-ji-SSKJr SSKJr SSKJr SSKrSSKJr SSKJ r SSKJ r SSKJ r SSK r SS KJr SS KJr SS KJr SS KJr SS KJr SSKJr SSKJr \ (aSSKJr \ \\\\ S4r!\"\"5r#"SS\5r$g)) annotations)Mapping)SequenceN)Real)Any) TYPE_CHECKING)Union) optuna_warn)BaseDistribution) get_logger) BaseSampler)LazyRandomState) FrozenTrial) TrialState)Studyc\rSrSrSrSSSjjrSSjrSSjrSSjrSSjr SS jr SS jr \ SS j5r SS jr\ SS j5rSSjrSSjrSrg) GridSampler ab Sampler using grid search. With :class:`~optuna.samplers.GridSampler`, the trials suggest all combinations of parameters in the given search space during the study. Example: .. testcode:: import optuna def objective(trial): x = trial.suggest_float("x", -100, 100) y = trial.suggest_int("y", -100, 100) return x**2 + y**2 search_space = {"x": [-50, 0, 50], "y": [-99, 0, 99]} study = optuna.create_study(sampler=optuna.samplers.GridSampler(search_space)) study.optimize(objective) Note: This sampler with :ref:`ask_and_tell` raises :exc:`RuntimeError` just after evaluating the final grid. This is because :class:`~optuna.samplers.GridSampler` automatically stops the optimization if all combinations in the passed ``search_space`` have already been evaluated, internally invoking the :func:`~optuna.study.Study.stop` method. As a workaround, we need to handle the error manually as in https://github.com/optuna/optuna/issues/4121#issuecomment-1305289910. Note: :class:`~optuna.samplers.GridSampler` does not take care of a parameter's quantization specified by discrete suggest methods but just samples one of values specified in the search space. E.g., in the following code snippet, either of ``-0.5`` or ``0.5`` is sampled as ``x`` instead of an integer point. .. testcode:: import optuna def objective(trial): # The following suggest method specifies integer points between -5 and 5. x = trial.suggest_float("x", -5, 5, step=1) return x**2 # Non-int points are specified in the grid. search_space = {"x": [-0.5, 0.5]} study = optuna.create_study(sampler=optuna.samplers.GridSampler(search_space)) study.optimize(objective, n_trials=2) Note: A parameter configuration in the grid is not considered finished until its trial is finished. Therefore, during distributed optimization where trials run concurrently, different workers will occasionally suggest the same parameter configuration. The total number of actual trials may therefore exceed the size of the grid. Note: All parameters must be specified when using :class:`~optuna.samplers.GridSampler` with :meth:`~optuna.study.Study.enqueue_trial`. Args: search_space: A dictionary whose key and value are a parameter name and the corresponding candidates of values, respectively. seed: A seed to fix the order of trials as the grid is randomly shuffled. This shuffle is beneficial when the number of grids is larger than ``n_trials`` in :meth:`~optuna.Study.optimize` to suppress suggesting similar grids. Please note that fixing ``seed`` for each process is strongly recommended in distributed optimization to avoid duplicated suggestions. Nc^UR5Hup4UHnURX55 M M! 0Ul[UR55Hup4[ U5URU'M [ [ R "URR565Ul[UR55Ul [UR5Ul [U=(d S5UlURRR!UR5 g)Nr)items _check_value _search_spacesortedlist itertoolsproductvalues _all_gridskeys _param_nameslen _n_min_trialsr_rngrngshuffle)self search_spaceseed param_name param_valuesvalues O/home/james-whalen/.local/lib/python3.13/site-packages/optuna/samplers/_grid.py__init__GridSampler.__init__ms)5(:(:(< $J%!!*4&)= (.|/A/A/C(D $J-1,-?D  z *)Ey00$2D2D2K2K2MNO"<#4#4#67 1#DIA.  doo.cLURRR5 gN)r#r$r()r&s r, reseed_rngGridSampler.reseed_rng~s r/c$SUR;dSUR;agSUR::a}URUR:acURR UR SUR 5 URR UR SUR5 gURU5n[U5S:Xa<[RS5 [[[UR555n[URR R#U55nURR UR SUR 5 URR UR SU5 g)Ngrid_id fixed_paramsrr'z`GridSampler` is re-evaluating a configuration because the grid has been exhausted. This may happen due to a timing issue during distributed optimization or when re-running optimizations on already finished studies.) system_attrsnumberr"_storageset_trial_system_attr _trial_idr_get_unvisited_grid_idsr!_loggerwarningrrangerintr#r$choice)r&studytrial target_gridsr5s r, before_trialGridSampler.before_trials) ** *n@R@R.R   0B0B!B NN 0 01C1C  NN 0 0)U\\ Z 33E: |  ! OOP  c$//&: ;O=PQG G  Gr/c/n/nURRURSS9nUHnSUR;dMUR URS5(dM:UR R 5(a URURS5 MyUR [R:XdMURURS5 M [[UR55[U5- [U5- n[U5S:Xa*[[UR55[U5- n[U5$)NF)deepcopyr5r'r)r9get_all_trials _study_idr7_same_search_spacer^ is_finishedappendrRUNNINGsetr?r"r!r)r&rB visited_grids running_gridstrialstunvisited_gridss r,r<#GridSampler._get_unvisited_grid_idss  ..u.OAANN*t/F/F~.0077&&((!(( )BCWW 2 22!(( )BCeD$6$6783};MMPSTaPbb  1 $!%(:(:";Y    -  4  '      %8GG =r/r)% __future__rcollections.abcrrrnumbersrtypingrrr numpyrxoptuna._warningsr optuna.distributionsr optuna.loggingr optuna.samplersr "optuna.samplers._lazy_random_stater optuna.trialrr optuna.studyrrcrdr@rerrr=rrHr/r,rsn"#$ (1%'>$#"c5#tT12  X ~=+~=r/