5ee0f6c5fc31124eddffedddb7c2ce816dd329c8,hypergan/train_hooks/gradient_penalty_train_hook.py,GradientPenaltyTrainHook,__init__,#GradientPenaltyTrainHook#Any#Any#Any#Any#Any#Any#,19

Before Change

    gd = tf.gradients(target, target_vars)
    gds = [tf.square(tf.norm(_gd, ord=2)) for _gd in gd if _gd is not None]
    r = tf.add_n(gds)
    self.d_loss = self.d_lambda * tf.reduce_mean(r)
    self.gan.add_metric("gp", self.d_loss)

  def losses(self):

After Change

    if self.config.target:
        v = getattr(gan, self.config.target)
        target = v.sample
        if "components" in self.config:
            target_vars = []
            for component in self.config.components:
                c = getattr(gan, component)
                target_vars += c.variables()
        else:
            target_vars = v.variables()

    gd = tf.gradients(target, target_vars)
    gds = [tf.square(_gd) for _gd in gd if _gd is not None]
    self.loss = tf.add_n([self.d_lambda * tf.reduce_mean(_r) for _r in gds])
    self.gds = gds

Instances