def METHOD_NAME(self):
    """ Check if the loss has plateaued. """
    # On a cooldown from previous update
    if self.cooldown_counter != 0:
        self.cooldown_counter -= 1
        return False
    loss_list = self.model.loss_list
    if self.mode in ['complex']:
        prev = loss_list[-self.patience: -self.patience//2]
        curr = loss_list[-self.patience//2:]
        prev, curr = np.mean(prev), np.mean(curr)
    elif self.mode in ['pytorch', 'keras']:
        curr = np.min(loss_list[-self.patience:])
        prev = self.best
    elif self.mode in ['mean']:
        curr = np.mean(loss_list[-self.patience:])
        prev = self.best
    if curr < (prev - self.min_delta):
        self.best = curr
        return False
    return True