05db9a67c8ec2fe3bc14993b6fc215e336e9d56a,hypergan/train_hooks/experimental/rolling_memory_train_hook.py,RollingMemoryTrainHook,__init__,#RollingMemoryTrainHook#Any#Any#Any#Any#,20

Before Change

        self._lambda = self.gan.configurable_param(config["lambda"])
    else:
        self._lambda = 1.0
    self.mx=tf.Variable(tf.zeros_like(self.gan.inputs.x))
    self.mg=tf.Variable(tf.zeros_like(self.gan.inputs.x))
    self._vlambda = self.gan.configurable_param(config.vlambda or 1.0)
    self.m_discriminator = gan.create_component(gan.config.discriminator, name="discriminator", input=tf.concat([self.mx, self.mg],axis=0), features=[gan.features], reuse=True)

After Change

  def __init__(self, gan=None, config=None, trainer=None, name="RollingMemoryTrainHook"):
    super().__init__(config=config, gan=gan, trainer=trainer, name=name)
    config = hc.Config(config)
    s = self.gan.ops.shape(self.gan.inputs.x)
    self.shape = [self.gan.batch_size() * (self.config.memory_size or 1), s[1], s[2], s[3]]
    self.mx=tf.Variable(tf.zeros(self.shape))
    self.mg=tf.Variable(tf.zeros(self.shape))
    self.m_discriminator = gan.create_component(gan.config.discriminator, name="discriminator", input=tf.concat([self.mx, self.mg],axis=0), features=[gan.features], reuse=True)

Instances