OpFromGraph is still under development. If you want to use it on GPU, the safest way would be setting inline=True at constructor (requires 0.9rc1+). This will cause more compilation time though. Or you can try constructing a GPU only graph by hand and build OfG with that, I didn't test that though.
Yes, a shared variable is "global" in OfG, much like a static variable in a C function. Using one OfG op to make multiple Apply nodes would use the same shared variable. If you want separate shared variables, you should define them outside OfG, and use pure symbolic graph inside OfG. On Wednesday, March 22, 2017 at 10:43:09 PM UTC+8, Šarūnas S. wrote: > > I have been trying to train an NN with little success and started > wondering whether all instances of OpFromGraph share the underlying shared > variables. Ie. when doing gradient updates - are my gradients wrt shared > variables computed over all OpFromGraph nodes or is it done only locally > within each OpFromGraph instance? > > I would welcome if someone could elaborate on this since the documentation > on OpFromGraph is very sparse. > > On Friday, 17 March 2017 10:29:16 UTC+2, Šarūnas S. wrote: >> >> I am building a reinforcement learner and I am wondering how to scale it. >> >> At first I initialised a deep neural network in Keras and convert it to >> theano computational graph which takes state variables as inputs and >> outputs an action to make. >> Then, I wrote a simulator in Theano where at decision points I >> theano.clone the DNN computational graph. Lastly, I do gradient descent on >> the DNN parameters in order to get a "good" DNN AI. If I use a proper DNN >> with many layers and parameters the compilation takes forever and >> iterations are very slow. >> >> Then I've tried using OpFromGraph. It seems to reduce my compilation time >> quite a bit. However, once I looked at the computational graph it seems >> that OpFromGraph moves everything back to the CPU. >> >> Given that the op is a DNN which are very GPU friendly I wonder whether >> there is a way to avoid that? >> >> Please find my graph at >> https://drive.google.com/open?id=0BzjH-3p3dTNzWU8zS05wMU5STEk >> >> -- --- You received this message because you are subscribed to the Google Groups "theano-users" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. For more options, visit https://groups.google.com/d/optout.
