import tensorflow as tf

        self.D_B_loss_real = binary_cross_entropy_loss(tf.ones_like(self.D_B_real),self.D_B_real)
        self.D_B_loss_fake = binary_cross_entropy_loss(tf.zeros_like(self.D_B_fake),self.D_B_fake)
        self.D_B_loss = (self.D_B_loss_real + self.D_B_loss_fake) / 2.0
        
        
        self.D_A_loss_real = binary_cross_entropy_loss(tf.ones_like(self.D_A_real),self.D_A_real)
        self.D_A_loss_fake = binary_cross_entropy_loss(tf.zeros_like(self.D_A_fake),self.D_A_fake)
        self.D_A_loss = (self.D_A_loss_real + self.D_A_loss_fake) / 2.0
        
        self.discriminator_loss = self.D_B_loss + self.D_A_loss
        
        self.loss_GABA_sum = tf.summary.scalar("g_loss_a2b", self.loss_GABA)
