(self, step_number, tail_start, body_value)
return min_value + (max_value - min_value) * .5 * (1 + math.cos(theta))
Returns the learning rate for the given step number, when in the tail.

    Args:
      step_number: Absolute step number from the start of training.
      tail_start: Step number at which the tail of the curve starts.
      body_value: Value relative to which the tail should be computed.
Returns the learning rate for the given step number, when in the tail.
Returns the learning rate for the given step number when in the tail .
def __call__(self, step_number, tail_start, body_value):
    """Returns the learning rate for the given step number, when in the tail.

    Args:
      step_number: Absolute step number from the start of training.
      tail_start: Step number at which the tail of the curve starts.
      body_value: Value relative to which the tail should be computed.
    """
    max_value = body_value
    min_value = self._min_value
    position_in_cycle = (
        ((step_number - tail_start) / self._steps_per_cycle) % 1.0)
    theta = math.pi * position_in_cycle
    return min_value + (max_value - min_value) * .5 * (1 + math.cos(theta))
def __call__ ( self , step_number , tail_start , body_value ) : max_value = body_value min_value = self . _min_value position_in_cycle = ( ( ( step_number - tail_start ) / self . _steps_per_cycle ) % 1.0 ) theta = math . pi * position_in_cycle return min_value + ( max_value - min_value ) * .5 * ( 1 + math . cos ( theta ) )