BUG: ufuncs created with np.frompyfunc do not recognize identity in reduce in numpy 1.25.X #24530
Description
Describe the issue:
Starting in numpy 1.25.0, it appears that the ufunc.reduce method does not recognize the identity argument for ufuncs created with np.frompyfunc
Reproduce the code example:
import numpy as np
import operator
print(np.__version__)
x = np.arange(10)
mask = x % 2 == 0
print(np.add.reduce(x, where=mask))
my_add = np.frompyfunc(operator.add, nin=2, nout=1, identity=0)
print(my_add.reduce(x, where=mask))Error message:
Result in numpy 1.24.4:
1.24.4
20
20Result in numpy 1.25.0:
1.25.0
20---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
[<ipython-input-7-a7d31df3c91a>](https://localhost:8080/#) in <cell line: 11>()
9
10 my_add = np.frompyfunc(operator.add, nin=2, nout=1, identity=0)
---> 11 print(my_add.reduce(x, where=mask))
ValueError: reduction operation 'add (vectorized)' does not have an identity, so to use a where mask one has to specify 'initial'Runtime information:
>>> import sys, numpy; print(numpy.__version__); print(sys.version)
1.25.0
3.10.12 (main, Jun 11 2023, 05:26:28) [GCC 11.4.0]
>>> print(numpy.show_runtime())
[{'numpy_version': '1.25.0',
'python': '3.10.12 (main, Jun 11 2023, 05:26:28) [GCC 11.4.0]',
'uname': uname_result(system='Linux', node='e87715ee78c7', release='5.15.109+', version='#1 SMP Fri Jun 9 10:57:30 UTC 2023', machine='x86_64')},
{'simd_extensions': {'baseline': ['SSE', 'SSE2', 'SSE3'],
'found': ['SSSE3',
'SSE41',
'POPCNT',
'SSE42',
'AVX',
'F16C',
'FMA3',
'AVX2'],
'not_found': ['AVX512F',
'AVX512CD',
'AVX512_KNL',
'AVX512_KNM',
'AVX512_SKX',
'AVX512_CLX',
'AVX512_CNL',
'AVX512_ICL']}},
{'architecture': 'Haswell',
'filepath': '/usr/local/lib/python3.10/dist-packages/numpy.libs/libopenblas64_p-r0-7a851222.3.23.so',
'internal_api': 'openblas',
'num_threads': 2,
'prefix': 'libopenblas',
'threading_layer': 'pthreads',
'user_api': 'blas',
'version': '0.3.23'}]
None
Context for the issue:
I am implementing jax.numpy.frompyfunc and had to special-case the tests in order to work around this bug: jax-ml/jax#17275