import tensorflow as tf

                                            scale=True,
                                            is_training=(mode=='train'),
                                            updates_collections=None,
                                            scope=(name+'batch_norm'))

    def build_model(self):
        features = self.features
        captions = self.captions
        batch_size = tf.shape(features)[0]

        captions_in = captions[:, :self.T]      
        captions_out = captions[:, 1:]  
        mask = tf.to_float(tf.not_equal(captions_out, self._null))
        
        
        # batch normalize feature vectors
