Add support for the default float, int and bool types for executorch::runtime::etensor::Scalar to` method #10040
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…::runtime::etensor::Scalar` to` method * move all default float, int and bool to ET_FORALL_FLOAT_INT_BOOL_TYPES macros * replace all to with `to##name` macros * add additional checks in `ScalarTest.ToScalarType` test
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/10040
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@pytorchbot label "release notes: runtime" |
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Summary
float,::executorch::runtime::etensor::Half, and::executorch::runtime::etensor::BFloat16fortomethod of ExecuTorch's Scalartomethods withto##name()macros (same as PyTorch c10::Scalar).floattype.uint16/32/64_ttypes (since 'uint64_t' can overflow' int64_t', separate logic is required) and does not includeexecutorch::runtime::etensor::complex.c10::overflows.hfrom torch. (I will add an overflow check after I figure out what is the right way to do this :))I need a bit further guidance related to adding support for more complex types and handling overflows:
TypeCast.hfor typecasting (similar to PyTorch c10). Would this be better than having the casting code in theScalarclass?c10::overflows.hfrom pytorch c10 to handle overflows?Fixes #9500
P.S. If you have any concerns about this PR, please let me know, I will fix :)
Test plan
I added tests in' runtime/core/portable_type/test/scalar_test.cpp' for additional types types.