import tensorflow as tf


            output_propensity_list = []
            for i in range(list_size):
                # Add position information (one-hot vector)
                click_feature = [tf.expand_dims(tf.zeros_like(self.labels[i]) , -1) for _ in range(4*list_size)]
                click_feature[i] = tf.expand_dims(tf.ones_like(self.labels[i]) , -1)
#                 click_feature[list_size:]=[tf.expand_dims(tf.zeros_like(self.labels[i]) , -1) for _ in range(3*list_size)]
                click_feature[list_size:list_size+i] =[tf.expand_dims(self.labels[k] , -1) for k in range(i-1,-1,-1)]
