CycleGAN loss function. The individual loss terms are also atrributes of this class that are accessed by fastai for recording during training.
CycleGANLoss(cgan, l_A = 10, l_B = 10, l_idt = 0.5, lsgan = TRUE)The CycleGAN model.
lambda_A, weight of domain A losses. (default=10)
lambda_B, weight of domain B losses. (default=10)
lambda_idt, weight of identity lossees. (default=0.5)
Whether or not to use LSGAN objective (default=True)
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