On Mon, Jun 11, 2012 at 12:03 AM, James Bergstra <bergs...@iro.umontreal.ca> wrote: > If anyone is interested in my ongoing API & bytecode adventure in why > / how lazy computing could be useful, I've put together a few tiny > hypothetically-runnable examples here: > > https://github.com/jaberg/numba/tree/master/examples > https://github.com/jaberg/numba/blob/master/examples/linear_svm.py > https://github.com/jaberg/numba/blob/master/examples/mcmc.py > > The purpose of the examples is to show how the features of e.g. Theano > and PyMC could be expressed as operators on raw Python code. Perhaps > most importantly of all, these transforms would work together: a PaCal > transform could automatically generate a likelihood function from a > model and data, and then a Theano transform could provide the > parameter gradients required to fit the likelihood. This natural > chaining is a complete PITA when every project uses its own AST. > > That numba fork also includes very sketchy pseudocode of the main work > routines in the numba/ad.py and numba/rv.py files. The linear_svm > example was recently using Theano as a backend. I don't think it works > right now but FWIW it is still close to running. >
For those interested, the linear_svm example works again. -- http://www-etud.iro.umontreal.ca/~bergstrj _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
