Hey all, I'm investigating an idea and it's gotten to the point that I'd like to solicit feedback. The idea is to use Theano or TensorFlow to accelerate existing NumPy programs. The technical challenges here are pretty daunting, but I feel like I have a decent understanding of its feasibility (I have a prototype that I think is promising). The other side of the equation is how valuable this would be. The potential benefits seem very compelling (cross-op optimizations, GPU and distributed execution "for free"), and I've heard a lot of people ask for better NumPy performance. The worrying thing, though, is that I haven't been able to find anyone willing to share their code or workflow. Not that I'm blaming anyone, but that situation makes me worried about the demand for something like this.
So, what do you think, would this be valuable or useful? Is it worth putting more time into this? Or will it be just another NumPy accelerator that doesn't get used? If you have any thoughts, or want to chime in about your experiences with NumPy performance, I'd definitely be interested to hear about it in the comments.