optuna.integration.AllenNLPExecutor¶
- class optuna.integration.AllenNLPExecutor(trial: optuna.trial._trial.Trial, config_file: str, serialization_dir: str, metrics: str = 'best_validation_accuracy', *, include_package: Optional[Union[str, List[str]]] = None)[source]¶
AllenNLP extension to use optuna with Jsonnet config file.
This feature is experimental since AllenNLP major release will come soon. The interface may change without prior notice to correspond to the update.
See the examples of objective function and config file.
Note
In
AllenNLPExecutor
, you can pass parameters to AllenNLP by either defining a search space using Optuna suggest methods or setting environment variables just like AllenNLP CLI. If a value is set in both a search space in Optuna and the environment variables, the executor will use the value specified in the search space in Optuna.- Parameters
trial – A
Trial
corresponding to the current evaluation of the objective function.config_file – Config file for AllenNLP. Hyperparameters should be masked with
std.extVar
. Please refer to the config example.serialization_dir – A path which model weights and logs are saved.
metrics – An evaluation metric for the result of
objective
.include_package – Additional packages to include. For more information, please see AllenNLP documentation.
Note
Added in v1.4.0 as an experimental feature. The interface may change in newer versions without prior notice. See https://github.com/optuna/optuna/releases/tag/v1.4.0.
- __init__(trial: optuna.trial._trial.Trial, config_file: str, serialization_dir: str, metrics: str = 'best_validation_accuracy', *, include_package: Optional[Union[str, List[str]]] = None)[source]¶
Methods
__init__
(trial, config_file, serialization_dir)run
()Train a model using AllenNLP.