Class Model

examples/GAN/WGAN.py:23–47

class Model(DCGAN.Model):
    # def generator(self, z):
    # you can override generator to remove BatchNorm, it will still work in WGAN

    def build_losses(self, vecpos, vecneg):
        # the Wasserstein-GAN losses
        self.d_loss = tf.reduce_mean(vecneg - vecpos, name='d_loss')
        self.g_loss = tf.negative(tf.reduce_mean(vecneg), name='g_loss')
        add_moving_summary(self.d_loss, self.g_loss)

    def optimizer(self):
        opt = tf.train.RMSPropOptimizer(1e-4)
        return opt

        # An alternative way to implement the clipping:
        """
        from tensorpack.tfutils import optimizer
        def clip(v):
            n = v.op.name
            if not n.startswith('discrim/'):
                return None
            logger.info("Clip {}".format(n))
            return tf.clip_by_value(v, -0.01, 0.01)
        return optimizer.VariableAssignmentOptimizer(opt, clip)
        """


class ClipCallback(Callback):