Proposal: Currently loss is simply one-dimensional tensor. However, in networks like ssd, there are multiple loss functions like regression and classification loss. Currently it is not possible to print both losses (to the best of my knowledge, please correct me if I am wrong). So the proposal is to support multiple outputs with the first output being the loss function to be considered. This would allow to use the other outputs to be printed via callbacks. Same with metrics.
Code to be changed:
In basic_train.py https://github.com/fastai/fastai_v1/blob/master/fastai/basic_train.py#L13, need to add condition to check if multiple outputs get the first output. Similarly next line for metrics.