n_jobsr(r r)r*r+)rrr/r.rrrr0[s zRayBackend.effective_n_jobs)NNN)rNNNN)Ú__name__Ú __module__Ú __qualname__Ú__doc__rr(rÚstrrrrr,r0Ú __classcell__rrrrr s:üþýüúþýüûú2r )ÚloggingÚtypingrrrÚjoblibrÚjoblib._parallel_backendsrÚ joblib.poolrr Úray._common.usagerÚray.util.multiprocessing.poolr Ú getLoggerr1r$r rrrrÚs