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"]
docstr: Return a slot named `name` created for `var` by
  the underlying MomentumOptimizer.
  
  Args:
    var: A variable passed to `minimize()` or `apply_gradients()`.
    name: A string.
  
  Returns:
    The `Variable` for the slot if it was created, `None` otherwise.
docstr_tok: ["Return","a","slot","named","`","name","`","created","for","`","var","`","by","the","underlying","MomentumOptimizer",".","Args",":","var",":","A","variable","passed","to","`","minimize","(",")","`","or","`","apply_gradients","(",")","`",".","name",":","A","string",".","Returns",":","The","`","Variable","`","for","the","slot","if","it","was","created",",","`","None","`","otherwise","."]
code: def get_slot(self, var, name):
      """
      Return a slot named `name` created for `var` by
      the underlying MomentumOptimizer.
  
      Args:
        var: A variable passed to `minimize()` or `apply_gradients()`.
        name: A string.
  
      Returns:
        The `Variable` for the slot if it was created, `None` otherwise.
      """
      return self._optimizer.get_slot(var, name)
  
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 15 for calling the YFOptimizer obj's underlying member method code with example usage: obj.get_slot(var, name) and returns: self