global step in optimizer

answer_classifier_cached_features/train.py

@@ -705,7 +705,9 @@ class attach_optimizer():
                 vars_to_train,
                 learning_rate = self.learning_rate)
 
-            self.train_op = self.optimizer.minimize(graph.total_loss)
+            self.train_op = self.optimizer.minimize(
+                graph.total_loss,
+                self.global_step)
                 
             # self.add_adam_optimizer(
             #     graph.total_loss,
@@ -854,6 +856,8 @@ class log_mgr():
                 eval_vars_dict['per_region_answer_prob'].shape)
             print np.max(eval_vars_dict['per_region_answer_prob'])
 
+            print 'Learning Rate: {}'.format(eval_vars_dict['lr'])
+
         if (iter % self.log_every_n_iter==0 or is_last) and (iter!=0):
             self.model_saver.save(
                 self.sess, 
@@ -956,6 +960,7 @@ if __name__=='__main__':
         'answer_scores': graph.answer_inference.answer_score[0],
         'accuracy': graph.moving_average_accuracy,
         'total_loss': graph.total_loss,
+        'lr': optimizer.learning_rate,
         # 'question_embed_concat': graph.question_embed_concat,
         # 'answer_embed_concat': graph.answers_embed_concat,
         # 'noun_embed': graph.noun_embed['positive_nouns'],