Lluís writes:
> Francesc Alted writes:
>> On Feb 20, 2012, at 6:18 PM, Dag Sverre Seljebotn wrote:
>>> You need at least a slightly different Python API to get anywhere, so
>>> numexpr/Theano is the right place to work on an implementation of this
>>> idea. Of course it would be nice if numexpr/Theano offered something as
>>> convenient as
>>>
>>> with lazy:
>>> arr = A + B + C # with all of these NumPy arrays
>>> # compute upon exiting…
>> Hmm, that would be cute indeed. Do you have an idea on how the code in the
>> with
>> context could be passed to the Python AST compiler (à la numexpr.evaluate("A
>> + B
>> + C"))?
> Well, I started writing some experiments to "almost transparently" translate
> regular ndarray operations to numexpr strings (or others) using only python
> code.
[...]
> My target was to use this to also generate optimized GPU kernels in-flight
> using
> pycuda, but I think some other relatively recent project already performed
> something similar (w.r.t. generating cuda kernels out of python expressions).
Aaahhh, I just had a quick look at Theano and it seems it's the project I was
referring to.
Good job! :)
Lluis
--
"And it's much the same thing with knowledge, for whenever you learn
something new, the whole world becomes that much richer."
-- The Princess of Pure Reason, as told by Norton Juster in The Phantom
Tollbooth
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