Docs should emphasize loss functions with logits

[dsevero]

I noticed that minimax_discriminator_loss uses binary_cross_entropy_with_logits (cf. binary_cross_entropy) which "combines a Sigmoid layer and the BCELoss" according to the docs.

This is a good practice when it comes to numerical stability, but maybe emphasizing this in the docs would be a good idea to prevent users from inserting a sigmoid as the final non-linearity in custom models. Maybe even raising a warning if we can somehow detect this.