lightning_template.utils.cli
============================

.. py:module:: lightning_template.utils.cli


Submodules
----------

.. toctree::
   :maxdepth: 1

   /autoapi/lightning_template/utils/cli/argument_parsers/index
   /autoapi/lightning_template/utils/cli/cli/index
   /autoapi/lightning_template/utils/cli/instantiate_class/index
   /autoapi/lightning_template/utils/cli/trainer/index


Classes
-------

.. autoapisummary::

   lightning_template.utils.cli.LightningCLI
   lightning_template.utils.cli.Trainer


Functions
---------

.. autoapisummary::

   lightning_template.utils.cli.recursive_instantate_class


Package Contents
----------------

.. py:class:: LightningCLI(save_config_callback: Optional[Type[lightning.pytorch.cli.SaveConfigCallback]] = SaveAndLogConfigCallback, trainer_class: Union[Type[lightning_template.utils.cli.trainer._Trainer], Callable[Ellipsis, lightning_template.utils.cli.trainer._Trainer]] = Trainer, *args, **kwargs)

   Bases: :py:obj:`lightning.pytorch.cli.LightningCLI`


   Implementation of a configurable command line tool for pytorch-lightning.


   .. py:method:: _setup_parser_kwargs(*args, **kwargs) -> Tuple[Dict[str, Any], Dict[str, Any]]


   .. py:method:: add_default_arguments_to_parser(parser: lightning.pytorch.cli.LightningArgumentParser) -> None

      Adds default arguments to the parser.



   .. py:method:: randomly_select_seed() -> int
      :staticmethod:



   .. py:method:: _set_seed() -> None

      Sets the seed.



   .. py:method:: before_instantiate_classes() -> None

      Implement to run some code before instantiating the classes.



   .. py:method:: _add_configure_optimizers_method_to_model(*args, **kwargs) -> None

      Overrides the model's :meth:`~lightning.pytorch.core.LightningModule.configure_optimizers` method if a
      single optimizer and optionally a scheduler argument groups are added to the parser as 'AUTOMATIC'.



.. py:function:: recursive_instantate_class(config)

.. py:class:: Trainer(num_folds: Optional[int] = None, *args, **kwargs)

   Bases: :py:obj:`lightning.pytorch.Trainer`


   .. py:attribute:: num_folds
      :value: None