test_finfo fails on numpy
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Assessment
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Newbie friendliness
- 35/100
- Issue type
- Bug
- Clarity
- Mostly clear
- Activity status
- Stale
- Tech stack
- numpy, python
- Domain
- testing-qa
Research direction
Start by locating the test_finfo spec and the compatibility level mentioned in the report. Compare the expected type of xp.finfo(xp.float32).eps with the NumPy and JAX examples, then run the relevant test suite; done means the test behavior consistently reflects the supported array API implementations.
Written by the indexing model from the issue text.
Description
The spec seems to imply that xp.finfo(xp.float32).eps is a python float, but numpy and jax.numpy use numpy scalars instead
In [1]: import torch
In [2]: torch.finfo(torch.float32).eps
Out[2]: 1.1920928955078125e-07
In [3]: type(torch.finfo(torch.float32).eps)
Out[3]: float
In [4]: import numpy as np
In [5]: type(np.finfo(np.float32).eps)
Out[5]: numpy.float32
In [6]: import jax.numpy as jnp
In [7]: type(jnp.finfo(jnp.float32).eps)
Out[7]: numpy.float32
Not hard to work around on the -compat level, even if having a wrapper for finfo feels a bit cheesy.
- Dominant language
- Python
- Stars
- 74
- Forks
- 54
- Avg merge
- 4h 35m
- Merged PRs (30d)
- 4
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