Add general fake_quantize_affine op #492
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/492
Note: Links to docs will display an error until the docs builds have been completed. ❗ 1 Active SEVsThere are 1 currently active SEVs. If your PR is affected, please view them below: ✅ No FailuresAs of commit 9c60424 with merge base 12ac498 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
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| @@ -335,6 +378,62 @@ def _dequantize_affine( | |||
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| return dequant.view(original_shape).to(output_dtype) | |||
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| def _fake_quantize_affine( | |||
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this can be a top level quant primitive I think
jerryzh168
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Jul 9, 2024
Summary: Add a general `fake_quantize_affine` op that simulates `quantize_affine` + `dequantize_affine` but without casting the intermediate quantized values to lower bit-widths, intended for quantization-aware training (QAT). Test Plan: python test/quantization/test_quant_primitives.py -k test_fake_quantize_affine
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Summary: Add a general `fake_quantize_affine` op that simulates `quantize_affine` + `dequantize_affine` but without casting the intermediate quantized values to lower bit-widths, intended for quantization-aware training (QAT). Test Plan: python test/quantization/test_quant_primitives.py -k test_fake_quantize_affine
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Summary: Add a general
fake_quantize_affineop that simulatesquantize_affine+dequantize_affinebut without casting the intermediate quantized values to lower bit-widths, intended for quantization-aware training (QAT).Test Plan:
python test/quantization/test_quant_primitives.py -k test_fake_quantize_affine