fetch_lfw_pairs issue #23750
Description
Describe the bug
On two different machines for exactly same code, I am getting different result.
Steps/Code to Reproduce
from sklearn.datasets import fetch_lfw_pairs
from sklearn.utils import resample
X = fetch_lfw_pairs(
subset="test",
# funneled=False,
# slice_=(slice(0, 250), slice(0, 250)),
resize=1,
color=True
)
n_samples = 1
imgs, y = resample(X.pairs, X.target, n_samples=n_samples, random_state=101)
print(imgs[0][0])Expected Results
Both on both machines should be the same.
Actual Results
Result on Machine 1:
array([[[ 77., 77., 77.],
[ 94., 88., 76.],
[107., 101., 77.],
...,
[159., 124., 97.],
[141., 110., 84.],
[136., 109., 82.]],
[[ 78., 78., 80.],
[108., 101., 91.],
[128., 121., 99.],
...,
[159., 124., 97.],
[151., 120., 94.],
[149., 124., 98.]],
[[ 82., 80., 85.],
[111., 104., 96.],
[130., 122., 103.],
...,
[163., 131., 105.],
[157., 129., 104.],
[159., 138., 110.]],
...,
[[ 27., 27., 27.],
[ 27., 27., 27.],
[ 24., 24., 24.],
...,
[151., 172., 235.],
[142., 163., 228.],
[128., 150., 210.]],
[[ 26., 24., 25.],
[ 33., 33., 33.],
[ 30., 29., 27.],
...,
[150., 171., 236.],
[136., 157., 222.],
[112., 133., 194.]],
[[ 31., 30., 26.],
[ 36., 35., 33.],
[ 37., 36., 34.],
...,
[146., 167., 230.],
[124., 145., 208.],
[ 93., 112., 171.]]], dtype=float32)
Result on Machine 2:
array([[[0. , 0.00392157, 0. ],
[0.00392157, 0.01176471, 0.04705882],
[0.01960784, 0.07450981, 0.16470589],
...,
[0. , 0. , 0. ],
[0. , 0. , 0. ],
[0. , 0. , 0.00392157]],
[[0. , 0. , 0. ],
[0.00392157, 0.01176471, 0.05098039],
[0.01960784, 0.07843138, 0.16862746],
...,
[0. , 0. , 0. ],
[0. , 0. , 0. ],
[0. , 0. , 0.00392157]],
[[0. , 0.00392157, 0. ],
[0.00392157, 0.01568628, 0.05490196],
[0.01568628, 0.07450981, 0.16470589],
...,
[0. , 0. , 0.00392157],
[0. , 0.00392157, 0. ],
[0. , 0.00392157, 0. ]],
...,
[[0. , 0. , 0. ],
[0. , 0. , 0. ],
[0. , 0. , 0. ],
...,
[0. , 0. , 0. ],
[0. , 0. , 0. ],
[0. , 0. , 0. ]],
[[0. , 0. , 0. ],
[0. , 0. , 0. ],
[0. , 0. , 0. ],
...,
[0. , 0. , 0. ],
[0. , 0. , 0. ],
[0. , 0. , 0. ]],
[[0. , 0. , 0. ],
[0. , 0. , 0. ],
[0. , 0. , 0. ],
...,
[0. , 0. , 0. ],
[0. , 0. , 0. ],
[0. , 0. , 0. ]]], dtype=float32)
Versions
Machine 1:
System:
python: 3.8.5 (default, Sep 4 2020, 07:30:14) [GCC 7.3.0]
executable: /home/anks/miniconda3/envs/stealth/bin/python
machine: Linux-5.17.9-1-MANJARO-x86_64-with-glibc2.10
Python dependencies:
pip: 21.2.4
setuptools: 58.0.4
sklearn: 1.0.2
numpy: 1.21.2
scipy: 1.7.3
Cython: 0.29.30
pandas: 1.3.0
matplotlib: 3.5.1
joblib: 1.1.0
threadpoolctl: 3.1.0
Built with OpenMP: True
Machine 2:
System:
python: 3.8.5 | packaged by conda-forge | (default, Sep 24 2020, 16:55:52) [GCC 7.5.0]
executable: /home/aimluser/miniconda3/envs/application_env/bin/python3.8
machine: Linux-4.4.0-042stab145.3-x86_64-with-glibc2.10
Python dependencies:
pip: 22.1.2
setuptools: 62.1.0
sklearn: 1.0.2
numpy: 1.22.3
scipy: 1.8.0
Cython: None
pandas: 1.3.0
matplotlib: 3.5.2
joblib: 1.1.0
threadpoolctl: 3.1.0
Built with OpenMP: True