Update imports after QAT was moved out of prototype #1883
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/torchtune/1883
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torchtune/utils/_import_guard.py
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| @@ -20,7 +20,7 @@ | |||
| _USE_NEW_TENSOR_CORE_TILED_LAYOUT_API = _is_fbcode() or ( | |||
| not _is_fbcode() | |||
| and ( | |||
| ("dev" not in torchao_version and torchao_version >= "0.6.0") | |||
| ("dev" not in torchao_version and torchao_version >= "0.7.0") | |||
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So the new API is not in 0.6.1? I thought it landed before that release
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Yeah it's not in 0.6.x
torchtune/training/quantization.py
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| - :class:`~torchao.quantization.quant_api.Int8DynActInt4WeightQuantizer`: "8da4w" (requires ``torch>=2.3.0``) | ||
| - :class:`~torchao.quantization.prototype.qat.Int8DynActInt4WeightQATQuantizer`: "8da4w-qat" (requires ``torch>=2.4.0``) | ||
| - :class:`~torchao.quantization.qat.Int8DynActInt4WeightQATQuantizer`: "8da4w-qat" (requires ``torch>=2.4.0``) |
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I think we can fully remove both of these torch requirements as we assume stable PyTorch (i.e. >= 2.5)
| mode = _quantizer_to_mode.get(type(quantizer), None) | ||
| if mode is not None and "module-swap" in mode: | ||
| warn( | ||
| "*QuantizerModuleSwap is deprecated. Please use the version without 'ModuleSwap' instead" |
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nit: should be able to just give the exact classes in the warn message using e.g. f"{quantizer.__class__.__name__}" (or something like that)
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hmm I don't think that's possible given we just assign the classes today, e.g.:
>>> class A: pass
...
>>> B = A
>>> A().__class__.__name__
'A'
>>> B().__class__.__name__
'A'
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Summary: pytorch/ao#1091 moved QAT out of prototype in torchao. This is a BC-breaking change so torchtune also needs to update its QAT imports. Additionally, after pytorch/ao#987 we decided that QAT in torchao will use module swaps to insert fake quantizes, so there is no need to have a separate module swap quantizer, so this commit removes the `*ModuleSwapQuantizer` option. Test Plan: pytest -m integration_test tests/recipes/test_qat_distributed.py should work
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Summary: pytorch/ao#1091 moved QAT out of prototype in torchao. This is a BC-breaking change so torchtune also needs to update its QAT imports. Additionally, after pytorch/ao#987 we decided that QAT in torchao will use module swaps to insert fake quantizes, so there is no need to have a separate module swap quantizer, so this commit removes the
*ModuleSwapQuantizeroption.Test Plan:
pytest -m integration_test tests/recipes/test_qat_distributed.py should work