&`ir# ddlZddlZddlZddlZddlZddlmZddlmZmZm Z m Z m Z m Z m Z mZmZmZddlZddlmZddlmZddlmZejeZedZded efd Z d'd eegefee eefgeffd ee eefde deed egeff dZGdde eZ d(de!fdZ"dZ#dZ$deee efd eee effdZ%ej&de e d e dfdZ'de(d efdZ)ded efd Z* d)d!e+d"e,d efd#Z-d e!fd$Z.d(d%e!d efd&Z/dS)*N)datetime) AnyCallableContextManagerDict GeneratorGenericListOptionalTypeVarUnion)count_required_parameters)UserExceptionWithTraceback) ObjectRefTbundlereturnc|}|dd|dd|ddd}|r||d<|S)zConvert a bundle of resources to Ray actor/task arguments. >>> bundle_to_remote_args({"GPU": 1, "memory": 1, "custom": 0.1}) {'num_cpus': 0, 'num_gpus': 1, 'memory': 1, 'resources': {'custom': 0.1}} CPUrGPUmemory)num_cpusnum_gpusr resources)copypop)rargss o/home/jaya/work/projects/VOICE-AGENT/VIET/agent-env/lib/python3.11/site-packages/ray/train/v2/_internal/util.pybundle_to_remote_argsrsi [[]]FJJua((JJua((**Xq))  D #"[ Ktrain_loop_per_worker train_funcconfigtrain_func_context fn_arg_namect}|dkr|d|d}t||dkr&pitjfd}n tjfd}|S)aValidates and constructs the training function to execute. Args: train_func: The training function to execute. This can either take in no arguments or a ``config`` dict. config (Optional[Dict]): Configurations to pass into ``train_func``. If None then an empty Dict will be created. train_func_context: Context manager for user's `train_func`, which executes backend-specific logic before and after the training function. fn_arg_name (Optional[str]): The name of training function to use for error messages. Returns: A valid training function. Raises: ValueError: if the input ``train_func`` is invalid. z: should take in 0 or 1 required arguments, but it accepts z required arguments instead.cb5cdddS#1swxYwYdSN)r#r"r$srtrain_fnz&construct_train_func..train_fnQs##%% * *!z&)) * * * * * * * * * * * * * * * * * *s $((c`5cdddS#1swxYwYdSr)r*)r"r$srr+z&construct_train_func..train_fnXs##%% $ $!z|| $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $s #'')r ValueError functoolswraps)r"r#r$r%num_required_paramserr_msgr+s``` rconstruct_train_funcr20s*4J??Q A A" A A A !!!a2  $ $ * * * * * * % $ * *  $ $ $ $ $ $ $ % $ $ Or c*eZdZdZdefdZdefdZdS)ObjectRefWrapperz>Thin wrapper around ray.put to manually control dereferencing.objc8tj||_dSr))rayput_ref)selfr5s r__init__zObjectRefWrapper.__init__csGCLL r rc4tj|jSr))r7getr9)r:s rr=zObjectRefWrapper.getfswty!!!r N)__name__ __module__ __qualname____doc__rr;r=r*r rr4r4`sPHH!A!!!!"Q""""""r r4F include_msc`d}|r|dz }tj|S)Nz%Y-%m-%d_%H-%M-%Sz.%f)rtodaystrftime)rBpatterns rdate_strrGjs5!G5 >   $ $W - --r c(tjSr))time monotonicr*r rtime_monotonicrKqs >  r cfd}|S)Nc j|_|Sr))rA)func copy_funcs rwrappedz_copy_doc..wrappedvs (  r r*)rOrPs` r _copy_docrQus# Nr object_refscTt|t}|r|n|g}|}i|rJtj|d\}}|r-t |tj|D] \}}||< |Jt t |ksJfd|D}|r|n|dS)aThis is a safe version of `ray.get` that raises an exception immediately if an input task dies, while the others are still running. TODO(ml-team, core-team): This is NOT a long-term solution, and we should not maintain this function indefinitely. This is a mitigation for a Ray Core bug, and should be removed when that is fixed. See here: https://github.com/ray-project/ray/issues/47204 Args: object_refs: A single or list of object refs to wait on. Returns: task_outputs: The outputs of the tasks. Raises: `RayTaskError`/`RayActorError`: if any of the tasks encounter a runtime error or fail due to actor/task death (ex: node failure). r') num_returnsc g|] }| Sr*r*).0tasktask_to_outputs r z ray_get_safe..sDDD~d+DDDr r) isinstancelistr7waitzipr=len)rRis_listunreadyreadyrW task_outputordered_outputsrXs @r ray_get_saferd}s,d++G!(;++{mKGN 3'q999w  3%(%?%? 3 3!k'2t$$ 3 ~  #k"2"2 2 2 2 2DDDD DDDO% =???1+==r context_managers)NNNc#Ktj5}|D]}|| dVddddS#1swxYwYdS)z Utility to invoke a list of context managers and yield sequentially. Args: context_managers: List of context managers to invoke. 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Returns: A decorator that performs this check, which raises an error if the caller is not a Ray Train worker. rprcJtjfd}|S)Ncddlm}r"|rtdjdt st djd|i|S)Nr)_in_tune_sessionz `ray.train.z` is deprecated when running in a function passed to Ray Tune. Please use the equivalent `ray.tune` API instead. See this issue for more context: https://github.com/ray-project/ray/issues/49454`z` cannot be used outside of a Ray Train training function. You are calling this API from the driver or another non-training process. These utilities are only available within a function launched by `trainer.fit()`.)%ray.tune.trainable.trainable_fn_utilsrDeprecationWarningr>rr)rkwargsrrprs r _wrapped_fnz9requires_train_worker.._wrap.._wrapped_fn s N N N N N N$ )9)9);); (F"+FFF()) "h hhh 2t&v&& &r )r.r/)rprrs` r_wrapz$requires_train_worker.._wrap s?    ' ' ' ' '   '&r )r)rrs` rrequires_train_workerrs6(x. Lr )r!)F)r)0rgr.loggingrIr{rtypingrrrrrr r r r r r7ray.train._internal.utilsr!ray.train.v2._internal.exceptionsr ray.typesr getLoggerr>rrdictrstrr2r4boolrGrKrQrdcontextmanagerrlobjectrors BaseExceptionintrrrr*r rrs                          ??????HHHHHH  8 $ $ GCLL$4*"9 --hr1uoxc3h0@!0C'DDE- T#s(^ $-'-# - b!e_ ----`"""""wqz"""......#>y$y/12#> 3S >#>#>#>#>L  >*       2 2C 2 2 2 2!(!s!!!!>-.JJJ&)JJJJJ,d$$$($$$$$$r