augmentation_code
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Reproducible code for Augmentation paper
Augmentation
Dependencies
- Python 3.6+
- Pillow, matplotlib, numpy, pytorch==0.4.0, seaborn, torchvision
Usage
-
mnist_experiments.py
runs a full set of experiments on MNIST and save the results to the directorysaved
. Note: the default run take a long time (43 hours) to finish, since we're running for all 10 seeds.python mnist_experiments.py
Currently, it executes the following experiments:
- Measure the difference between exact augmented objective and approximate objectives (on original images, 1st order approximation, 2nd order approximation).
- Measure the agreement and KL divergence between the predictions made by model trained on exact augmented objective and models trained on approximate objectives.
- Compute kernel target alignment for features from different transformations.
-
plot.py
plots all the figures in the paper using the saved results frommnist_experiments.py
. The figures are saved in the directoryfigs
.python plot.py