CycleGANLoss: CycleGANLoss

Description Usage Arguments Details

View source: R/cycleGAN_models.R

Description

CycleGAN loss function. The individual loss terms are also atrributes of this class that are accessed by fastai for recording during training.

Usage

1
CycleGANLoss(cgan, l_A = 10, l_B = 10, l_idt = 0.5, lsgan = TRUE)

Arguments

cgan

The CycleGAN model.

l_A

lambda_A, weight of domain A losses. (default=10)

l_B

lambda_B, weight of domain B losses. (default=10)

l_idt

lambda_idt, weight of identity lossees. (default=0.5)

lsgan

Whether or not to use LSGAN objective (default=True)

Details

Attributes: 'self.cgan' ('nn.Module'): The CycleGAN model. 'self.l_A' ('float'): lambda_A, weight of domain A losses. 'self.l_B' ('float'): lambda_B, weight of domain B losses. 'self.l_idt' ('float'): lambda_idt, weight of identity lossees. 'self.crit' ('AdaptiveLoss'): The adversarial loss function (either a BCE or MSE loss depending on 'lsgan' argument) 'self.real_A' and 'self.real_B' ('fastai.torch_core.TensorImage'): Real images from domain A and B. 'self.id_loss_A' ('torch.FloatTensor'): The identity loss for domain A calculated in the forward function 'self.id_loss_B' ('torch.FloatTensor'): The identity loss for domain B calculated in the forward function 'self.gen_loss' ('torch.FloatTensor'): The generator loss calculated in the forward function 'self.cyc_loss' ('torch.FloatTensor'): The cyclic loss calculated in the forward function


fastai documentation built on July 28, 2021, 5:06 p.m.