Metadata-Version: 2.1
Name: deepcs
Version: 0.2.7
Summary: deepcs provides utilitary functions for the CentraleSupelec deeplearning lab works
Author-email: Jeremy Fix <jeremy.fix@centralesupelec.fr>
Maintainer-email: Jeremy Fix <jeremy.fix@centralesupelec.fr>
License: SPDX-License-Identifier: CECILL-C
        
        Copyright (C) 2020- CentraleSupélec and contributors
        
        deepcs is available under the terms of the Cecill-C License (see Licence_CeCILL-C.txt).
        
Keywords: deep learning,CentraleSupelec
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE.txt
Requires-Dist: torch >=1.5.0
Requires-Dist: torchinfo >=0.0.9
Requires-Dist: torchvision >=0.6

# Deepcs package

The package can be installed with pip, see the [pypi page](https://pypi.org/project/deepcs/)

This package is used within the deeplearning labs at CentraleSupélec you can access on [this page](https://github.com/jeremyfix/deeplearning-lectures).

It provides some handy high level functions :

- for the training and validation loops
- for displaying the summary of a model and progress during training
- for easily getting unique log directories for logging the training with your tensorboard writer

Note, though, that if you ended up on this page, you may still be interested in more professional libraries such as [torch lightning](https://www.pytorchlightning.ai/) which provides you with the high level pytorch scripting we need for easily experimenting.
