Fix indentation to be self-consistent (#279)

* Fix indentation to be self-consistent Replace 2-space with 4-space indentation * Fix indentation to be self-consistent Replace 2-space with 4-space indentation * Fix indentation Replace 3-space indentation with 4-space indentation

Author: justinshenk

vae/main.py

@@ -58,11 +58,11 @@ def encode(self, x):
 
  def reparameterize(self, mu, logvar):
  if self.training:
- std = logvar.mul(0.5).exp_()
- eps = Variable(std.data.new(std.size()).normal_())
- return eps.mul(std).add_(mu)
+  std = logvar.mul(0.5).exp_()
+  eps = Variable(std.data.new(std.size()).normal_())
+  return eps.mul(std).add_(mu)
  else:
- return mu
+  return mu
 
  def decode(self, z):
  h3 = self.relu(self.fc3(z))
@@ -129,10 +129,10 @@ def test(epoch):
  recon_batch, mu, logvar = model(data)
  test_loss += loss_function(recon_batch, data, mu, logvar).data[0]
  if i == 0:
- n = min(data.size(0), 8)
- comparison = torch.cat([data[:n],
+  n = min(data.size(0), 8)
+  comparison = torch.cat([data[:n],
  recon_batch.view(args.batch_size, 1, 28, 28)[:n]])
- save_image(comparison.data.cpu(),
+  save_image(comparison.data.cpu(),
  'results/reconstruction_' + str(epoch) + '.png', nrow=n)
 
  test_loss /= len(test_loader.dataset)
@@ -144,7 +144,7 @@ def test(epoch):
  test(epoch)
  sample = Variable(torch.randn(64, 20))
  if args.cuda:
- sample = sample.cuda()
+  sample = sample.cuda()
  sample = model.decode(sample).cpu()
  save_image(sample.data.view(64, 1, 28, 28),
  'results/sample_' + str(epoch) + '.png')