class_docstr: Optimizer that implements the YellowFin algorithm.
  
  Implemented as a wrapper around tf.train.MomentumOptimizer
class_docstr_tok: ["Optimizer","that","implements","the","YellowFin","algorithm",".","Implemented","as","a","wrapper","around","tf.train.MomentumOptimizer"]
code: 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
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import delta.compat
  from tensorflow.python.framework import ops
label_desc: Use image node_id 10 for calling the YFOptimizer obj's underlying member method code with example usage: obj.update_hyper_param() and returns: assign_hyper_op