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 <m...@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-le...@python.org > https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ > Member address: michael.sieber...@gmail.com
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