def _init_losses(self):
data_type = torch.cuda.FloatTensor
self.l1_loss = nn.L1Loss().type(data_type)
self.exclusion_loss = ExclusionLoss().type(data_type)
self.freq_grad_loss = FreqGradLoss().type(data_type)
self.binary_loss = BinaryLoss().type(data_type)
self.nonzero_loss = NonZeroLoss().type(data_type)
self.nonzero_mask_loss = NonZeroMaskLoss_v2().type(data_type)
def _init_losses(self):
data_type = torch.cuda.FloatTensor
self.gngc_loss = YIQGNGCLoss().type(data_type)
self.blur_function = StdLoss().type(data_type)
self.gradient_loss = GradientLoss().type(data_type)
self.l1_loss = nn.L1Loss().type(data_type)
self.extended_l1_loss = ExtendedL1Loss().type(data_type)
self.gray_loss = GrayLoss().type(data_type)
self.exclusion_loss = ExclusionLoss().type(data_type)
def _init_losses(self):
data_type = torch.cuda.FloatTensor
self.l1_loss = nn.L1Loss().type(data_type)
self.exclusion_loss = ExclusionLoss().type(data_type)
self.freq_var_loss = FreqVarLoss().type(data_type)
self.mask_var_loss = MaskVarLoss().type(data_type)
self.freq_grad_loss = FreqGradLoss().type(data_type)
self.mask_grad_loss = MaskGradLoss().type(data_type)
self.mask_tc_loss = MaskTCLoss().type(data_type)
self.proj_loss = ProjLoss().type(data_type)
self.binary_loss = BinaryLoss().type(data_type)
self.nonzero_loss = NonZeroLoss().type(data_type)
self.diss_loss = DissLoss().type(data_type)
self.nonzero_mask_loss = NonZeroMaskLoss().type(data_type)
def _init_losses(self):
data_type = torch.cuda.FloatTensor
self.l1_loss = nn.L1Loss().type(data_type)
self.exclusion_loss = ExclusionLoss().type(data_type)
self.gngc_loss = YIQGNGCLoss().type(data_type)
def _init_losses(self):
data_type = torch.cuda.FloatTensor
self.l1_loss = nn.L1Loss().type(data_type)
self.mse_loss = nn.MSELoss().type(data_type)
self.exclusion_loss = ExclusionLoss().type(data_type)
def _init_losses(self):
data_type = torch.cuda.FloatTensor
self.mse_loss = torch.nn.MSELoss().type(data_type)
self.exclusion_loss = ExclusionLoss().type(data_type)
self.blur_loss = StdLoss().type(data_type)