:py:mod:`train_autoencoder`
===========================

.. py:module:: train_autoencoder

.. autoapi-nested-parse::

   Trains (or validates etc.) an AutoEncoder model against images using the PyTorch Lightning Command Line Interface.

   Please see :class:`cnn.AutoEncoder` for details of the auto-encoder architecture.

   Input Arguments
   ===============

   Please see `PyTorch Lightning CLI <https://pytorch-lightning.readthedocs.io/en/stable/common/lightning_cli.html>`_ for
   details on how to use the command line interface.

   The help page prints all options::

       python -m anchor_python_training.train_autoencoder -h

   As a suggestion, first create a configuration file by saving the contents to e.g. `config.yaml`::

       python -m anchor_python_training.train_autoencoder fit --print_config

   and then use these configuration file to perform the training::

       python -m anchor_python_training.train_autoencoder fit --config config.yaml

   The outputted model is saved incrementally via checkpoints to a directory `lightning_logs` in the working directory
   (unless otherwise configured).

   The `predict` subcommand is not currently recommended for productive use.



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


Functions
~~~~~~~~~

.. autoapisummary::

   train_autoencoder.main



.. py:function:: main()