For the loss, I am choosing nn.CrossEntropyLoss() in PyTOrch, which (as I have found out) does not want to take one-hot encoded labels as true ... ... <看更多>

CrossEntropyLoss.html The CrossEntropyLoss from pytorch combin. ... /should-i-use-softmax-as-output-when-using-cross-entropy-loss-in-pytorch. ... <看更多>

You need to make sure to have two neurons in the final layer of the model. Make sure that you do not add a softmax function. Use the below for resources: https ... ... <看更多>

It is a Softmax activation plus a Cross-Entropy loss. ... Caffe: Sigmoid Cross-Entropy Loss Layer; Pytorch: BCEWithLogitsLoss ... ... <看更多>