softmax_cross_entropy_with_logits 68
TF supports not needing to have hard labels for cross entropy loss:
logits = [[4.0, 2.0, 1.0], [0.0, 5.0, 1.0]] labels = [[1.0, 0.0, 0.0], [0.0, 0.8, 0.2]] tf.nn.softmax_cross_entropy_with_logits(labels=labels, logits=logits)
Can we do the same thing in Pytorch?