Python torch.nn 模块，NLLLoss2d() 实例源码

def __init__(self, weight=None):
        super(CrossEntropyLoss2d,self).__init__()

        self.loss = nn.NLLLoss2d(weight)

def log_loss(loss_weight=None, size_ave=True, dim=2):

    if dim == 1:
        return nn.NLLLoss(weight=loss_weight,size_average=size_ave)
    elif dim == 2:
        return nn.NLLLoss2d(weight=loss_weight,size_average=size_ave)

def __init__(self, weight=None, size_average=True, ignore_index=255):
        super(CrossEntropyLoss2d, self).__init__()
        self.nll_loss = nn.NLLLoss2d(weight, size_average, ignore_index)

def __init__(self, gamma=2, weight=None, size_average=True, ignore_index=255):
        super(FocalLoss2d, self).__init__()
        self.gamma = gamma
        self.nll_loss = nn.NLLLoss2d(weight, size_average, ignore_index)

def __init__(self, size_average=True):
        super(CrossEntropyLoss2D, self).__init__()
        self.nll_loss_2d = nn.NLLLoss2d(size_average=size_average)

def __init__(self, weights, size_average=True):
        super(MSCrossEntropyLoss2D, self).__init__()
        self.nll_loss_2d = nn.NLLLoss2d(size_average=size_average)
        self.weights = weights

def __init__(self, weight=None):
        super().__init__()
        self.loss = nn.NLLLoss2d(weight)

def __init__(self, weight=None):
        super().__init__()
        self.loss = nn.NLLLoss2d(weight)

def __init__(self, weight=None):
        super().__init__()
        self.loss = nn.NLLLoss2d(weight)

def __init__(self, weight=None):
        super().__init__()
        self.loss = nn.NLLLoss2d(weight)

def __init__(self, weight=None):
        super().__init__()
        self.loss = nn.NLLLoss2d(weight)

def __init__(self, weight=None):
        super(CrossEntropyLoss2d,self).__init__()

        self.loss = nn.NLLLoss2d(weight)