@mattip @seiko2plus Do you know where I should add the tests for this?

Do you know where I should add the tests for this?

maybe within [numpy/core/tests/test_cpu_dispatcher.py] (https://github.com/numpy/numpy/blob/main/numpy/core/tests/test_cpu_dispatcher.py) but it will require loading the module in a separate process.

@seiko2plus Is there a preference in NumPy for warnings vs errors? My question here is partially because of the fact that enabling a feature that doesn't exist is not equivalent to disabling a feature that doesn't exist, and so may require different ways of handling the error--a warning for the latter seems appropriate, but in the case of the former, it may be better to throw an error and exit. Thoughts?

@seiko2plus Is there a preference in NumPy for warnings vs errors? My question here is partially because of the fact that enabling a feature that doesn't exist is not equivalent to disabling a feature that doesn't exist, and so may require different ways of handling the error--a warning for the latter seems appropriate, but in the case of the former, it may be better to throw an error and exit. Thoughts?

For reviewers and interested parties, the current PR's behavior regarding errors/warnings:

@magsol,

As long as the error does not affect the workflow of the following procedures, then choosing to raise runtime-warning would make sense. according to Python's warning-doc RuntimeWarning is reserved for warnings about dubious runtime features. maybe ImportWarning would be a better choice since it's ignored by default.
however, the end-user has the upper hand here, since this behavior can be changed during the runtime through module warning, for example, warnings can be treated as errors via:

import os, warnings
os.environ['NPY_DISABLE_CPU_FEATURES'] = 'XXXX'
warnings.simplefilter("error", RuntimeWarning)
import numpy as np

@seiko2plus That's perfect. Thank you!

Tests are missing. For an example of tests that change the environment variables and then run python in a subprocess, see env manipulation in numpy/core/tests/test_cpu_feature.py

I can't reproduce these errors locally. Even when setting up a machine with --cpu-baseline=native correctly, all the tests pass on my end. Wondering if you may have any insights @mattip @seiko2plus

@Micky774, to reproduce this error, you have to disable the dispatch-able features similar to what the smoke test does, for example:

python setup.py build --cpu-baseline=native --cpu-dispatch=none install --user
python runtests.py -n

or just

python runtests.py --cpu-dispatch=none

In general, you have to escape the dispatch tests if __cpu_dispatch__ is equal to None or if it's an empty list.

@Micky774, please let me know when it's ready for review.

@Micky774, please let me know when it's ready for review.

@seiko2plus Should be good now! Thanks for the help :)

@seiko2plus could you take a look? I think the aarch64 failure is systematic and not connected to this PR.