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'Smart_aug' is module to make data_augmentation differentiable, thus allowing to learn its parameters, with 'Data_aug' classes.


# Requirements and Installation

* Python version >= 3.5
* PyTorch version >= 1.3
* Higher version >=

# Example Usage

Look to 'test_dataug.py'

![Optimization process](docs/smart_aug_optim.png "Optimization process")
![Forward data augmentation](docs/smart_aug_forward.png "Forward data augmentation")
![UML](docs/smart_aug_uml.png "UML")