Earlier quoted context omitted.
That’s a fairly aggressive response. Both TF and Theano require static graph while PyTorch lets you use Python’s regular control flows (if, for, while, etc). This makes building modular model components much easier, since you can reason about execution mostly as if it’s normal numerical Python code. I have tried running PyMC3 models on GPUs (when they were on Theano; not sure if they have transitioned since) and it i…
> “I have tried running PyMC3 models on GPUs (when they were on Theano; not sure if they have transitioned since) and it is slower than CPUs, not for small models but the big, SIMD-wide ones.“ Can you post a link to your code with some synthetic data of the sizes you’re talking about to demonstrate this? I hear it as a criticism a lot, but have never found it to be true (full disclosure: I work on a large-scale produ…
I don’t have pymc code anymore since we have moved to Stan, and now starting porting code to Pyro.
> forgive the parts that are bad about it (like needing to explicitly write a wrapper for the backwards calculation for custom layers
Why do that when AD does it for you?