class_docstr: A learning rate decay schedule interface.
class_docstr_tok: ["A","learning","rate","decay","schedule","interface","."]
docstr: Applies the learning rate decay schedule to the given learning rate.
  
  Args:
    learning_rate: Float `Tensor` learning rate.
  
  Returns:
    Float `Tensor` learning rate with applied decay schedule.
docstr_tok: ["Applies","the","learning","rate","decay","schedule","to","the","given","learning","rate",".","Args",":","learning_rate",":","Float","`","Tensor","`","learning","rate",".","Returns",":","Float","`","Tensor","`","learning","rate","with","applied","decay","schedule","."]
code: def apply(self, learning_rate):
      """Applies the learning rate decay schedule to the given learning rate.
  
      Args:
        learning_rate: Float `Tensor` learning rate.
  
      Returns:
        Float `Tensor` learning rate with applied decay schedule.
      """
  
file_path: adanet/research/improve_nas/trainer/optimizer.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import abc
  import functools
  import tensorflow.compat.v1
label_desc: Use image node_id 1 for calling the LearningRateSchedule obj's underlying member method code with example usage: obj.apply(learning_rate) without return types