Hi Everyone, I am using numpy on pypy to train a deep neural network. For my workload numpy on pypy is taking twice the time to train as numpy on Cpython. I am using Numpy via cpyext.
I read in the documentation, "Performance-wise, the speed is mostly the same as CPython's NumPy (it is the same code); the exception is that interactions between the Python side and NumPy objects are mediated through the slower cpyext layer (which hurts a few benchmarks that do a lot of element-by-element array accesses, for example)." Is there any way in which I can profile my application to see how much additional overhead cypext layer is adding or is it the numpy via pypy which is slowing down the things. I have tried vmprof, but I couldn't figure out from it how much time cpyext layer is taking. Any help will be highly appreciated. Regards Yash
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