import torch as t


def multilabelloss():
    return t.nn.MultiLabelSoftMarginLoss()


def multilabel_marginloss():
    return t.nn.MultiLabelMarginLoss()


def bceloss():
    return t.nn.BCELoss()


def weight_loss():
    pass


def identityloss():


    class Loss:

        def __call__(self, x):
            return x
    return Loss()

8a5b5a779a7cb60fe92181d4d155c9b3dd657da5
<mask token>


def bceloss():
    return t.nn.BCELoss()


<mask token>


def identityloss():


    class Loss:

        def __call__(self, x):
            return x
    return Loss()

<mask token>


def multilabelloss():
    return t.nn.MultiLabelSoftMarginLoss()


<mask token>


def bceloss():
    return t.nn.BCELoss()


def weight_loss():
    pass


def identityloss():


    class Loss:

        def __call__(self, x):
            return x
    return Loss()

<mask token>


def multilabelloss():
    return t.nn.MultiLabelSoftMarginLoss()


def multilabel_marginloss():
    return t.nn.MultiLabelMarginLoss()


def bceloss():
    return t.nn.BCELoss()


def weight_loss():
    pass


def identityloss():


    class Loss:

        def __call__(self, x):
            return x
    return Loss()

import torch as t


def multilabelloss():
    return t.nn.MultiLabelSoftMarginLoss()


def multilabel_marginloss():
    return t.nn.MultiLabelMarginLoss()


def bceloss():
    return t.nn.BCELoss()


def weight_loss():
    pass


def identityloss():


    class Loss:

        def __call__(self, x):
            return x
    return Loss()
