import tensorflow as tf

    self.d_loss_reals.append(self.d_loss_real)
    self.d_loss_fakes.append(self.d_loss_fake)
    self.d_loss_classes.append(self.d_loss_class)
    self.d_losses.append(self.d_loss)
    self.predictions = self.end_points_D_val['predictions']

  def _get_vars_semi_supervised(self):
    t_vars = tf.trainable_variables()
    d_vars = [var for var in t_vars if var.name.startswith('d_')]
    g_vars = [var for var in t_vars if var.name.startswith('g_')]
    for x in d_vars:
      assert x not in g_vars
    for x in g_vars:
      assert x not in d_vars
