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@ -13,10 +13,10 @@ It's also possible to use the, non-differentiable, data augmentation module 'Ran
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* Python version >= 3.5
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* PyTorch version >= 1.3
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* Kornia version >= 0.2.0
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* Higher version >=
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* Higher version >= 0.1.5
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* Optionnal:
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..* matplot >=
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..* matplot >= 3.1.1
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## Kornia
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@ -101,4 +101,6 @@ We rely on the 'Higher' library to solve this bi-level optimisation problem. See
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## Code example
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An example use of Smart_aug can be found in 'test_dataug.py' with Augmented model, and 'run_dist_dataugV3' in 'train_utils.py'.
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An example use of Smart_aug can be found in 'smart_aug_example.py', and 'run_simple_smartaug' in 'train_utils.py'.
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For more control over the optimization process see 'test_dataug.py' and 'run_dist_dataugV3' in 'train_utils.py'.
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