# The MIT-Zero License

# Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.

# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so.

# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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# THE SOFTWARE.

import keras
from keras import backend as K


class Loss():
    @staticmethod
    def built_in_softmax_kl_loss(target, output):
        '''
        Custom Loss Function
        :param target: ground truth values
        :param output: predicted values
        :return kullback_leibler_divergence loss
        '''
        target = K.flatten(target)
        output = K.flatten(output)
        target = target / K.sum(target)
        output = K.softmax(output)
        return keras.losses.kullback_leibler_divergence(target, output)