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evaluation

evaluation

 
 

noise

noise

 
 

README.md

README.md

 
 

acgd.py

acgd.py

 
 

augment.py

augment.py

 
 

evaluation.py

evaluation.py

 
 

graph_dataset_mnist.py

graph_dataset_mnist.py

 
 

main.py

main.py

 
 

model.py

model.py

 
 

save_outputs.py

save_outputs.py

 
 

spectral_normalization.py

spectral_normalization.py

 
 

superpixels_dataset.py

superpixels_dataset.py

 
 

utils.py

utils.py

 
 

README.md

Generating MNIST datasets

Run main.py with the default parameters to start training. MNIST Superpixels graphs are generated by default, use --sparse-mnist to generate Sparse MNIST graphs.

Models and sample graphs will be saved every five epochs in the models and figs directories respectively. FID scores and losses will be saved in the losses directory.