Add support for using AffineQuantizedTensor with weights_only=True
#630
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/630
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 009d28e with merge base 8bba8ed ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
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Summary: `torch.load(file, weights_only=True)` is safer so ideally we can use that, by default it does not work with tensor subclasses, since now we have https://pytorch.org/docs/main/notes/serialization.html#torch.serialization.add_safe_globals we can add all tensor subclass classes and special types to globals so that these can work with `weights_only=True` Test Plan: python test/dtypes/test_affine_quantized.py Reviewers: Subscribers: Tasks: Tags:
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| return int8_dynamic_activation_int8_weight(layout_type=SemiSparseLayoutType()) | ||
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| if TORCH_VERSION_AFTER_2_5: |
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A n00b qn: it wasn't super clear to me why these functions are used during unpickling?
but I trust that you added them because they appeared in the error message :)
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yeah that's correct, these functions are serialized as well when we do dynamic quantization
msaroufim
approved these changes
Aug 8, 2024
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Summary:
torch.load(file, weights_only=True)is safer so ideally we can use that, by default it does not work with tensor subclasses, since now we have https://pytorch.org/docs/main/notes/serialization.html#torch.serialization.add_safe_globals we can add all tensor subclass classes and special types to globals so that these can work withweights_only=TrueTest Plan:
python test/dtypes/test_affine_quantized.py
Reviewers:
Subscribers:
Tasks:
Tags: