Metadata-Version: 2.1
Name: deepcs
Version: 0.2.1
Summary: deepcs provides utilitary functions for the CentraleSupelec deeplearning lab works
Home-page: https://github.com/jeremyfix/deepcs/tree/main/
Author: Jeremy Fix
Author-email: jeremy.fix@centralesupelec.fr
License: CeCILL-C License V1
Keywords: deep learning,centralesupelec
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: CeCILL-C Free Software License Agreement (CECILL-C)
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Provides-Extra: dev
License-File: LICENSE.txt

# 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.


