Fix c_gan. (#1333)

fluid/gan/c_gan/c_gan.py

@@ -163,8 +163,9 @@ def train(args):
                 total_images = np.concatenate([real_image, generated_images])
                 fig = plot(total_images)
                 msg = "Epoch ID={0}\n Batch ID={1}\n D-Loss={2}\n DG-Loss={3}\n gen={4}".format(
-                    pass_id, batch_id, np.mean(d_loss_np), dg_loss_np,
-                    check(generated_images))
+                    pass_id, batch_id,
+                    np.sum(d_loss_np),
+                    np.sum(dg_loss_np), check(generated_images))
                 print(msg)
                 plt.title(msg)
                 plt.savefig(

fluid/gan/c_gan/dc_gan.py

@@ -150,7 +150,8 @@ def train(args):
                 fig = plot(total_images)
                 msg = "Epoch ID={0} Batch ID={1} D-Loss={2} DG-Loss={3}\n gen={4}".format(
                     pass_id, batch_id,
-                    np.mean(d_loss_np), dg_loss_np, check(generated_images))
+                    np.sum(d_loss_np),
+                    np.sum(dg_loss_np), check(generated_images))
                 print(msg)
                 plt.title(msg)
                 plt.savefig(

fluid/gan/c_gan/network.py

@@ -101,7 +101,7 @@ def D_cond(image, y):
     h2 = bn(fc(h1, dfc_dim), act='leaky_relu')
     h2 = fluid.layers.concat([h2, y], 1)
 
-    h3 = fc(h2, 1)
+    h3 = fc(h2, 1, act='sigmoid')
     return h3
 
 
@@ -131,7 +131,7 @@ def D(x):
     x = conv(x, df_dim, act='leaky_relu')
     x = bn(conv(x, df_dim * 2), act='leaky_relu')
     x = bn(fc(x, dfc_dim), act='leaky_relu')
-    x = fc(x, 1, act=None)
+    x = fc(x, 1, act='sigmoid')
     return x