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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/2370
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andrewor14
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Jun 16, 2025
| self._dequantize = dequantize_affine | ||
| elif zero_point_domain == ZeroPointDomain.NONE: | ||
| self._quantize = quantize_affine_no_zero_point | ||
| self._dequantize = dequantize_affine_no_zero_point |
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These changes aren't required to make the test pass right, just for clean ups? (we can keep them in this PR, just wanted to ask for my understanding)
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Yes, this is just for simplification!
metascroy
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Jun 16, 2025
liangel-02
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Aug 25, 2025
* Test PARQ with torchao activation quantization * Replace assertTrue with torch.testing.assert_close
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Added a test case to show numerical equivalency between quantizing:
UnifTorchaoQuantizer+ int8 activations with torchao'sFakeQuantizeConfigInt8DynamicActivationIntxWeightConfigNext steps with target
EmbeddingQuantizerandPackedLinearInt8DynamicActivationIntxWeightLayout.