yellowfin.py 文件源码

def update_hyper_param(self):
    assign_hyper_ops = []
    self._mu = tf.identity(tf.cond(
      self._do_tune, lambda: self.get_mu_tensor(),
      lambda: self._mu_var))
    with tf.control_dependencies([self._mu]):
      self._lr = tf.identity(tf.cond(
        self._do_tune, lambda: self.get_lr_tensor(),
        lambda: self._lr_var))

    with tf.control_dependencies([self._mu, self._lr]):
      if self._use_unsmoothed_lr_mu:
        assign_hyper_ops.append(tf.assign(self._mu_var, self._mu) )
        assign_hyper_ops.append(tf.assign(self._lr_var, self._lr) )
      else:
        self._mu = self._beta * self._mu_var + (1 - self._beta) * self._mu
        self._lr = self._beta * self._lr_var + (1 - self._beta) * self._lr
        with tf.control_dependencies([self._mu, self._lr] ):
          assign_hyper_ops.append(tf.assign(self._mu_var, self._mu) )
          assign_hyper_ops.append(tf.assign(self._lr_var, self._lr) )
    assign_hyper_op = tf.group(*assign_hyper_ops)
    return assign_hyper_op