import tensorflow as tf

        self.g_variables = [var for var in trainable_variables if 'generator' in var.name]
      
        print ('Variable printing start :'  )
        for var in self.d_variables: 
            print(var.name)
            
        self.test_image_A = tf.placeholder(tf.float32,[None, self.image_size,self.image_size,self.input_dim], name='test_A')
        self.test_image_B = tf.placeholder(tf.float32,[None, self.image_size, self.image_size,self.output_c_dim], name='test_B')
        self.saver = tf.train.Saver()
        
        
    def train_network(self):
        
        self.learning_rate = tf.placeholder(tf.float32)
