Add NVFP4 QAT #2666
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Add NVFP4 QAT #2666
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**Summary:** This commit adds a QAT flow for NVFP4, following the
numerics in `NVFP4Tensor` closely but without the dtyping casting,
swizzling, and the packing/unpacking. Users can call this flow as follows:
```
from torchao.quantization import quantize_
from torchao.quantization.qat import NVFP4FakeQuantizeConfig, QATConfig
qat_config = QATConfig(
activation_config=NVFP4FakeQuantizeConfig(),
weight_config=NVFP4FakeQuantizeConfig(),
step="prepare",
)
quantize_(model, qat_config)
```
**Test Plan:**
```
python test/quantization/test_qat.py -k test_qat_nvfp4
```
[ghstack-poisoned]
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/2666
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 87175e9 with merge base 97b090d ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
andrewor14
added a commit
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Aug 1, 2025
**Summary:** This commit adds a QAT flow for NVFP4, following the
numerics in `NVFP4Tensor` closely but without the dtyping casting,
swizzling, and the packing/unpacking. Users can call this flow as follows:
```
from torchao.quantization import quantize_
from torchao.quantization.qat import NVFP4FakeQuantizeConfig, QATConfig
qat_config = QATConfig(
activation_config=NVFP4FakeQuantizeConfig(),
weight_config=NVFP4FakeQuantizeConfig(),
step="prepare",
)
quantize_(model, qat_config)
```
**Test Plan:**
```
python test/quantization/test_qat.py -k test_qat_nvfp4
```
ghstack-source-id: fe592ca
Pull Request resolved: #2666
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topic: new feature
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Stack from ghstack (oldest at bottom):
Summary: This commit adds a QAT flow for NVFP4, following the
numerics in
NVFP4Tensorclosely but without the dtyping casting,swizzling, and the packing/unpacking. Users can call this flow as follows:
Test Plan: