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)