implement per-group quantization for Int8WeightOnlyConfig#4018
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Summary: This is needed for #2752, as there are some Meta-only callsites for `Int8WeightOnlyConfig` v1 using per-group quantization. 99% Claude Test Plan: ``` pytest test/quantization/quantize_/workflows/int8/test_int8_tensor.py -k test_int8_weight_only_v1_v2_per_group_equivalence ``` ghstack-source-id: 300693d ghstack-comment-id: 4013529969 Pull-Request: #4018
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/4018
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 4d04fad with merge base 637c4ac ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
vkuzo
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Mar 6, 2026
| y = y.reshape(*activation_tensor.shape[:-1], weight_tensor.qdata.shape[0]) | ||
| if weight_tensor.block_size[-1] < weight_tensor.qdata.shape[-1]: | ||
| # Per-group quantization: dequantize weight, then do FP matmul | ||
| w_dequant = weight_tensor.dequantize().to(output_dtype) |
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same logic as v1:
This was referenced Mar 6, 2026
andrewor14
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Mar 12, 2026
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Summary:
This is needed for #2752, as there
are some Meta-only callsites for
Int8WeightOnlyConfigv1 usingper-group quantization.
99% Claude
Test Plan: