examples/dcgan/dcgan.rb in ruby-dnn-1.2.1 vs examples/dcgan/dcgan.rb in ruby-dnn-1.2.2

@@ -127,10 +127,10 @@
     images = @gen.predict(noise)
     y_real = Numo::SFloat.ones(batch_size, 1)
     y_fake = Numo::SFloat.zeros(batch_size, 1)
     @dis.enable_training
     dis_loss = @dis.train_on_batch(x_batch, y_real)
-    dis_loss + @dis.train_on_batch(images, y_fake)
+    dis_loss += @dis.train_on_batch(images, y_fake)
 
     noise = Numo::SFloat.new(batch_size, 20).rand(-1, 1)
     label = Numo::SFloat.cast([1] * batch_size).reshape(batch_size, 1)
     dcgan_loss = train_on_batch(noise, label)