class_docstr: Cosine.
class_docstr_tok: ["Cosine","."]
docstr: See `LearningRateSchedule`.
docstr_tok: ["See","`","LearningRateSchedule","`","."]
code: def apply(self, learning_rate):
      """See `LearningRateSchedule`."""
  
      # Start at -1 since we increment before reading.
      global_step = tf.get_variable(
          "decay_step", initializer=-1, trainable=False
      )
      increment_op = tf.assign_add(global_step, 1)
      with tf.control_dependencies([increment_op]):
          learning_rate = self._decay_fn(
              learning_rate=learning_rate,
              global_step=global_step.read_value(),
          )
      return learning_rate
  
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 2 for calling the Cosine obj's underlying member method code with example usage: obj.apply(learning_rate) and returns: learning_rate