jP ddlmZddlZddlmZmZmZmZddl m Z m Z m Z m Z mZmZdddddgd d d d d d Zd$dZdZdZdZdZdZdZdZdZdZ d%d&d#ZdS)') annotationsN) TASK2DATA TASK2METRICget_cfg get_save_dir) DEFAULT_CFGDEFAULT_CFG_DICTLOGGER NUM_THREADScheckscolorstrz ax-platformzbayesian-optimization==1.4.3 hpbandster ConfigSpacez HEBO>=0.2.0hyperopt nevergradoptunazoopt) randomaxbayesoptbohbheborrrrvaluedictct|trd|DSt|tr d|DSt|trt d|DSt|t jr|St|t jr| S|S)a#Convert NumPy-backed Tune values into native Python types for YAML serialization. Args: value (dict): The value to convert. Can be a dict, list, tuple, NumPy scalar, or NumPy array. Returns: The converted value with NumPy types replaced by native Python types. c4i|]\}}|t|S_sanitize_tune_value).0kvs Z/var/www/html/Carbon-Document/venv/lib/python3.11/site-packages/ultralytics/utils/tuner.py z(_sanitize_tune_value..!s'EEEtq!'**EEEc,g|]}t|Srrr r"s r# z(_sanitize_tune_value..#s!777A$Q''777r%c34K|]}t|VdSNrr's r# z'_sanitize_tune_value..%s+<<)!,,<<<<<3.s(,,!s1vv,,,,,,r%zWTuneBOHB does not support quantized search spaces with the current ConfigSpace version.)r;upperlog)choicesz-TuneBOHB does not support parameters of type z with sampler type .cTi|]%\}}dd|D|&S)rgc34K|]}t|VdSr*rirjs r#r+z8_convert_bohb_search_space...(!7!7Q#a&&!7!7!7!7!7!7r%joinr pathrs r#r$z._convert_bohb_search_space..9```;4!7!7$!7!7!777```r%)r rHrIrray.tune.search.sampler[r\r]r^r_r`!ray.tune.search.variant_generatorrbray.tune.utilsrd ValueErrorConfigurationSpaceru get_samplerr,addUniformFloatHyperparameterr;rlUniformIntegerHyperparameterCategoricalHyperparameter categoriestyper>sampler)rLrr[r\r]r^r_r`rbrdresolved_space resolved_vars domain_vars grid_varscsrwdomainparrrlfixed_param_spaces r#_convert_bohb_search_spacervs 9&ABBBbbbbbbbbbbbbbbbbAAAAAA++++++!\%4@@@N,;ON,K,K)M; qoppp  ' ' ) )B# fhh,,t,,,,,$$&& gy ) ) xvww w fe $ $ Ggz=R)S)S  FF66v|6]>]9      , , GW1M1M  FF;88fFW8XX Y Y Y YFV @UFF%)&.%9%9%BFFF  a`R_```   r%cht|\}}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)r7max)rLmetricmode)r ray.tune.search.bohb.bohb_searchr7r)rLrXrrr7s r#_create_bohb_searchrsK7u==B999999 8"[%6U C C CEV VVr%ctjtdddl}ddlm}||jjt|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 rHrIrray.tune.search.nevergradr optimizers OnePlusOner)rXngrs r#_create_nevergrad_searchrs\ 9+FGGG999999 ?R]%=kRVFW^c d d ddr%ctjtdddlm}ddlm}ddlm}||d}||\}}}d|D}| |}||fS) 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. rrrar8rcTrecTi|]%\}}dd|D|&S)rgc34K|]}t|VdSr*rirjs r#r+z9_convert_zoopt_search_space...rsr%rtrvs r#r$z/_convert_zoopt_search_space..rxr%) r rHrIrzrbray.tune.search.zooptr8r{rdrK) rLrbr8rdrr_rdim_dicts r#_convert_zoopt_search_spacers 9'BCCCAAAAAA111111++++++!