Try GD

1 files changed, 5 insertions, 1 deletions

diff --git a/cgan.py b/cgan.py
index a34a0e3..d579e33 100755
--- a/cgan.py
+++ b/cgan.py
@@ -141,6 +141,7 @@ class CGAN():
             gen_imgs = self.generator.predict([noise, labels])
 
             # Train the discriminator
+
             d_loss_real = self.discriminator.train_on_batch([imgs, labels], valid*smooth_real)
             d_loss_fake = self.discriminator.train_on_batch([gen_imgs, labels], valid*smooth_fake)
             d_loss = 0.5 * np.add(d_loss_real, d_loss_fake)
@@ -152,7 +153,10 @@ class CGAN():
             # Condition on labels
             sampled_labels = np.random.randint(0, 10, batch_size).reshape(-1, 1)
             # Train the generator
-            g_loss = self.combined.train_on_batch([noise, sampled_labels], valid)
+            if epoch % 3 == 0
+                g_loss = self.combined.train_on_batch([noise, sampled_labels], valid)
+            else:
+                g_loss = 0
 
             # Plot the progress
             #print ("%d [D loss: %f, acc.: %.2f%%] [G loss: %f]" % (epoch, d_loss[0], 100*d_loss[1], g_loss))