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
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