(self, learning_rate, epoch)
return float(learning_rate * self.change ** self.steps)
Returns the current learning rate given the epoch and initial learning rate.

        Arguments:
            learning_rate (float): Initial learning rate
            epoch (int): Current epoch, used to calculate the adjusted learning rate.

        Returns:
            (float): The adjusted learning rate.
Returns the current learning rate given the epoch and initial learning rate.
Returns the current learning rate given the epoch and initial learning rate .
def get_learning_rate(self, learning_rate, epoch):
        """
        Returns the current learning rate given the epoch and initial learning rate.

        Arguments:
            learning_rate (float): Initial learning rate
            epoch (int): Current epoch, used to calculate the adjusted learning rate.

        Returns:
            (float): The adjusted learning rate.
        """
        self.steps = np.floor(epoch / self.step_config)

        return float(learning_rate * self.change ** self.steps)
def get_learning_rate ( self , learning_rate , epoch ) : self . steps = np . floor ( epoch / self . step_config ) return float ( learning_rate * self . change ** self . steps )