gmddlZddlZddlZddlmZddlmZmZmZm Z m Z ddl Z ddl m Z ddlmZddlmZmZmZmZmZmZmZmZmZgZereejereejereejereejereej ereej!ereej"e e#Z$dZ%d Z&Gd d Z'Gd d e'Z(Gdde'Z)Gdde'Z*Gdde'Z+Gdde'Z,Gdde'Z-Gdde'Z.e+e*e,e(e)e-e.dZ/ ddee e0ee'fde e0ej1ffdZ2dS)Nwraps)AnyDictListOptionalUnion) get_logger) PartialState) LoggerTypeis_aim_availableis_clearml_availableis_comet_ml_availableis_dvclive_availableis_mlflow_availableis_tensorboard_availableis_wandb_availablelistifyc<tfd}|S)a Decorator to selectively run the decorated function on the main process only based on the `main_process_only` attribute in a class. Checks at function execution rather than initialization time, not triggering the initialization of the `PartialState`. ct|ddr+t|g|Ri|S|g|Ri|S)Nmain_process_onlyF)getattrr on_main_process)selfargskwargsfunctions O/var/www/html/ai-engine/env/lib/python3.11/site-packages/accelerate/tracking.pyexecute_on_main_processz0on_main_process..execute_on_main_processLsj 4,e 4 4 3;<>>11(;;DR4RRR6RR R8D24222622 2r)rr s` rrrCs6 8__3333_3 #"r!ctS)z@Returns a list of all supported available trackers in the system)_available_trackersr!rget_available_trackersr%Vs r!cLeZdZdZdZd dZdefdZdedee fdZ d Z d S) GeneralTrackera` A base Tracker class to be used for all logging integration implementations. Each function should take in `**kwargs` that will automatically be passed in from a base dictionary provided to [`Accelerator`]. Should implement `name`, `requires_logging_directory`, and `tracker` properties such that: `name` (`str`): String representation of the tracker class name, such as "TensorBoard" `requires_logging_directory` (`bool`): Whether the logger requires a directory to store their logs. `tracker` (`object`): Should return internal tracking mechanism used by a tracker class (such as the `run` for wandb) Implementations can also include a `main_process_only` (`bool`) attribute to toggle if relevent logging, init, and other functions should occur on the main process or across all processes (by default will use `True`) TFc<|sd}t|ds|dz }t|dst|dkr|dz }|dz }dt|vrt|dkr|dz }|d z }t|dkrtd |dSdS) Nnamez`name`requires_logging_directoryrz, z`requires_logging_directory`trackerz `tracker`zThe implementation for this tracker class is missing the following required attributes. Please define them in the class definition: )hasattrlendirNotImplementedError)r_blankerrs r__init__zGeneralTracker.__init__ns C4(( x4!=>> 6s88a<<4KC55D ))s88a<<4KC{"3xx!||)  |r!valuescdS)a Logs `values` as hyperparameters for the run. Implementations should use the experiment configuration functionality of a tracking API. Args: values (Dictionary `str` to `bool`, `str`, `float` or `int`): Values to be stored as initial hyperparameters as key-value pairs. The values need to have type `bool`, `str`, `float`, `int`, or `None`. Nr$rr4s rstore_init_configurationz'GeneralTracker.store_init_configurations  r!stepc dS)a Logs `values` to the current run. Base `log` implementations of a tracking API should go in here, along with special behavior for the `step parameter. Args: values (Dictionary `str` to `str`, `float`, or `int`): Values to be logged as key-value pairs. The values need to have type `str`, `float`, or `int`. step (`int`, *optional*): The run step. If included, the log will be affiliated with this step. Nr$rr4r8rs rlogzGeneralTracker.logs  r!cdS)z Should run any finalizing functions within the tracking API. If the API should not have one, just don't overwrite that method. Nr$rs rfinishzGeneralTracker.finishs r!N)F) __name__ __module__ __qualname____doc__rr3dictr7rintr;r>r$r!rr'r'[s ,  t       $  hsm          r!r'ceZdZdZdZdZededeee j fffd Z e dZ edefd Zedded eefd Zeded eefd ZedZxZS)TensorBoardTrackera A `Tracker` class that supports `tensorboard`. Should be initialized at the start of your script. Args: run_name (`str`): The name of the experiment run logging_dir (`str`, `os.PathLike`): Location for TensorBoard logs to be stored. **kwargs (additional keyword arguments, *optional*): Additional key word arguments passed along to the `tensorboard.SummaryWriter.__init__` method. tensorboardTrun_name logging_dirc  ddlm}n#t$rddl}YnwxYwt ||_tj |||_ |j |j fi||_ td|jd|j tddS)Nr)rGz Initialized TensorBoard project z logging to aMake sure to log any initial configurations with `self.store_init_configuration` before training!) torch.utilsrGModuleNotFoundError tensorboardXsuperr3rHospathjoinrI SummaryWriterwriterloggerdebug)rrHrIrrG __class__s rr3zTensorBoardTracker.__init__s / / / / / / / /" / / / . . . . . . /   7<< X>>/k/0@KKFKK  e eeSWSceefff o     s  c|jSNrTr=s rr,zTensorBoardTracker.tracker {r!r4c||j|i|jtj}tj|jt|}t j |dttj|dd5} tj ||n3#tj j$rtdwxYw dddn #1swxYwYtddS) a Logs `values` as hyperparameters for the run. Should be run at the beginning of your experiment. Stores the hyperparameters in a yaml file for future use. Args: values (Dictionary `str` to `bool`, `str`, `float` or `int`): Values to be stored as initial hyperparameters as key-value pairs. The values need to have type `bool`, `str`, `float`, `int`, or `None`. ) metric_dictT)exist_okz hparams.ymlwz-Serialization to store hyperparameters failedNzQStored initial configuration hyperparameters to TensorBoard and hparams yaml file)rT add_hparamsflushtimerPrQrRrIstrmakedirsopenyamldump representerRepresenterErrorrUerrorrV)rr4project_run_namedir_nameoutfiles rr7z+TensorBoardTracker.store_init_configurationsX B777 9;;7<< 0#6F2G2GHH Ht,,,, "',,x77 = =   &'****#4    LMMM +                 hiiiiis*?DCD0DDDDNr8c t|}|D]\}}t|ttfr|jj||fd|i|8t|tr|jj||fd|i|dt|tr|jj ||fd|i||j t ddS)a Logs `values` to the current run. Args: values (Dictionary `str` to `str`, `float`, `int` or `dict` of `str` to `float`/`int`): Values to be logged as key-value pairs. The values need to have type `str`, `float`, `int` or `dict` of `str` to `float`/`int`. step (`int`, *optional*): The run step. If included, the log will be affiliated with this step. kwargs: Additional key word arguments passed along to either `SummaryWriter.add_scaler`, `SummaryWriter.add_text`, or `SummaryWriter.add_scalers` method based on the contents of `values`. global_stepz"Successfully logged to TensorBoardN)ritems isinstancerDfloatrT add_scalarrcadd_textrC add_scalarsrarUrVrr4r8rkvs rr;zTensorBoardTracker.logs LLNN J JDAq!c5\** J& &q!HHHHHHHAs## J$ $QFFtFvFFFFAt$$ J' '1II$I&III  9:::::r!c |D]\}}|jj||fd|i|tddS)a Logs `images` to the current run. Args: values (Dictionary `str` to `List` of `np.ndarray` or `PIL.Image`): Values to be logged as key-value pairs. The values need to have type `List` of `np.ndarray` or step (`int`, *optional*): The run step. If included, the log will be affiliated with this step. kwargs: Additional key word arguments passed along to the `SummaryWriter.add_image` method. roz)Successfully logged images to TensorBoardN)rprT add_imagesrUrVrvs r log_imageszTensorBoardTracker.log_imagessaLLNN E EDAq "DK "1a D DT DV D D D D @AAAAAr!cl|jtddS)z- Closes `TensorBoard` writer zTensorBoard writer closedN)rTcloserUrVr=s rr>zTensorBoardTracker.finish s1  011111r!rY)r?r@rArBr*r+rrcr rPPathLiker3propertyr,rCr7rrDr;r{r> __classcell__rWs@rrFrFsI   D!%    5bk9I3J      _  Xjtjjj_j.;;$;hsm;;;_;2BBXc]BBB_B 22_22222r!rFc NeZdZdZdZdZdZedeffd Z e dZ ede fdZ edde d eefd Zedde d eefd Ze dd edeedeeeded eef dZedZxZS) WandBTrackeraF A `Tracker` class that supports `wandb`. Should be initialized at the start of your script. Args: run_name (`str`): The name of the experiment run. **kwargs (additional keyword arguments, *optional*): Additional key word arguments passed along to the `wandb.init` method. wandbFrHc t||_ddl}|jdd|ji||_t d|jt ddS)NrprojectzInitialized WandB project rKr$)rOr3rHrinitrunrUrV)rrHrrrWs rr3zWandBTracker.__init__#s    5:>>dm>v>> A$-AABBB o     r!c|jSrY)rr=s rr,zWandBTracker.tracker0s xr!r4czddl}|j|dtddS)u Logs `values` as hyperparameters for the run. Should be run at the beginning of your experiment. Args: values (Dictionary `str` to `bool`, `str`, `float` or `int`): Values to be stored as initial hyperparameters as key-value pairs. The values need to have type `bool`, `str`, `float`, `int`, or `None`. rNT)allow_val_changez5Stored initial configuration hyperparameters to WandB)rconfigupdaterUrV)rr4rs rr7z%WandBTracker.store_init_configuration4sA   FT::: LMMMMMr!Nr8c d|jj|fd|i|tddS)a, Logs `values` to the current run. Args: values (Dictionary `str` to `str`, `float`, `int` or `dict` of `str` to `float`/`int`): Values to be logged as key-value pairs. The values need to have type `str`, `float`, `int` or `dict` of `str` to `float`/`int`. step (`int`, *optional*): The run step. If included, the log will be affiliated with this step. kwargs: Additional key word arguments passed along to the `wandb.log` method. r8zSuccessfully logged to WandBN)rr;rUrVr:s rr;zWandBTracker.logCs>  V11$1&111 344444r!c ddl|D]#\}}|j|fd|Difd|i|$tddS)a Logs `images` to the current run. Args: values (Dictionary `str` to `List` of `np.ndarray` or `PIL.Image`): Values to be logged as key-value pairs. The values need to have type `List` of `np.ndarray` or step (`int`, *optional*): The run step. If included, the log will be affiliated with this step. kwargs: Additional key word arguments passed along to the `wandb.log` method. rNc:g|]}|Sr$)Image).0imagers r z+WandBTracker.log_images..ds%<<<%++e,,<<rUrVr=s rr>zWandBTracker.finishs/  '(((((r!rYNNNN)r?r@rArBr*r+rrrcr3rr,rCr7rrDr;r{rrrr>rrs@rrrs D!&        _  X Nt N N N_ N55$5hsm555_5 <<zCometMLTracker.finishs/  )*****r!rY)r?r@rArBr*r+rrcr3rr,rCr7rrDr;r>rrs@rrrs   D!