RGAN and RCGAN implementation

[dsevero]

I implemented RGAN and RCGAN from [1]. Would it make sense to add it to torchgan.models?

[1] Esteban, Cristóbal, Stephanie L. Hyland, and Gunnar Rätsch. "Real-valued (medical) time series generation with recurrent conditional gans." arXiv preprint arXiv:1706.02633 (2017).

[avik-pal]

@dsevero It seems like an interesting model to have. Go ahead an open a PR for that.

[dsevero]

Great.

Also, this NN is usually used for generating time-series data. As far as I've seen torchgan.trainer.Trainer specializes in images. I had to hack it a bit so that the recon parameter was optional (doesn't make much sense to generate images in my case).

Maybe a new Trainer class is in order? SequenceTrainer?

[avik-pal]

Yes seems a valid thing to do. Ideally, I would like to have a common abstraction of trainer for more variants of GAN but it is not a very simple task. For the time being, we should have a SequenceTrainer.

(I also have thoughts of deprecating the Trainer in this release for an ImageTrainer and completely removing it in a later release)

[dsevero]

That was my next suggestion actually. GANs did focus on image generation in the beginning, but I think it's safe to say that the scenario has changed.

Last thing, what if the user wants to train with the tensors directly instead of a dataloader? This other hack I did (this one looks really really bad) solved it for me, but I think that supporting this directly in torch.trainer.BaseTrainer would make more sense.