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Fix VAE losses (sum over everything) #296

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Merged
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Feb 2, 2018
Merged

Fix VAE losses (sum over everything) #296

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9 changes: 3 additions & 6 deletions vae/main.py
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Original file line number Diff line number Diff line change
Expand Up @@ -77,25 +77,22 @@ def forward(self, x):
model = VAE()
if args.cuda:
model.cuda()
optimizer = optim.Adam(model.parameters(), lr=1e-3)


# Reconstruction + KL divergence losses summed over all elements and batch
def loss_function(recon_x, x, mu, logvar):
BCE = F.binary_cross_entropy(recon_x, x.view(-1, 784))
BCE = F.binary_cross_entropy(recon_x, x.view(-1, 784), size_average=False)

# see Appendix B from VAE paper:
# Kingma and Welling. Auto-Encoding Variational Bayes. ICLR, 2014
# https://arxiv.org/abs/1312.6114
# 0.5 * sum(1 + log(sigma^2) - mu^2 - sigma^2)
KLD = -0.5 * torch.sum(1 + logvar - mu.pow(2) - logvar.exp())
# Normalise by same number of elements as in reconstruction
KLD /= args.batch_size * 784

return BCE + KLD


optimizer = optim.Adam(model.parameters(), lr=1e-3)


def train(epoch):
model.train()
train_loss = 0
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