class_docstr: Cosine-sawtooth-shaped tail that simulates warm restarts.
  
  Creates a cyclic learning rate curve; each cycle is half of a cosine, falling
  from maximum value to minimum value. For motivation and further details, see
  Loshchilov & Hutter (2017) [https://arxiv.org/abs/1608.03983].
docstr: Configures the periodic behavior of this learning rate function.
  
  Args:
    steps_per_cycle: Number of training steps per sawtooth cycle. The
        learning rate will be highest at the start of each cycle, and lowest
        at the end.
    min_value: Minimum value, reached at the end of each cycle.
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code: def __init__(self, steps_per_cycle, min_value=1e-5):
      """Configures the periodic behavior of this learning rate function.
  
      Args:
        steps_per_cycle: Number of training steps per sawtooth cycle. The
            learning rate will be highest at the start of each cycle, and lowest
            at the end.
        min_value: Minimum value, reached at the end of each cycle.
      """
      self._steps_per_cycle = steps_per_cycle
      self._min_value = min_value
  
file_path: trax/trax/supervised/lr_schedules.py
imports: import math
  import gin
  from trax.fastmath import numpy
label_desc: Use image node_id 1 to create a new _CosineSawtoothTail object  with example: obj = _CosineSawtoothTail(steps_per_cycle, min_value)