https://github.com/yairchu/numpy-floats-bug

Chasing after what looks like a strange bug in numpy on M1
https://github.com/yairchu/numpy-floats-bug

Last synced: 23 days ago
JSON representation

Chasing after what looks like a strange bug in numpy on M1

• Host: GitHub
• URL: https://github.com/yairchu/numpy-floats-bug
• Owner: yairchu
• Created: 2024-07-09T08:26:46.000Z (4 months ago)
• Default Branch: main
• Last Pushed: 2024-07-14T18:48:02.000Z (4 months ago)
• Last Synced: 2024-07-15T17:09:10.897Z (4 months ago)
• Language: Assembly
• Size: 13.7 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# numpy bug goose-chase

In this repo I investigated [a bug in numpy](https://github.com/numpy/numpy/issues/26940),

where the same calculation `np.square(vec)` performed again produces different results,

and generally things didn't make sense!

Reproduced on Python 3.12.4 numpy=1.26.4 on macOS 14.4.1 M1 Pro.

Didn't repro for me with numpy==2.0.0, nor on Linux/Windows!

To test on your environment:

```bash

python -m venv venv

venv/bin/python -m pip install -r requirements.txt

venv/bin/python floating_point_determinism_test.py

```

The common output I get looks like this:

```text

INCONSISTENT!

Difference: [2.5243549e-29+0.j 0.0000000e+00+0.j 0.0000000e+00+0.j]

Using  version 1.26.4

```

However with `numpy==2.0.0` the valid output comes and looks like this:

```text

Results are consistent.

Difference: [0.+0.j 0.+0.j 0.+0.j]

Using  version 2.0.0

```