optuna.integration.ChainerMNStudy¶
- class optuna.integration.ChainerMNStudy(study: Study, comm: CommunicatorBase)[source]¶
A wrapper of
Study
to incorporate Optuna with ChainerMN.See also
ChainerMNStudy
provides the same interface asStudy
. Please refer tooptuna.study.Study
for further details.See the example if you want to optimize an objective function that trains neural network written with ChainerMN.
- Parameters
study – A
Study
object.comm – A ChainerMN communicator.
Methods
__init__
(study, comm)optimize
(func[, n_trials, timeout, catch])Optimize an objective function.
- optimize(func: Callable[[ChainerMNTrial, CommunicatorBase], float], n_trials: Optional[int] = None, timeout: Optional[float] = None, catch: Tuple[Type[Exception], ...] = ()) None [source]¶
Optimize an objective function.
This method provides the same interface as
optuna.study.Study.optimize()
except the absence ofn_jobs
argument.