How to use the torchgan.losses.functional.auxiliary_classification_loss function in torchgan
To help you get started, we’ve selected a few torchgan examples, based on popular ways it is used in public projects.
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torchgan / torchgan / torchgan / losses / auxclassifier.py View on Github 
def forward(self, logits, labels):
return auxiliary_classification_loss(logits, labels, self.reduction)def forward(self, logits, labels):
return auxiliary_classification_loss(logits, labels, self.reduction)torchgan
Research Framework for easy and efficient training of GANs based on Pytorch
Package Health Score
45 / 100Popular torchgan functions
- torchgan.logging.logger.Logger
- torchgan.logging.visualize.Visualize
- torchgan.losses.functional.auxiliary_classification_loss
- torchgan.losses.functional.boundary_equilibrium_discriminator_loss
- torchgan.losses.functional.dragan_gradient_penalty
- torchgan.losses.functional.energy_based_pulling_away_term
- torchgan.losses.functional.minimax_discriminator_loss
- torchgan.losses.functional.minimax_generator_loss
- torchgan.losses.functional.mutual_information_penalty
- torchgan.losses.functional.wasserstein_gradient_penalty
- torchgan.losses.loss.DiscriminatorLoss
- torchgan.losses.loss.GeneratorLoss
- torchgan.models.AutoEncodingDiscriminator
- torchgan.models.dcgan.DCGANDiscriminator
- torchgan.models.dcgan.DCGANGenerator
- torchgan.models.model.Discriminator
- torchgan.models.model.Generator
- torchgan.trainer.Trainer
- torchgan.utils.getenv_defaults
- torchgan.utils.reduce