&        _  X Pt P P P_ P77$7hsm777_72++_+++++r!rc $eZdZdZdZdZeddedee ee j ffdZ e dZed efd Zed ed eefd Zedd ed eedeeeeffdZedZd S) AimTrackeraF A `Tracker` class that supports `aim`. Should be initialized at the start of your script. Args: run_name (`str`): The name of the experiment run. **kwargs (additional keyword arguments, *optional*): Additional key word arguments passed along to the `Run.__init__` method. aimT.rHrIc ||_ddlm}|dd|i||_|j|j_t d|jt ddS)Nr)RunrepozInitialized Aim project rKr$)rHrrrTr*rUrV)rrHrIrrs rr3zAimTracker.__init__s  c55{5f55 =  ? ??@@@ o     r!c|jSrYrZr=s rr,zAimTracker.trackerr[r!r4c||jd<dS) Logs `values` as hyperparameters for the run. Should be run at the beginning of your experiment. Args: values (`dict`): Values to be stored as initial hyperparameters as key-value pairs. hparamsNrZr6s rr7z#AimTracker.store_init_configurations"( Ir!r8c f|D]\}}|jj|f||d|dS)a} Logs `values` to the current run. Args: values (`dict`): Values to be logged as key-value pairs. step (`int`, *optional*): The run step. If included, the log will be affiliated with this step. kwargs: Additional key word arguments passed along to the `Run.track` method. r*r8N)rprTtrack)rr4r8rkeyvalues rr;zAimTracker.log sT!,,.. D DJC DK e C#D C CF C C C C D Dr!Nrc0ddl}i}i}|,|di}|di}|D]J\}}t|tr|\} } n|d} } |j| fd| i|} |jj| f||d|KdS)a Logs `images` to the current run. Args: values (`Dict[str, Union[np.ndarray, PIL.Image, Tuple[np.ndarray, str], Tuple[PIL.Image, str]]]`): Values to be logged as key-value pairs. The values need to have type `np.ndarray` or PIL.Image. If a tuple is provided, the first element should be the image and the second element should be the caption. step (`int`, *optional*): The run step. If included, the log will be affiliated with this step. kwargs (`Dict[str, dict]`): Additional key word arguments passed along to the `Run.Image` and `Run.track` method specified by the keys `aim_image` and `track`, respectively. rN aim_imagerr)captionr)rgetrprqtuplerrTr) rr4r8rr aim_image_kwtrack_kwrrimgrrs rr{zAimTracker.log_imagess     !::k266Lzz'2..H ,,.. J JJC%'' )$ WW$bW! #GGwG,GGI DK i Ic I I I I I I  J Jr!c8|jdS)z% Closes `aim` writer N)rTr}r=s rr>zAimTracker.finish;s r!)rNN)r?r@rArBr*r+rrcrr rPr~r3rr,rCr7rDr;rr{r>r$r!rrrsZ D!%     8E#r{BR_r!rcTeZdZdZdZdZe ddedee ee j fdeedee e ee fefd eed eed eefd Zed ZedefdZededeefdZedZdS) MLflowTrackeru A `Tracker` class that supports `mlflow`. Should be initialized at the start of your script. Args: experiment_name (`str`, *optional*): Name of the experiment. Environment variable MLFLOW_EXPERIMENT_NAME has priority over this argument. logging_dir (`str` or `os.PathLike`, defaults to `"."`): Location for mlflow logs to be stored. run_id (`str`, *optional*): If specified, get the run with the specified UUID and log parameters and metrics under that run. The run’s end time is unset and its status is set to running, but the run’s other attributes (source_version, source_type, etc.) are not changed. Environment variable MLFLOW_RUN_ID has priority over this argument. tags (`Dict[str, str]`, *optional*): An optional `dict` of `str` keys and values, or a `str` dump from a `dict`, to set as