Hi all, in PyTorch they (kind of) recently introduced torch.compile: https://pytorch.org/tutorials/intermediate/torch_compile_tutorial.html In TensorFlow, eager execution needs to be activated manually, otherwise it creates a graph object which then acts like this kind of pipe. Don‘t know whether that‘s useful info for an implementation in Numpy. I‘m just referring to what I think may be similar to pipes in other Numpy-like frameworks. Best, Michael
On 15. Feb 2024, at 22:13, Marten van Kerkwijk <mhvk@astro.utoronto.ca> wrote:
What were your conclusions after experimenting with chained ufuncs?
If the speed is comparable to numexpr, wouldn’t it be `nicer` to have non-string input format?
It would feel a bit less like a black-box.
I haven't gotten further than it yet, it is just some toying around I've been doing. But I'd indeed prefer not to go via strings -- possibly numexpr could use a similar mechanism to what I did to construct the function that is being evaluated.
Aside: your suggestion of the pipe led to some further discussion at https://github.com/numpy/numpy/issues/25826#issuecomment-1947342581 -- as a more general way of passing arrays to functions.
-- Marten _______________________________________________ NumPy-Discussion mailing list -- numpy-discussion@python.org To unsubscribe send an email to numpy-discussion-leave@python.org https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ Member address: michael.siebert2k@gmail.com