FiP ddlmZddlZddlmZmZmZmZddl m Z m Z m Z m Z mZmZdddddgd d d d d d ZddZdZdZdZdZdZdZdZdZdZ d ddZy)) annotationsN) TASK2DATA TASK2METRICget_cfg get_save_dir) DEFAULT_CFGDEFAULT_CFG_DICTLOGGER NUM_THREADScheckscolorstrz ax-platformzbayesian-optimization==1.4.3 hpbandster ConfigSpacez HEBO>=0.2.0hyperopt nevergradoptunazoopt) randomaxbayesoptbohbheborrrrct|tr-|jDcic]\}}|t|c}}St|tr|Dcgc] }t|c}St|t rt d|DSt|t jr|jSt|t jr|jS|Scc}}wcc}w)a#Convert NumPy-backed Tune values into native Python types for YAML serialization. Args: value (dict): The value to convert. Can be a dict, list, tuple, NumPy scalar, or NumPy array. Returns: The converted value with NumPy types replaced by native Python types. c32K|]}t|ywN)_sanitize_tune_value).0vs Y/var/www/pod-logistic/pod-ai/venv/lib/python3.12/site-packages/ultralytics/utils/tuner.py z'_sanitize_tune_value..%s<)!,<) isinstancedictitemsrlisttuplenpgenericitemndarraytolist)valuekrs rrrs%7<{{}Etq!'**EE%167A$Q'77%-s*c"%%'--/ !T!   C>>3<.s,!s1v,r!zWTuneBOHB does not support quantized search spaces with the current ConfigSpace version.)r4upperlog)choicesz-TuneBOHB does not support parameters of type z with sampler type .c32K|]}t|ywrrcrds rr z-_convert_bohb_search_space..!7Q#a&!7r!)r rBrCrray.tune.search.samplerUrVrWrXrYrZ!ray.tune.search.variant_generatorr\ray.tune.utilsr^ ValueErrorConfigurationSpacejoin get_samplerr"addUniformFloatHyperparameterr4rfUniformIntegerHyperparameterCategoricalHyperparameter categoriestyper7sampler)rFrrUrVrWrXrYrZr\r^resolved_space resolved_vars domain_vars grid_varscspathdomainparrzrfr,fixed_param_spaces r_convert_bohb_search_spacervs 9&ABbbA+!%4@N,;N,K)M; opp  ' ' )B# fhh,t,,$$& gy )vw w fe $Ggz=R)S FF66v||6<]9   ,GW1M FF;88fFWFW8X Y?V @U@U?VW%%)&..%9%B%B$C1F -6S``;4!7$!77>``   as#H0cRt|\}}ddlm}||t|d|fS)aCreate a BOHB searcher using a ConfigSpace definition compatible with current ConfigSpace versions. Args: space (dict): The hyperparameter search space. task (str): The task type (e.g., 'detect', 'segment', 'classify'). Returns: (tuple): A tuple containing the TuneBOHB searcher and fixed parameter space dict. Raises: ImportError: If required BOHB packages are not installed. r)r0max)rFmetricmode)r ray.tune.search.bohb.bohb_searchr0r)rFrRrrr0s r_create_bohb_searchrs17u=B9 "[%6U CEV VVr?ctjtdddl}ddlm}||j jt|dS)a3Create a Nevergrad searcher with a default optimizer. Args: task (str): The task type (e.g., 'detect', 'segment', 'classify'). Returns: (NevergradSearch): The configured Nevergrad search algorithm. Raises: ImportError: If the 'nevergrad' package is not installed. rrN)NevergradSearchr) optimizerrr) r rBrCrray.tune.search.nevergradr optimizers OnePlusOner)rRngrs r_create_nevergrad_searchrs> 9+FG9 R]]%=%=kRVFW^c ddr?ctjtdddlm}ddlm}ddlm}||d}||\}}}|Dcic]\}}djd |D| } }}|j|} | | fScc}}w) aZConvert a Tune search space into ZOOpt-compatible dimensions and fixed-only Tune param_space. Args: space (dict): The hyperparameter search space. Returns: (tuple): A tuple containing the ZOOpt dimension dict and fixed parameter space dict. Raises: ImportError: If the 'zoopt' package is not installed. rrr[r1r]Tr_rac32K|]}t|ywrrcrds rr z._convert_zoopt_search_space..rlr!) r rBrCrnr\ray.tune.search.zooptr1ror^rrrE) rFr\r1r^r{r|_rr,rdim_dicts r_convert_zoopt_search_spacers 9'BCA1+!