def build_loss(self): with tf.name_scope('Loss'): g_loss, d_loss = loss_wgan(*self.d_outputs) with tf.variable_scope(self.name, reuse=True): gp = gradient_penalty(*self.g_outputs, self.D, lamb=10) d_loss += gp self._build_loss(g_loss, d_loss)
def build_loss(self): with tf.name_scope('Loss'): g_loss, d_loss = loss_relative_bce_gan(*self.d_outputs, average=True) with tf.variable_scope(self.name, reuse=True): gp = gradient_penalty(*self.g_outputs, graph_fn=self.D, lamb=10) d_loss += gp self._build_loss(g_loss, d_loss)