在这种情况下,我们将使用"generalized dice loss"。这个损失函数的定义如下: classGeneralizedDiceLoss(nn.Module):def__init__(self,num_classes):super(GeneralizedDiceLoss,self).__init__()self.num_classes=num_classesdefforward(self,input,target):smooth=1e-5# 计算每个类别的交叉熵损失loss=F.cross_ent...
👍 1 oke-aditya mentioned this issue Nov 18, 2022 New Feature: Dice Loss pytorch/vision#6435 Open Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment Assignees No one assigned Labels None yet Projects None yet Milestone No milestone ...
torch.Tensor: per batch and per class Generalized Dice Score, i.e., with the shape [batch_size, num_classes]. torch.Tensor: Per batch and per class Generalized Dice Score, i.e., with the shape [batch_size, num_classes]. Raises: ValueError: if `y_pred` or `y` are not PyTorch te...
Returns: torch.Tensor: per batch and per class Generalized Dice Score, i.e., with the shape [batch_size, num_classes]. Raises: ValueError: if `y_pred` or `y` are not PyTorch tensors, if `y_pred` and `y` have less than three dimensions, or `y_pred` and `y` don't have ...