class_docstr: Optimizer that implements the YellowFin algorithm.
  
  See [Zhang et. al., 2017](https://arxiv.org/abs/1706.03471) for details.
docstr: Return a slot named `name` created for `var`.
  
  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","`",".","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`.
  
      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._momentum_optimizer.get_slot(var, name)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow.compat.v1
label_desc: Use image node_id 15 for calling the YellowFinOptimizer obj's underlying member method code with example usage: obj.get_slot(var, name) and returns: self