name scope added

@@ -125,9 +125,10 @@ class DTN(object):
             f_vars = [var for var in t_vars if 'content_extractor' in var.name]
             
             # train op
-            self.d_train_op_src = slim.learning.create_train_op(self.d_loss_src, self.d_optimizer_src, variables_to_train=d_vars)
-            self.g_train_op_src = slim.learning.create_train_op(self.g_loss_src, self.g_optimizer_src, variables_to_train=g_vars)
-            self.f_train_op_src = slim.learning.create_train_op(self.f_loss_src, self.f_optimizer_src, variables_to_train=f_vars)
+            with tf.name_scope('source_train_op'):
+                self.d_train_op_src = slim.learning.create_train_op(self.d_loss_src, self.d_optimizer_src, variables_to_train=d_vars)
+                self.g_train_op_src = slim.learning.create_train_op(self.g_loss_src, self.g_optimizer_src, variables_to_train=g_vars)
+                self.f_train_op_src = slim.learning.create_train_op(self.f_loss_src, self.f_optimizer_src, variables_to_train=f_vars)
             
             # summary op
             d_loss_src_summary = tf.summary.scalar('src_d_loss', self.d_loss_src)
@@ -158,8 +159,9 @@ class DTN(object):
             self.g_optimizer_trg = tf.train.AdamOptimizer(self.learning_rate)
 
             # train op
-            self.d_train_op_trg = slim.learning.create_train_op(self.d_loss_trg, self.d_optimizer_trg, variables_to_train=d_vars)
-            self.g_train_op_trg = slim.learning.create_train_op(self.g_loss_trg, self.g_optimizer_trg, variables_to_train=g_vars)
+            with tf.name_scope('target_train_op'):
+                self.d_train_op_trg = slim.learning.create_train_op(self.d_loss_trg, self.d_optimizer_trg, variables_to_train=d_vars)
+                self.g_train_op_trg = slim.learning.create_train_op(self.g_loss_trg, self.g_optimizer_trg, variables_to_train=g_vars)
             
             # summary op
             d_loss_fake_trg_summary = tf.summary.scalar('trg_d_loss_fake', self.d_loss_fake_trg)