%4@N).9M1aR_`;4!7$!77>``//6H & &&as #BcVt|\}}ddlm}|d||t|d|fS)aCreate a ZOOpt searcher with required budget and converted search space. Args: space (dict): The hyperparameter search space. task (str): The task type (e.g., 'detect', 'segment', 'classify'). iterations (int): The maximum number of trials (budget) for ZOOpt. Returns: (tuple): A tuple containing the ZOOptSearch searcher and fixed parameter space dict. Raises: ImportError: If the 'zoopt' package is not installed. rrasracosr)algobudgetrrr)rrr1r)rFrR iterationsrrr1s r_create_zoopt_searchrs>#>e"DH1  zH[QUEV]b  r?cD|d|dfSt|}t|trI|sd|dfS|tvr0dj t t}t d|d|d|dk(rd||fS |dk(r/t|trt||i|fSt||i|fS|dk(r5t|trt||\}}nt|\}}|}|||fS|d k(rt|||fS|d k(r6t|trt|||\}}nt|\}}|}|||fSt|ts||dfSt|} | rtj| d d lm} | |t$|d ||fS#t&t(f$r} t)d|d| | d} ~ wwxYw)aResolve search algorithms and normalize Tune param_space for known Ray Tune searchers. Args: search_alg (str | object | None): The search algorithm to use. Can be a string name, a pre-instantiated Ray Tune searcher object, or None for default behavior. task (str): The task type (e.g., 'detect', 'segment', 'classify'). space (dict): The hyperparameter search space. iterations (int): The maximum number of trials to run. Returns: (tuple): A tuple containing (resolved_search_alg, tuner_param_space, resolved_search_alg_kind). - resolved_search_alg: The configured searcher or None. - tuner_param_space: The normalized parameter space for the tuner. - resolved_search_alg_kind: The normalized algorithm name or None. Raises: ValueError: If an unsupported search_alg string is provided. ModuleNotFoundError: If required dependencies for the chosen algorithm are not installed. Nz, z!Unsupported Ray Tune search_alg 'z'. Supported values: rjrrrrrr)create_searcherr)rrzRay Tune search_alg 'z4' requires additional dependencies. Original error: )r>r"r2rCrrsortedrprSrGrrrrrr rBray.tune.searchrr ImportErrorModuleNotFoundError) r9rRrFrr: supportedresolved_search_algtuner_param_spacer requirementsres r_resolve_ray_search_algrs(UD  )*5J*c"$ $ 8 8 &)D"EFI@ Labkallmno o  ! * *#  *c*(5r:EE %e ,r:- -  *c*9LUTX9Y6#%6'A%'H$$&0#&(9:E E  $+D15*D D  *c*9MeUY[e9f6#%6'B5'I$$&0#&(9:E E*c*ud* *2:>   % %l 33z+d2C%PRWYccc , -!#J:E99FFFc  tjd tjdddlddlmddlm}ddlm }m }  ddl } t| d sJ tj j"d d id j%dddj%dddj%dddj%dddj%dddj%dddj%dddj%dd d!j%ddd"j%d#d$d%j%ddd&j%dd'd(j%dd'd)j%dd*d+j%dd'd,j%ddd-j%dd.j%ddj%ddj%ddj%ddj%ddj%ddj%ddj%ddj'dd/d0 } |j(} j+|j-d1d2fd3} |s(j-d4s| }tj.d5j-d6t0| }||d6<d6vrtj.d7|d8t3|| ||\}}}j5| t6|xsdd9}j-d:xs t8d:xsd;}|d?