Avoid inplace operators in general tests

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#287 opened on Sep 1, 2024 2 comments 0 reactions 0 assignees View on GitHub

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Assessment

Difficulty: 2/5
Estimated time: 1-3 hours
Newbie friendliness: 42/100

Issue type: Bug
Clarity: Clearly specified
Activity status: Stale
Tech stack: numpy, python
Domain: testing

Research direction

Start at array_api_tests/pytest_helpers.py around line 483 and inspect the generic test that uses an inplace operator. Reproduce the scalar behavior shown in the issue, then run the affected general tests. Done means NumPy scalar implementations no longer fail there while the relevant array API tests still pass.

Written by the indexing model from the issue text.

Description

low priority

numpy returns scalars instead of 0d arrays:

import numpy as np
import array_api_strict as xps

xps.mean(xps.asarray(4, dtype=xps.float32)).__iadd__(1)
np.mean(np.asarray(4, dtype=np.float32)).__iadd__(1)  # AttributeError: 'numpy.float32' object has no attribute '__iadd__'

And this causes errors in unrelated tests since inplace operators are used in more generic tests:
https://github.com/data-apis/array-api-tests/blob/4caff2867c69d5b9b329320319b61c5444bf6f87/array_api_tests/pytest_helpers.py#L483

I don't think using inplace-operators in this case is particularly important and can probably be switched to a normal bitwise or.

xref: https://github.com/numpy/numpy/issues/27305

Dominant language: Python
Stars: 74
Forks: 54
Avg merge: 4h 35m
Merged PRs (30d): 4

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