tags on the run. If a run is being resumed, these tags are set on the resumed run. If a new run is being created, these tags are set on the new run. Environment variable MLFLOW_TAGS has priority over this argument. nested_run (`bool`, *optional*, defaults to `False`): Controls whether run is nested in parent run. True creates a nested run. Environment variable MLFLOW_NESTED_RUN has priority over this argument. run_name (`str`, *optional*): Name of new run (stored as a mlflow.runName tag). Used only when `run_id` is unspecified. description (`str`, *optional*): An optional string that populates the description box of the run. If a run is being resumed, the description is set on the resumed run. If a new run is being created, the description is set on the new run. mlflowFNexperiment_namerIrun_idtags nested_runrH descriptionctjd|}tjd|}tjd|}t|trt j|}tjd|}ddl}|d|d} t| dkr;t| d krt d | dj } n| ||| } ||| |||| |_td |tddS)NMLFLOW_EXPERIMENT_NAME MLFLOW_RUN_ID MLFLOW_TAGSMLFLOW_NESTED_RUNrzname = '') filter_stringr z?Multiple experiments with the same name found. Using first one.)r*artifact_locationr)r experiment_idrHnestedrrzInitialized mlflow experiment rK)rPenvironrrqrcjsonloadsrsearch_experimentsr.rUwarningrcreate_experiment start_run active_runrV) rrrIrrrrHrrexpsrs rr3zMLflowTracker.__init__bsx*..)A?SS88z~~mT22 dC  $:d##DZ^^$7DD  ((7T/7T7T7T(UU t99q==4yy1}}`aaa G1MM"44$"-5M !**'# +    GoGGHHH o     r!c|jSrY)rr=s rr,zMLflowTracker.trackers r!r4c tddl}t|D]j\}}tt ||jjjkr6t d|d|d|jjjd||=kt|}tdt||jjj D]>}| t||||jjj z?tddS)rrNz,Accelerate is attempting to log a value of "z " for key "zJ" as a parameter. MLflow's log_param() only accepts values no longer than z) characters so we dropped this attribute.z6Stored initial configuration hyperparameters to MLflow)rlistrpr.rcutils validationMAX_PARAM_VAL_LENGTHrU warning_oncerangeMAX_PARAMS_TAGS_PER_BATCH log_paramsrCrV)rr4rr*r values_listis rr7z&MLflowTracker.store_init_configurationsD   // ! !KD%3u::!8!MMM##_5__UY__GM|G^Gs___4L6<<>>** q#k**FL,C,]^^ l lA   d;q1v|7N7h3h/h#ijj k k k k MNNNNNr!r8c Ni}|D]X\}}t|ttfr|||<'td|dt |d|dYddl}|||t ddS) a Logs `values` to the current run. Args: values (`dict`): Values to be logged as key-value pairs. step (`int`, *optional*): The run step. If included, the log will be affiliated with this step. z/MLflowTracker is attempting to log a value of " " of type for key "zc" as a metric. MLflow's log_metric() only accepts float and int types so we dropped this attribute.rN)r8zSuccessfully logged to mlflow) rprqrDrrrUrtyperrrV)rr4r8metricsrwrxrs rr;zMLflowTracker.logsLLNN  DAq!c5\**  ##kakkSWXYSZSZkkfgkkk  7... 455555r!c6ddl}|dS)z, End the active MLflow run. rN)rend_run)rrs rr>zMLflowTracker.finishs#  r!)NNNNFNN)r?r@rArBr*r+rrcrr rPr~rrboolr3rr,rCr7rDr;r>r$r!rrrCsv6 D!& $9= $59%*"&%), , , eC$456,  , uT#s(^S012 , TN , 3-, c], , , _, \XOtOOO_O66$6hsm666_60_r!rc xeZdZdZdZdZeddefdZe dZ ede fd Z edde eeeeffd eefd Zedde d eefd Ze dd edeedeeeded eef dZedZedZdS)ClearMLTrackera A `Tracker` class that supports `clearml`. Should be initialized at the start of your script. Args: run_name (`str`, *optional*): Name of the experiment. Environment variables `CLEARML_PROJECT` and `CLEARML_TASK` have priority over this argument. **kwargs (additional keyword arguments, *optional*): Kwargs passed along to the `Task.