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LightningArgumentParser

class pytorch_lightning.cli.LightningArgumentParser(*args, **kwargs)[source]

Bases: object

Extension of jsonargparse’s ArgumentParser for pytorch-lightning.

Initialize argument parser that supports configuration file input.

For full details of accepted arguments see ArgumentParser.__init__.

add_lightning_class_args(lightning_class, nested_key, subclass_mode=False, required=True)[source]

Adds arguments from a lightning class to a nested key of the parser.

Parameters
Return type

List[str]

Returns

A list with the names of the class arguments added.

add_lr_scheduler_args(lr_scheduler_class=(<class 'torch.optim.lr_scheduler._LRScheduler'>, <class 'pytorch_lightning.cli.ReduceLROnPlateau'>), nested_key='lr_scheduler', link_to='AUTOMATIC')[source]

Adds arguments from a learning rate scheduler class to a nested key of the parser.

Parameters
  • lr_scheduler_class (Union[Type[_LRScheduler], Type[ReduceLROnPlateau], Tuple[Union[Type[_LRScheduler], Type[ReduceLROnPlateau]], ...]]) – Any subclass of torch.optim.lr_scheduler.{_LRScheduler, ReduceLROnPlateau}. Use tuple to allow subclasses.

  • nested_key (str) – Name of the nested namespace to store arguments.

  • link_to (str) – Dot notation of a parser key to set arguments or AUTOMATIC.

Return type

None

add_optimizer_args(optimizer_class=(<class 'torch.optim.optimizer.Optimizer'>, ), nested_key='optimizer', link_to='AUTOMATIC')[source]

Adds arguments from an optimizer class to a nested key of the parser.

Parameters
Return type

None

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