최강혁 / dddd

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yunjey
eaa2d5ec 1 parent 4e56e6dc

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Showing 1 changed file with 7 additions and 5 deletions
...@@ -125,9 +125,10 @@ class DTN(object): ...@@ -125,9 +125,10 @@ class DTN(object):
125 f_vars = [var for var in t_vars if 'content_extractor' in var.name] 125 f_vars = [var for var in t_vars if 'content_extractor' in var.name]
126 126
127 # train op 127 # train op
128 - self.d_train_op_src = slim.learning.create_train_op(self.d_loss_src, self.d_optimizer_src, variables_to_train=d_vars) 128 + with tf.name_scope('source_train_op'):
129 - self.g_train_op_src = slim.learning.create_train_op(self.g_loss_src, self.g_optimizer_src, variables_to_train=g_vars) 129 + self.d_train_op_src = slim.learning.create_train_op(self.d_loss_src, self.d_optimizer_src, variables_to_train=d_vars)
130 - self.f_train_op_src = slim.learning.create_train_op(self.f_loss_src, self.f_optimizer_src, variables_to_train=f_vars) 130 + self.g_train_op_src = slim.learning.create_train_op(self.g_loss_src, self.g_optimizer_src, variables_to_train=g_vars)
131 + self.f_train_op_src = slim.learning.create_train_op(self.f_loss_src, self.f_optimizer_src, variables_to_train=f_vars)
131 132
132 # summary op 133 # summary op
133 d_loss_src_summary = tf.summary.scalar('src_d_loss', self.d_loss_src) 134 d_loss_src_summary = tf.summary.scalar('src_d_loss', self.d_loss_src)
...@@ -158,8 +159,9 @@ class DTN(object): ...@@ -158,8 +159,9 @@ class DTN(object):
158 self.g_optimizer_trg = tf.train.AdamOptimizer(self.learning_rate) 159 self.g_optimizer_trg = tf.train.AdamOptimizer(self.learning_rate)
159 160
160 # train op 161 # train op
161 - self.d_train_op_trg = slim.learning.create_train_op(self.d_loss_trg, self.d_optimizer_trg, variables_to_train=d_vars) 162 + with tf.name_scope('target_train_op'):
162 - self.g_train_op_trg = slim.learning.create_train_op(self.g_loss_trg, self.g_optimizer_trg, variables_to_train=g_vars) 163 + self.d_train_op_trg = slim.learning.create_train_op(self.d_loss_trg, self.d_optimizer_trg, variables_to_train=d_vars)
164 + self.g_train_op_trg = slim.learning.create_train_op(self.g_loss_trg, self.g_optimizer_trg, variables_to_train=g_vars)
163 165
164 # summary op 166 # summary op
165 d_loss_fake_trg_summary = tf.summary.scalar('trg_d_loss_fake', self.d_loss_fake_trg) 167 d_loss_fake_trg_summary = tf.summary.scalar('trg_d_loss_fake', self.d_loss_fake_trg)
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