Add to function and decorator for AffineQuantizedTensor
#251
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Summary: att Next: we can move AffineQuantizedTensor to dtypes and make nf4tensor to use the same implements decorator Test Plan: python test/quantization/test_quant_api.py Reviewers: Subscribers: Tasks: Tags:
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looks good, nice cleanup, the only concern I have (potentially unfounded) is the potential for circular imports. Since every subclass will need to share the global op table they will all need to import from this file. Not sure if there is that much benefit to have a global op registry dict
oh we'll not put the general stuff in this file, current code is still temporary state, we'll move to dtypes folder global op registry dict is more for convenience, it's not required, we can refactor as well if that becomes an issue |
| # args[0].transposed = not args[0].transposed | ||
| # new = args[0]._change_shape(args[0].shape[::-1]) | ||
| # return return_and_correct_aliasing(func, args, kwargs, new) | ||
| raise Exception("transpose not implemented yet") |
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I think you could even return NotImplemented, which will result in a more standardized stack trace. Give it a try if you like.
Summary: att Next: we can move AffineQuantizedTensor to dtypes and make nf4tensor to use the same implements decorator Test Plan: python test/quantization/test_quant_api.py Reviewers: Subscribers: Tasks: Tags:
Summary:
att
Next: we can move AffineQuantizedTensor to dtypes and make nf4tensor to use the same implements decorator
Test Plan:
python test/quantization/test_quant_api.py
Reviewers:
Subscribers:
Tasks:
Tags: