Yes, for torch tensor is pretty clear.
I meant as part of http://pytorch.org/docs/master/torchvision/transforms.html 52 torchvision.transform. So I could for example load mnist using the MNIST loader and automatically iterate over the train_loader such as each element would be batch_size * dimension instead of batch_size * feature_map * height * width.
It seems torchvision package is only provided for convolutional (and it make sense) but I think  could be interesting to have this functionality if you want to train  a fully connected for whatever reason.