o $i @s~ddlZddlmZmZmZddlmZddlmZddl m Z ddl Z ddl m Z ddlmZeeZGdd d eZdS) N)AnyDictOptional)Parallel)MultiprocessingBackend) PicklingPool) usage_lib)PoolcseZdZdZ   ddeedeedeeeefffdd Z     dd ed ee d eed eedeeeeff fd d Z fddZ Z S) RayBackendzRay backend uses ray, a system for scalable distributed computing. More info about Ray is available here: https://docs.ray.io. N nesting_levelinner_max_num_threadsray_remote_argsc s,td||_tjd||d|dS)zT``ray_remote_args`` will be used to configure Ray Actors making up the pool.z util.joblib)r r N)rrecord_library_usager super__init__)selfr r r kwargs __class__rX/home/ubuntu/veenaModal/venv/lib/python3.10/site-packages/ray/util/joblib/ray_backend.pyrs  zRayBackend.__init__n_jobsparallelpreferrequirec  stft_ |dkr7ts+ddl}d|jvr"td |jdntdt t tj j d}|}tt|j||||fd|durH|n|ji|} | S) aMake Ray Pool the father class of PicklingPool. PicklingPool is a father class that inherits Pool from multiprocessing.pool. The next line is a patch, which changes the inheritance of Pool to be from ray.util.multiprocessing.pool. ``ray_remote_args`` will be used to configure Ray Actors making up the pool. This will override ``ray_remote_args`` set during initialization. rN RAY_ADDRESSz)Connecting to ray cluster at address='{}'zStarting local ray clusterCPUr )r r __bases__rayis_initializedosenvironloggerinfoformatinitint_privatestatecluster_resourcesrr configurer ) rrrrrr memmappingpool_argsr"ray_cpus eff_n_jobsrrrr,)s8    zRayBackend.configurecs4tt||}|dkrttjjd}|}|S)Nrr)rr effective_n_jobsr(r r)r*r+)rrr/r.rrrr0[s zRayBackend.effective_n_jobs)NNN)rNNNN)__name__ __module__ __qualname____doc__rr(rstrrrrr,r0 __classcell__rrrrr s:2r )loggingtypingrrrjoblibrjoblib._parallel_backendsr joblib.poolrr ray._common.usagerray.util.multiprocessing.poolr getLoggerr1r$r rrrrs