__init__` method. clearmlFNrHc `ddlm}|}d|_|rd|_||_dS|dt jd||dt jd||j d i||_dS) Nr)TaskFTrCLEARML_PROJECT task_name CLEARML_TASKr$) rr current_task_initialized_externallytask setdefaultrPrrr)rrHrrrs rr3zClearMLTracker.__init__s      ((** ',$  +/D ($DI F."*..9JH*U*UVVV+rz~~nh'O'OPPPDI'''' r!c|jSrY)rr=s rr,zClearMLTracker.tracker yr!r4c6|j|S)z Connect configuration dictionary to the Task object. Should be run at the beginning of your experiment. Args: values (`dict`): Values to be stored as initial hyperparameters as key-value pairs. )rconnect_configurationr6s rr7z'ClearMLTracker.store_init_configurationsy..v666r!r8c |j}|D]\}}t|tt fs2t d|dt|d|dS||j d||d|ft |\}}|j d||||d|dS) a Logs `values` dictionary to the current run. The dictionary keys must be strings. The dictionary values must be ints or floats Args: values (`Dict[str, Union[int, float]]`): Values to be logged as key-value pairs. If the key starts with 'eval_'/'test_'/'train_', the value will be reported under the 'eval'/'test'/'train' series and the respective prefix will be removed. Otherwise, the value will be reported under the 'train' series, and no prefix will be removed. step (`int`, *optional*): If specified, the values will be reported as scalars, with the iteration number equal to `step`. Otherwise they will be reported as single values. kwargs: Additional key word arguments passed along to the `clearml.Logger.report_single_value` or `clearml.Logger.report_scalar` methods. z-Accelerator is attempting to log a value of "rrzn" as a scalar. This invocation of ClearML logger's report_scalar() is incorrect so we dropped this attribute.N)r*r)titleseriesr iterationr$) rr rprqrDrrrUrrreport_single_valuer_get_title_series report_scalar rr4r8rclearml_loggerrwrxr r s rr;zClearMLTracker.logs$--//LLNN h hDAqa#u.. ##AAA%)!WWAA89AAA |22MMMfMMM*<zClearMLTracker.finish[sD 9 T9  IOO         r!cdD]8}||dzr|t|dzd|fcS9|dfS)N)evaltesttrain_r r) startswithr.)r*prefixs rr z ClearMLTracker._get_title_seriesds^/ 7 7Fv|,, 7CKK!O--.6666 7W}r!rYr)r?r@rArBr*r+rrcr3rr,rCr7rr rDrrrr;r{rrrr> staticmethodr r$r!rrrs   D!& ( ( ( ( (_ (X7t777_7hh$sE#u*$556hhsmhhh_hBgggXc]ggg_g"" $" #x#x#xc#x49o #x  #x sm #x#x#x_#xJ_\r!rceZdZdZdZdZeddeedee ffd Z e dZ ed e fd Zedd e d eefd Zed ZxZS)DVCLiveTrackera5 A `Tracker` class that supports `dvclive`. Should be initialized at the start of your script. Args: run_name (`str`, *optional*): Ignored for dvclive. See `kwargs` instead. kwargs: Additional key word arguments passed along to [`dvclive.Live()`](https://dvc.org/doc/dvclive/live). Example: ```py from accelerate import Accelerator accelerator = Accelerator(log_with="dvclive") accelerator.init_trackers(project_name="my_project", init_kwargs={"dvclive": {"dir": "my_directory"}}) ``` dvcliveFNrHlivec vddlm}t||n|di||_dS)Nr)Liver$)r#r&rOr3r$)rrHr$rr&rWs rr3zDVCLiveTracker.