1. torchgan.losses

This losses subpackage is a collection of popular loss functions used in the training of GANS. Currently the following losses are supported:

These losses are tested with the current available trainers. So if you need to implement you custom loss for using with the trainer it is recommended that you subclass the GeneratorLoss and DiscriminatorLoss

1.1. Loss

1.2. Least Squares Loss

1.3. Minimax Loss

1.4. Boundary Equilibrium Loss

1.5. Energy Based Loss

1.6. Wasserstein Loss

1.7. Mutual Information Penalty