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Theano and the Future of PyMC
- kirillseva 9y agoAnother lesson about the dangers of relying on a separate team to maintain core part of your software. Not that using dependencies is a bad thing, but one should still be aware of what tradeoff they are making. In terms of a new backend, there's uber's pyro [1] that's based on pytorch, and then there's Edward [2] that's based on tensorflow (and I think recently got integrated into tensorflow repo). Would be interesting to see pyMC adopt MXNet as its backend. I'm sure Amazon will become a heavy user and might sponsor the development. Or at least the authors will be able to get jobs there without a whiteboarding interview phase. [1] https://github.com/uber/pyro https://github.com/uber/pyro [2] http://edwardlib.org/ http://edwardlib.org/
- sirfz 9y agoOur team migrated from Theano to Tensorflow more than a year ago and the transition was pretty natural as both frameworks share very similar design philosophies. I never used PyMC myself, but Tensorflow seems like the natural replacement in this case.
- LeoJiWoo 9y agoThat's unfortunate. I used theano for some voter analysis projects, that some friends needed. I liked it quite a bit.
- bagrow 9y agoIt's probably not as easy a swap as tensorflow, but stan would be a natural fit for bayesian inference, and its NUTS sampler should be very performant. http://mc-stan.org http://mc-stan.org
- Fede_V 9y agoFor experimenting, I think the imperative paradigm (define the graph by running it) makes for much faster experimentation and requires a lot less boilerplate code. All big DL frameworks (TF, PyTorch, MXNet, Chainer) are now either imperative or have an imperative API in the works.