sarthak268 / c3vqg-official Goto Github PK

# in /models/iq.py ,
# the error occurs specifically in line 119,

eps = Variable((Normal(torch.zeros_like(mu).cuda(), self.alpha.data.pow(-1))).sample())

# line 82
self.alpha = nn.Parameter(torch.randn(z_size)) # may contain negative values.

# Replace line 119 with:
d = self.alpha.data.pow(-1)
d = torch.nan_to_num(d.clamp(min=1e-4, max=2), 1e-4) # using 2 instead of 1e-4 for replacing nan causes gradient explosion.
eps = Variable((Normal(torch.zeros_like(mu).cuda(), d)).sample())

Time: 1.2242, Epoch [0/15], Step [3470/5748], LR: 0.010000, Center-Loss: 2.8797, KL: 0.4320, I-recon: 0.5033, C-recon: 6.6174, C-cycle: 0.9655, Regularisation: 2.0211
Time: 1.2230, Epoch [0/15], Step [3480/5748], LR: 0.010000, Center-Loss: 20.7928, KL: 2370.2771, I-recon: 0.5432, C-recon: 186.4624, C-cycle: 1.1244, Regularisation: 2.0197
Time: 1.3085, Epoch [0/15], Step [3490/5748], LR: 0.010000, Center-Loss: 35342.1523, KL: 61860.1836, I-recon: 54.0946, C-recon: 491.9528, C-cycle: 1.8422, Regularisation: 2.7531
Time: 1.2436, Epoch [0/15], Step [3500/5748], LR: 0.010000, Center-Loss: 2750158.5000, KL: 20850.5977, I-recon: 4949.4941, C-recon: 1919.1410, C-cycle: 0.9973, Regularisation: 9.3367
Time: 1.3291, Epoch [0/15], Step [3510/5748], LR: 0.010000, Center-Loss: nan, KL: nan, I-recon: nan, C-recon: nan, C-cycle: 17.0083, Regularisation: nan
Time: 1.2298, Epoch [0/15], Step [3520/5748], LR: 0.010000, Center-Loss: nan, KL: nan, I-recon: nan, C-recon: nan, C-cycle: 2.0468, Regularisation: nan
Time: 1.2376, Epoch [0/15], Step [3530/5748], LR: 0.010000, Center-Loss: nan, KL: nan, I-recon: nan, C-recon: nan, C-cycle: 1.9318, Regularisation: nan