ride.hparamsearch
¶
Module Contents¶
Classes¶
Attributes¶
- class ride.hparamsearch.Hparamsearch(Module: Type[ride.core.RideModule])[source]¶
- configs() ride.core.Configs [source]¶
- run(args: pytorch_lightning.utilities.parsing.AttributeDict)[source]¶
Run hyperparameter search using the tune.schedulers.ASHAScheduler
- Parameters:
args (AttributeDict) – Arguments
- Side-effects:
Saves logs to TUNE_LOGS_PATH / args.id
- static dump(hparams: dict, identifier: str, extention='yaml') str [source]¶
Dumps haparams to TUNE_LOGS_PATH / identifier / “best_hparams.json”
- static load(path: Union[pathlib.Path, str], old_args=AttributeDict(), Cls: Type[ride.core.RideModule] = None, auto_scale_lr=False) pytorch_lightning.utilities.parsing.AttributeDict [source]¶
Loads hparams from path
- Parameters:
path (Union[Path, str]) – Path to jsonfile containing hparams
old_args (Optional[AttributeDict]) – The AttributeDict to be updated with the new hparams
cls (Optional[RideModule]) – A class whole hyperparameters can be used to select the relevant hparams to take
- Returns:
AttributeDict with updated hyperparameters
- Return type:
AttributeDict