AntoineH/smart_augmentation
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'Smart_aug' objective is to make data augmentation differentiable, thus allowing to learn its parameters, with 'Higher' objects, such as 'Data_aug' classes. The meta-learning of the data augmentation parameter is performed jointly with the training of the model. Thus it minimize the overhead compared to other data augmentation learning techniques.
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Harle, Antoine (Contracteur) a2135e4709 Evite redefinition inutile de prob dist + Fix mineur transformation
2020-01-27 17:29:25 -05:00
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higher Evite redefinition inutile de prob dist + Fix mineur transformation 2020-01-27 17:29:25 -05:00
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README.md Ajout d'un Readme 2020-01-24 15:19:49 -05:00

README.md

'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'