Implicit dimension choice for softmax warning

[Mona_Jalal]

Thanks for your response. It is part of an older code for focal loss here:

        logpt = F.log_softmax(input)

Logpt = logpt.gather(1,target) IndexError: Dimension out of range (expected to be in range of [-1, 0], but got 1)

I found this implementation of focal loss in GitHub and I am using it for an imbalanced dataset binary classification problem. # IMPLEMENTATION CREDIT: https://github.com/clcarwin/focal_loss_pytorch class FocalLoss(nn.Module): def __init__(self, gamma=0.5, alpha=None, size_average=True): super(FocalLoss, self).__init__() self.gamma = gamma self.alpha = alpha if isinstance(alpha,(float,int)): self.alpha = torch.Tensor([alpha,1-alpha]) if isinstance…