&`iddlmZmZddlmZmZddlmZddl m Z m Z m Z e dGddeZ e Gd d e Ze Gd d e Zd S))ABCabstractmethod)AnyDict)get_train_context) Deprecated DeveloperAPI PublicAPIstable) stabilitycveZdZdZedeeeffdZedefdZ edefdZ edZ edefdZ e defdZe defd Ze defd Ze defd Ze defd Ze defd Zee dZdS) TrainContextz(Abstract interface for training context.returnc,ddlm}t|)zB[Deprecated] User metadata dict passed to the Trainer constructor.r)!_GET_METADATA_DEPRECATION_MESSAGE)ray.train.contextrDeprecationWarning)selfrs l/home/jaya/work/projects/VOICE-AGENT/VIET/agent-env/lib/python3.11/site-packages/ray/train/v2/api/context.py get_metadatazTrainContext.get_metadatas& HGGGGG !BCCCcRddlm}t|d)z4[Deprecated] Trial name for the corresponding trial.r*_TUNE_SPECIFIC_CONTEXT_DEPRECATION_MESSAGEget_trial_namerrrformatrrs rrzTrainContext.get_trial_names; QPPPPP 6 = =>N O O   rcRddlm}t|d)z2[Deprecated] Trial id for the corresponding trial.rr get_trial_idrrs rr zTrainContext.get_trial_ids: QPPPPP 6 = =n M M   rcRddlm}t|d)z9[Deprecated] Trial resources for the corresponding trial.rrget_trial_resourcesrrs rr"z TrainContext.get_trial_resources's; QPPPPP 6 = =>S T T   rcRddlm}t|d)a[Deprecated] Log directory corresponding to the trial directory for a Tune session. This is deprecated for Ray Train and should no longer be called in Ray Train workers. If this directory is needed, please pass it into the `train_loop_config` directly. rr get_trial_dirrrs rr$zTrainContext.get_trial_dir0s: QPPPPP 6 = =o N N   rcdS)z,Experiment name for the corresponding trial.Nrs rget_experiment_namez TrainContext.get_experiment_name=s  rcdS)aGet the current world size (i.e. total number of workers) for this run. .. testcode:: import ray.train from ray.train.torch import TorchTrainer NUM_WORKERS = 2 def train_fn_per_worker(config): assert ray.train.get_context().get_world_size() == NUM_WORKERS trainer = TorchTrainer( train_fn_per_worker, scaling_config=ray.train.ScalingConfig(num_workers=NUM_WORKERS), ) trainer.fit() Nr&r's rget_world_sizezTrainContext.get_world_sizeB * rcdS)aGet the world rank of this worker. .. testcode:: import ray.train from ray.train.torch import TorchTrainer def train_fn_per_worker(config): if ray.train.get_context().get_world_rank() == 0: print("Worker 0") trainer = TorchTrainer( train_fn_per_worker, scaling_config=ray.train.ScalingConfig(num_workers=2), ) trainer.fit() Nr&r's rget_world_rankzTrainContext.get_world_rankY ( rcdS)aGet the local rank of this worker (rank of the worker on its node). .. testcode:: import ray.train from ray.train.torch import TorchTrainer def train_fn_per_worker(config): if ray.train.get_context().get_local_rank() == 0: print("Local rank 0 worker") trainer = TorchTrainer( train_fn_per_worker, scaling_config=ray.train.ScalingConfig(num_workers=2), ) trainer.fit() Nr&r's rget_local_rankzTrainContext.get_local_rankor.rcdS)a!Get the local world size of this node (i.e. number of workers on this node). Example: .. testcode:: import ray.train from ray.train.torch import TorchTrainer def train_fn_per_worker(): print(ray.train.get_context().get_local_world_size()) trainer = TorchTrainer( train_fn_per_worker, scaling_config=ray.train.ScalingConfig(num_workers=2), ) trainer.fit() Nr&r's rget_local_world_sizez!TrainContext.get_local_world_sizer+rcdS)aGet the rank of this node. Example: .. testcode:: import ray.train from ray.train.torch import TorchTrainer def train_fn_per_worker(): print(ray.train.get_context().get_node_rank()) trainer = TorchTrainer( train_fn_per_worker, scaling_config=ray.train.ScalingConfig(num_workers=1), ) trainer.fit() Nr&r's r get_node_rankzTrainContext.get_node_rankr+rcdS)aEReturns the :class:`~ray.train._internal.storage.StorageContext` storage context which gives advanced access to the filesystem and paths configured through `RunConfig`. NOTE: This is a DeveloperAPI, and the `StorageContext` interface may change without notice between minor versions. Nr&r's r get_storagezTrainContext.get_storages  rN)__name__ __module__ __qualname____doc__rrstrrrrr r"r$rr(intr*r-r0r2r4r r6r&rrrr s22Dd38nDDDZD     Z  c   Z   Z   s    Z   S   ^     ^ ,    ^ *    ^ * c   ^ , s   ^ ,  ^\   rrc`eZdZdZdefdZdefdZdefdZdefdZ defdZ defdZ d Z d S) DistributedTrainContextz4Implementation of TrainContext for distributed mode.rcBtSN)get_internal_train_contextr(r's rr(z+DistributedTrainContext.get_experiment_names)++??AAArcBtSr@)rAr*r's rr*z&DistributedTrainContext.get_world_size)++::<<r>s>>BSBBBB===============CcCCCCc eZdZdZ ddededededed ef d Zd efd Zd efd Zd efdZ d efdZ d efdZ d efdZ dZ dS)LocalTrainContextz.Implementation of TrainContext for local mode.rexperiment_name world_size world_rank local_ranklocal_world_size node_rankcZ||_||_||_||_||_||_dSr@)rLrMrNrOrPrQ)rrLrMrNrOrPrQs r__init__zLocalTrainContext.__init__s4 /$$$ 0"rrc|jSr@)rLr's rr(z%LocalTrainContext.get_experiment_names ##rc|jSr@)rMr's rr*z LocalTrainContext.get_world_size rc|jSr@)rNr's rr-z LocalTrainContext.get_world_rankrVrc|jSr@)rOr's rr0z LocalTrainContext.get_local_rankrVrc|jSr@)rPr's rr2z&LocalTrainContext.get_local_world_sizes $$rc|jSr@)rQr's rr4zLocalTrainContext.get_node_ranks ~rc td)Nz+Local storage context not yet implemented. )NotImplementedErrorr's rr6zLocalTrainContext.get_storages!"OPPPrN)rKrrrKr)r7r8r9r:r;r<rSr(r*r-r0r2r4r6r&rrrJrJs488  !#### #  #  ##### $S$$$$%c%%%%sQQQQQrrJN)abcrrtypingrr(ray.train.v2._internal.execution.contextrrAray.util.annotationsrr r rr>rJr&rrrasA########EDDDDDDDDD Xr r r r r 3r r r j:::::l:::2&Q&Q&Q&Q&Q &Q&Q&Q&Q&Qr