There isn’t. Generally you take the argmax of these probabilities and that is your prediction. This is how fastai does it. Argmax = highest (before probability) index. Aka the logits.
So for example, my model doesn’t output things that sum to 1. Really they output what we call logits, which are a bunch of positive or negative numbers. In this example my model predicts three classes.
x,_ = dls.train.one_batch()
x will be a batch of data. I will then use raw pytorch to get the model logits:
logits = learn.model(x)
These logits (on a batch of 1) may look like the following:
tensor([[0.4, 10.2, -20.]])
What we then do is perform softmax and argmax to translate this into something comperable.