Enable fp16+int4 mixed precission path for int4 xpu path with int zero point

[liangan1]

Backgroup
For XPU device, when user select the int zero point, the _torch.ops.aten.weight_int4pack_mm_with_scales_and_zeros kernel operator will be used to do A16W4 computation. Both Afp16W4 and ABF16int4 are supported in this op on XPU device, while only the BF16 activation is supported in the torchAO now, In this PR we want to unlock the FP16 activation support.

[pytorch-bot]

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/2240

• 📄 Preview Python docs built from this PR

Note: Links to docs will display an error until the docs builds have been completed.

✅ No Failures

As of commit fa6ca5d with merge base 2c901b3 ():
💚 Looks good so far! There are no failures yet. 💚

This comment was automatically generated by Dr. CI and updates every 15 minutes.

[liangan1]

@jerryzh168 can you help to review?

[liangan1]

@EikanWang

[jerryzh168]

can you add a test? maybe add one under

ao/test/dtypes/test_affine_quantized.py

Line 299 in 4d5f657

class TestAffineQuantizedBasic(TestCase):

for now, current tests are not very well structured

[liangan1]

@pytorchbot label new feature

[pytorch-bot]

Didn't find following labels among repository labels: new,feature

[liangan1]

@pytorchbot label quantize

[liangan1]

@pytorchbot merge

[pytorchmergebot]

Merge started

Your change will be merged once all checks pass (ETA 0-4 Hours).

Learn more about merging in the wiki.

Questions? Feedback? Please reach out to the PyTorch DevX Team

Advanced Debugging

Check the merge workflow status
here

[pytorchmergebot]

Merge failed

Reason: 1 jobs have failed, first few of them are: PR Label Check / Check PR Labels

Details for Dev Infra team

Raised by workflow job

[liangan1]

@pytorchbot label ciflow/xpu

[pytorch-bot]

To add these label(s) (ciflow/xpu) to the PR, please first approve the workflows that are awaiting approval (scroll to the bottom of this page).

This helps ensure we don't trigger CI on this PR until it is actually authorized to do so. Please ping one of the reviewers if you do not have access to approve and run workflows.

[liangan1]

@pytorchbot label ciflow/xpu

[pytorch-bot]

Didn't find following labels among repository labels: ciflow/xpu

[liangan1]

@pytorchbot label ci

[liangan1]

can you add a test? maybe add one under

ao/test/dtypes/test_affine_quantized.py

Line 299 in 4d5f657

class TestAffineQuantizedBasic(TestCase):

for now, current tests are not very well structured

Yes. I checked the test in test_affine_quantized.py. xpu is not enabled for a lot of UTs(no only for dtype), I will open a new pr to enable these UTs.