ENH: test vecdot values, incl complex conj #314
Conversation
Preferred as long as xp.isdtype is not universally available (looking at you pytorch)
|
Let's get this in and see if this causes any issues going forward. |
| else: | ||
| true_val = None | ||
| def true_val(x, y, axis=-1): | ||
| return xp.sum(xp.multiply(_conj(x), y), dtype=res.dtype) |
There was a problem hiding this comment.
Unfortunately, if you look here, there is no approximate testing done at all for floating-point values https://github.com/data-apis/array-api-tests/pull/314/files?diff=unified#diff-6056c0b3af9cd3ba66387432a17f5f36bbd54220419656441a8b01bcdc4df44bR57.
We should probably add a flag to that helper to allow approximate testing to be enabled. Some functions are impossible to do approximate testing for because they don't even have a single possible output (e.g., eigh could pick completely different eigenvectors and still be correct).
There are helpers used in the elementwise functions that could be reused here for testing floating-point (and complex) closeness. Basically, they test with very large epsilons. Even that would be enough to detect that a library isn't conjugating, which is the real concern for this test specifically.
Add a value test for
vecdotfor real and complex fp types: this is a matching test for data-apis/array-api-compat#201 and data-apis/array-api-strict#98A weird thing is that the test should fail without data-apis/array-api-strict#98 but locally it does not. Probably I'm not generating enough examples---is there a way to bump the number with a cmdline switch? Tried several variations of
python --max-examples=100but no luck so far.closes gh-312