def _decay_learning_rate(self, global_step, end_learning_rate, decay_steps):
    '\n        Applies a square-root decay to the learning rate.\n\n        :param global_step: Global step to use for the decay computation.\n        :type global_step: `int`\n        :param end_learning_rate: The minimal end learning rate.\n        :type end_learning_rate: `float`\n        :param decay_steps: Number of decayed steps.\n        :type decay_steps: `int`\n        :return: The decayed learning rate\n        :rtype: `float`\n        '
    decayed_learning_rate = (((self.learning_rate - end_learning_rate) * ((1 - (global_step / decay_steps)) ** 2)) + end_learning_rate)
    return decayed_learning_rate
Applies a square-root decay to the learning rate.

:param global_step: Global step to use for the decay computation.
:type global_step: `int`
:param end_learning_rate: The minimal end learning rate.
:type end_learning_rate: `float`
:param decay_steps: Number of decayed steps.
:type decay_steps: `int`
:return: The decayed learning rate
:rtype: `float`
def _decay_learning_rate(self, global_step, end_learning_rate, decay_steps):
    '\n        Applies a square-root decay to the learning rate.\n\n        :param global_step: Global step to use for the decay computation.\n        :type global_step: `int`\n        :param end_learning_rate: The minimal end learning rate.\n        :type end_learning_rate: `float`\n        :param decay_steps: Number of decayed steps.\n        :type decay_steps: `int`\n        :return: The decayed learning rate\n        :rtype: `float`\n        '
    decayed_learning_rate = (((self.learning_rate - end_learning_rate) * ((1 - (global_step / decay_steps)) ** 2)) + end_learning_rate)
    return decayed_learning_rate