__init__sK        ,DD$$.... r!c|jSrY)r$r=s rr,zDVCLiveTracker.trackerrr!r4c:|j|dS)a Logs `values` as hyperparameters for the run. Should be run at the beginning of your experiment. Stores the hyperparameters in a yaml file for future use. Args: values (Dictionary `str` to `bool`, `str`, `float`, `int`, or a List or Dict of those types): Values to be stored as initial hyperparameters as key-value pairs. The values need to have type `bool`, `str`, `float`, or `int`. N)r$rr6s rr7z'DVCLiveTracker.store_init_configurations  V$$$$$r!r8c Jddlm}| ||j_|D]`\}}||r|jj||fi|/td|dt|d|da|j dS)a Logs `values` to the current run. Args: values (Dictionary `str` to `str`, `float`, or `int`): Values to be logged as key-value pairs. The values need to have type `str`, `float`, or `int`. step (`int`, *optional*): The run step. If included, the log will be affiliated with this step. kwargs: Additional key word arguments passed along to `dvclive.Live.log_metric()`. r)MetricNz)Accelerator attempted to log a value of "rrzh" as a scalar. This invocation of DVCLive's Live.log_metric() is incorrect so we dropped this attribute.) dvclive.plotsr*r$r8rp could_logrrUrr next_step)rr4r8rr*rwrxs rr;zDVCLiveTracker.logs )(((((  !DINLLNN  DAq"" $ $Q44V4444##AAA%)!WWAA89AAA r!c8|jdS)z* Closes `dvclive.Live()`. N)r$rr=s rr>zDVCLiveTracker.finishs r!rrY)r?r@rArBr*r+rrrcrr3rr,rCr7rDr;r>rrs@rr"r"ls& D!&AA#AXc]AAAAA_A X %t % % %_ %$hsm_8_r!r")rrrrGrrr#log_withrIcg}|kt|ttfs|g}d|vstj|vrd|Dt z}n|D]}|tvrHt t|ts&td|dtjt t|tr| |t|}||vrz|t vrLtt|}|j r|td|d| |td|d |S) a9 Takes in a list of potential tracker types and checks that: - The tracker wanted is available in that environment - Filters out repeats of tracker types - If `all` is in `log_with`, will return all trackers in the environment - If a tracker requires a `logging_dir`, ensures that `logging_dir` is not `None` Args: log_with (list of `str`, [`~utils.LoggerType`] or [`~tracking.GeneralTracker`], *optional*): A list of loggers to be setup for experiment tracking. Should be one or several of: - `"all"` - `"tensorboard"` - `"wandb"` - `"comet_ml"` - `"mlflow"` - `"dvclive"` If `"all"` is selected, will pick up all available trackers in the environment and initialize them. Can also accept implementations of `GeneralTracker` for custom trackers, and can be combined with `"all"`. logging_dir (`str`, `os.PathLike`, *optional*): A path to a directory for storing logs of locally-compatible loggers. NallcVg|]&}tt|t$|'Sr$) issubclassrr')ros rrz#filter_trackers..s-RRRQja..Q.QRqRRRr!z Unsupported logging capability: z. Choose between zLogging with `z+` requires a `logging_dir` to be passed in.zTried adding logger z+, but package is unavailable in the system.)rqrrr ALLr%r3rr'rappendLOGGER_TYPE_TO_CLASSrcr+rUrV)r/rIloggerslog_type tracker_inits rfilter_trackersr;s4G(T5M22 " zH H   ( : :RR(RRRUkUmUmmGG$ w w:--jhQ_6`6`-$%v%v%vcmcrctct%v%vwwwd8nnn==wNN8,,,,)(33Hw..#'='?'???+?H +NL+F&#.#6*4(n(n(n(n+&+&%&$NN84444"LL)u)u)u)uvvv Nr!rY)3rrPrb functoolsrtypingrrrrr rfloggingr stater rr rrrrrrrrr#r6 TENSORBOARDWANDBCOMETMLAIMMLFLOWCLEARMLDVCLIVEr?rUrr%r'rFrrrrrr"r7rcr~r;r$r!rrGsT$ 33333333333333                       7z56661z/0003z1222/z~...2z01113z12223z1222 H  ###& G G G G G G G G Tl2l2l2l2l2l2l2l2^x)x)x)x)x)>x)x)x)vN+N+N+N+N+^N+N+N+b````````FNNNNNNNNNbUUUUU^UUUpQQQQQ^QQQj % ,0445j.89:4sBK'(444444r!