Theano resources • /r/MachineLearning

I've recently switched (from my own custom NN code) to theano and its been a marvel to have the benefits of a flexible optimized graph but I often find its a bit of a black box. It can do a lot of very nice things but I always worry that they might cost me in performance. E.g. is it more efficient to vectors in order to do fewer larger matrix multiplications (e.g. in the units of an LSTM or a GRU) does is the loss in memory locality or shuffling stuff around in memory outweigh the gains of larger matrix multiplications? I still have figured out how to efficiently implement attention with minibatches. I realize I can try to profile and test this stuff (and I do) but I am wondering where people normally go to get this kind of info on theano?