}|d@k(r| dA}t?tAtBidBjEd4d ijEd1d2C}|jGdDdDEjHjK|rLtjtMdFdG|dHjHjOtQ||dDI}nGjI||jS|||dJdKL||jT|jVMN}|jY|j[}j]|S#t$r tdwxYw#ttf$rd } YwxYw)OaRun hyperparameter tuning using Ray Tune. Args: model (YOLO): Model to run the tuner on. space (dict, optional): The hyperparameter search space. If not provided, uses default space. grace_period (int, optional): The grace period in epochs of the ASHA scheduler. gpu_per_trial (int, optional): The number of GPUs to allocate per trial. iterations (int, optional): The maximum number of trials to run. search_alg (str | ray.tune.search.Searcher | ray.tune.search.SearchAlgorithm, optional): Search algorithm to use. Strings are resolved to supported Ray Tune searchers. Pre-instantiated objects are reused, and known searchers with special Tune param_space requirements are normalized automatically. **train_args (Any): Additional arguments to pass to the `train()` method. Returns: (ray.tune.ResultGrid): A ResultGrid containing the results of the hyperparameter search. Examples: >>> from ultralytics import YOLO >>> model = YOLO("yolo26n.pt") # Load a YOLO26n model Start tuning hyperparameters for YOLO26n training on the COCO8 dataset >>> result_grid = model.tune(data="coco8.yaml", use_ray=True) uN💡 Learn about RayTune at https://docs.ultralytics.com/integrations/ray-tunez ray[tune]rN)tune) RunConfig) ASHASchedulerHyperBandForBOHBzHRay Tune required but not found. To install run: pip install "ray[tune]" __version__Fz>=2.0.0raylr0gh㈵>g{Gz?lrfg?momentumgffffff?g\(\? weight_decayggMbP? warmup_epochsg@warmup_momentumgffffff?boxg4@r;g?g@cls_pwdflg?g(@hsv_hhsv_sg?hsv_vdegreesgF@ translatescaleshearg$@ ) perspectiveflipudfliplrbgrmosaicmixupcutmix copy_paste close_mosaicr=rclj}d|_|jtt |}|j  j }d|vr|jddn|}d||d<|jdi|}|jS#t$r|d<Y.wxYw)zKTrain the YOLO model with the specified hyperparameters and return results.Nrr=) gettrainerreset_callbacksrr#update get_trial_idsplit Exceptiontrain results_dict) configmodel_to_traintrial_id trial_suffixresults base_namemodel_in_storer train_argsrs r_tunezrun_ray_tune.._tunes0!%&&(%d6l3 j! '((*H69Xo8>>#.r28L ){!L>:F6N '.&&00###  '&F6N 's4B""B32B3resumez6Search space not provided, using default search space.dataz'Data not provided, using default "data=z".)cpugpuepochsdepochr) time_attrrrmax_t grace_periodreduction_factorr)rrrrrexist_ok)r=T)parentsrzTuner: z Resuming tuning run z...) trainableresume_erroredc8|jd|jSNrtrainable_namertrials rzrun_ray_tune..sE4H4H3I5>>JZ1[r?c8|jd|jSrrrs rrzrun_ray_tune..su7K7K6LAennM]4^r?)r9 scheduler num_samplestrial_name_creatortrial_dirname_creator) storage_pathr=) param_space tune_config run_config)/r infor rBrrray.tunerray.tune.schedulersrrrrwandbhasattrAssertionError check_versionruniformrandintrRputrwarningrrwith_resourcesr r rminrrrpopmkdirTuner can_restorer restorer2 TuneConfigparentr=fit get_resultsshutdown)modelrFr gpu_per_trialrr9rrrrr default_spacerRrrrrresolved_search_alg_kindtrainable_with_resourcesrrtune_dirtunerrrrrrs ` @@@@r run_ray_tuner Ns@ KK`an!!+.&Gum,,, )U; t||D$' t||D#& DLLd+   S%0  c3/  4<<T2 t||C& t||C% $,,sC( t||C& c3' c3' c3' 4<<T* T\\#s+!" c4(#$ c4(%&||C/,,sC(,,sC(||C%,,sC(c3',,sC(ll3, Q+7M> ::DWWU^Nvv.I$$* 1OP >>&)D/ 2DE&M Z@bIJG^D%HD*,D $225+VcVhgh:ij NN8 $ I(8(B IcE4 u- I 6)$t$    Kz Kj*..5*IJ K ^^FF + H NN4$N/ zzh' x *++@ #NO ""3x=rGrSrrrrrrr rr?rr's#IIbb . = )   ,60&)66!rW(e('2.DR $ r rr r  rr?