scaffold.torch.lightning.loggers
================================

.. py:module:: scaffold.torch.lightning.loggers


Attributes
----------

.. autoapisummary::

   scaffold.torch.lightning.loggers.logger


Classes
-------

.. autoapisummary::

   scaffold.torch.lightning.loggers.HyperoptLightningLogger


Module Contents
---------------

.. py:class:: HyperoptLightningLogger

   Bases: :py:obj:`pytorch_lightning.loggers.logger.Logger`


   
   Lightning wrapper around hyperopt logging.


   .. py:method:: finalize(status: str) -> None

      Finalisation of experiment run.

      :param status: The experiment outcome (success, failed, etc.).
      :type status: str



   .. py:method:: log_hyperparams(params: Union[Dict[str, Any], argparse.Namespace]) -> None

      Logging of hyperparameters for experiment.

      :param params: The parameters to be logged.
      :type params: argparse.Namespace



   .. py:method:: log_metrics(metrics: Dict[str, Any], step: int) -> None

      Logging of metrics.

      :param metrics: Dictionary of metric names and values to be logged
      :type metrics: Dict
      :param step: The step counter of optimisation iterations
      :type step: int



   .. py:property:: name
      :type: str


      The experiment name.


   .. py:property:: version
      :type: str


      The experiment version.


.. py:data:: logger