GeneratorLoss#
- class deepinv.loss.adversarial.GeneratorLoss(weight_adv=1.0, D=None, device='cpu', **kwargs)[source]#
Bases:
Loss
Base generator adversarial loss.
Override the forward function to call
adversarial_loss
with quantities depending on your specific GAN model. For examples, seeSupAdversarialGeneratorLoss
andUnsupAdversarialGeneratorLoss
See Imaging inverse problems with adversarial networks for formulae.
- Parameters:
weight_adv (float) – weight for adversarial loss, defaults to 1.
D (torch.nn.Module) – discriminator network. If not specified,
D
must be provided in forward(), defaults to None.device (str) – torch device, defaults to
"cpu"
- adversarial_loss(real, fake, D=None)[source]#
Typical adversarial loss in GAN generators.
- Parameters:
real (torch.Tensor) – image labelled as real, typically one originating from training set
fake (torch.Tensor) – image labelled as fake, typically a reconstructed image
D (torch.nn.Module) – discriminator/critic/classifier model. If
None
, thenD
passed from__init__
used. Defaults toNone
.
- Returns:
generator adversarial loss
- Return type:
Examples using GeneratorLoss
:#

Imaging inverse problems with adversarial networks