\%4@@@N)/.99M1a``R_```//66H & &&r%clt|\}}ddlm}|d||t|d|fS)aCreate a ZOOpt searcher with required budget and converted search space. Args: space (dict): The hyperparameter search space. task (str): The task type (e.g., 'detect', 'segment', 'classify'). iterations (int): The maximum number of trials (budget) for ZOOpt. Returns: (tuple): A tuple containing the ZOOptSearch searcher and fixed parameter space dict. Raises: ImportError: If the 'zoopt' package is not installed. rrasracosr)algobudgetrrr)rrr8r)rLrX iterationsrrr8s r#_create_zoopt_searchrs\#>e"D"DH111111 ; zH[QUEV]b    r%c|d|dfSt|}t|trX|sd|dfS|tvr=dt t}t d|d|d|dkrd||fS |dkr  4  %l 3 3 3333333z+d2C%PPPRWYccc , -! gJ g gde g g   s?-G3GAGG'AG0G AGG; G66G; rL dict | None grace_periodint gpu_per_trial int | Nonerc N tjd tjddgddlddlmddlm}dd lm }m } n#t$rtd wxYw ddl } t| d sJn#ttf$rd } YnwxYwtjjd didddddddddddddddddddddd d!d"d#ddd$d%d&d'dd!d(dd)d*dd)d+dd,d-dd)d.ddd/dd0dddddddddddddddddd1d2 } |j} |d3d4fd5} |s+d6s| }tjd7d8t0| }||d8<d8vrtjd9|d:t3|| ||\}}}| t6|pdd;}d<pt8d<pd=}|d>t:| d?|t=||d@A}|dBkr| d>t:| d?|d@C}t?tAtBidD"d6d i"d3d4E}|#dFdFGj$%|rRtjtMdHdI|dJj$'tQ||dFK}nH$||)|||dLdMN||j*|j+OP}|,|-}.|S)QaRun 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]zpydantic>=2.0,<2.12) constrainrN)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@rBg?g@cls_pwdflg?g(@hsv_hhsv_sg?hsv_vdegreesgF@ translatescaleshearg$@ ) perspectiveflipudfliplrbgrmosaicmixupcutmix copy_paste close_mosaicrDrc}d|_|tt |}| }d|vr|ddn|}d||d<n#t$r|d<YnwxYw|j di|}|j S)zKTrain the YOLO model with the specified hyperparameters and return results.NrrDr) gettrainerreset_callbacksrrupdate get_trial_idsplit Exceptiontrain results_dict) configmodel_to_traintrial_id trial_suffixresults base_namemodel_in_storer train_argsrs r#_tunezrun_ray_tune.._tunes00!%&&(((%d6ll33 j!!! '((**H69Xoo8>>#..r228L )::L::F6NN ' ' '&F6NNN ''.&0000##s$?B$$B65B6resumez6Search space not provided, using default search space.dataz'Data not provided, using default "data=z".)cpugpuepochsdepochr) time_attrrrmax_trreduction_factorr)rrrrrexist_ok)rDT)parentsrzTuner: z Resuming tuning run z...) trainableresume_erroredc$|jd|jSNrtrainable_namertrials r#zrun_ray_tune..sE4H1[1[5>1[1[r%c$|jd|jSrrrs r#rzrun_ray_tune..su7K4^4^en4^4^r%)r@ scheduler num_samplestrial_name_creatortrial_dirname_creator) storage_pathrD) param_space tune_config run_config)/r infor rHrrray.tunerray.tune.schedulersrrrrwandbhasattrAssertionError check_versionruniformrandintrXputrwarningrrwith_resourcesr r rminrrrpopmkdirTuner can_restorer restorer9 TuneConfigparentrDfit get_resultsshutdown)modelrLrrrr@rrrrr default_spacerXrrrrresolved_search_alg_kindtrainable_with_resourcesrr tune_dirtunerrrrrrs ` @@@@r# run_ray_tuner/Ns@ K`aaan!+:O9PQQQQ &&&&&&GGGGGGGGG nnn!"lmmmn um,,,,,,  ( )U;;; t||D$'' t||D#&& DLLd++   S%00  c3//  4<<T22 t||C&& t||C%% $,,sC(( t||C&& c3'' c3'' c3'' 4<<T** T\\#s++!" c4((#$ c4((%&||C//,,sC((,,sC((||C%%,,sC((c3'',,sC((ll3,, Q++7M> :DWWU^^Nvv..I$$$$$$$$$* Q11QOPPP >>&)D/ 2 2DE&M ZIIIIJJJG^D%HHD*,D $225+VcVhgh:i:ijj NN8 $ $ I(8(B IcE 4 u-- I 6))$$t$      Kz Kj*..5*I*IJ K  ^^FF + + H NN4$N/// zh''  x **NNNNNOOO ""3x==r4s#"""""IIIIIIIIIIIIbbbbbbbbbbbbbbbb . = )    ,6000&)))66!6!6!rWWW(eee('''2.DDDR $ rrrrrrrr%