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NumPy compiler warnings on Windows #54
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Testing with the command from the PyMC Installation Guide (WIndows)
And reproducing with a minimal env:
I compared the So the problem was introduced in aesara-devs/aesara@rel-2.3.3...rel-2.3.4 Upon further investigation it looks like I don't see performance differences between Still, the question remains if these prints are indicative of broken dependencies (and should be fixed via the feedstock), or if they are practically irrelevant and should be hidden. |
Doesn't a Windows installation require an additional Conda package like Aside from that, the warnings you're seeing look like the ones emitted by something like Regardless, it looks like the environments you're using/creating do not have build toolchains that NumPy and—as a result—Aesara can recognize/use. |
Including
mamba logs
Yes, they are created by logging, with the WARNING level. I do not tweak my local
Same with the NumPy build toolchains. What's the point of installing Aesara through conda-forge if it doesn't do a better job than pip when it comes to installing performance-relevant build dependencies? |
There was a post on Discourse where a one-liner setting in https://discourse.pymc.io/t/pymc-installation-issue/9279/5 @brandonwillard is that a sensible solution? And if so, could it become the default? |
Yeah, something like that could work. @dgerlanc has been looking into the Mac compilation issues; he might have precision answers to a few common Mac + architecture cases, as well. |
To clarify, this is essentially two issues:
This can be resolved by installing |
Part 1 as explained in #54 (comment) seems to have been solved in the main branch by aesara-devs/aesara#1050. Part 2 has been solved in the latest releases via the So it seems to me like the next Aesara release will close this issue. 🚀 |
Yes, the measures were taken in several places, I think we can close the issue already. |
Solution to issue cannot be found in the documentation.
Issue
Even fresh, minimal environments on Windows have a broken compiler toolchain, rendering them completely unusable.
This command creates a small environment:
conda create -n aesara-test -c conda-forge python=3.9 aesara -y
Upon
import aesara
there are lots of errors and warnings:At first I thought this was just one environment, but the problem appears in all new environments I create. And I'm running out of non-broken old environments to fall back to 😬
With these broken environments, doing a posterior predictive sampling with a GP is about 100x slower than in non-broken envs.
Installed packages
Environment info
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