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thanks for the great work. I see that the loss of the netwok is a self implemented binary cross entropy loss parameterized by class weights. (I guess the weights are used to adress the imbalanced data labels?). I read the code in main.py, but I didn't see the weights take part in any computation -(target*torch.log(input+eps)+(1-target)*torch.log(1-input+eps))
Would this be updated later? Thanks
The text was updated successfully, but these errors were encountered:
thanks for the great work. I see that the loss of the netwok is a self implemented binary cross entropy loss parameterized by class weights. (I guess the weights are used to adress the imbalanced data labels?). I read the code in main.py, but I didn't see the weights take part in any computation
-(target*torch.log(input+eps)+(1-target)*torch.log(1-input+eps))
Would this be updated later? Thanks
The text was updated successfully, but these errors were encountered: