lightning_template.utils#
Subpackages#
lightning_template.utils.callbackslightning_template.utils.callbacks.custom_reprlightning_template.utils.callbacks.model_checkpointlightning_template.utils.callbacks.save_and_log_config_callbacklightning_template.utils.callbacks.set_precision_and_cudnn_callbacklightning_template.utils.callbacks.set_sharing_strategy_callbacklightning_template.utils.callbacks.set_wandb_logger_callback
lightning_template.utils.clilightning_template.utils.loggerslightning_template.utils.looplightning_template.utils.mixinlightning_template.utils.optimlightning_template.utils.progresslightning_template.utils.timer
Package Contents#
Classes#
Implementation of a configurable command line tool for pytorch-lightning. |
|
- class lightning_template.utils.LightningCLI(save_config_callback: Type[lightning.pytorch.cli.SaveConfigCallback] | None = SaveAndLogConfigCallback, trainer_class: Type[lightning_template.utils.cli.trainer._Trainer] | Callable[Ellipsis, lightning_template.utils.cli.trainer._Trainer] = Trainer, *args, **kwargs)#
Bases:
lightning.pytorch.cli.LightningCLIImplementation of a configurable command line tool for pytorch-lightning.
- _setup_parser_kwargs(*args, **kwargs) Tuple[Dict[str, Any], Dict[str, Any]]#
- add_default_arguments_to_parser(parser: lightning.pytorch.cli.LightningArgumentParser) None#
Adds default arguments to the parser.
- static randomly_select_seed() int#
- _set_seed() None#
Sets the seed.
- before_instantiate_classes() None#
Implement to run some code before instantiating the classes.
- _add_configure_optimizers_method_to_model(*args, **kwargs) None#
Overrides the model’s
configure_optimizers()method if a single optimizer and optionally a scheduler argument groups are added to the parser as ‘AUTOMATIC’.
- class lightning_template.utils.Trainer(num_folds: int | None = None, *args, **kwargs)#
Bases:
lightning.pytorch.Trainer