[tmva][sofie] Add HardSigmoid operator for ONNX inference #20933
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Implemented the HardSigmoid operator (ONNX opset 6+) for Project SOFIE. This operator is a prerequisite for supporting MobileNetV3 architectures (specifically for the HardSwish activation). Implemented in `ROperator_HardSigmoid`. - Uses hexfloat constants (`0x0p+0f`, `0x1p+0f`) for clamp bounds to ensure bit-exact reproducibility and prevent implicit double-precision promotion. - Attributes `alpha` and `beta` are strictly handled as floats to avoid `CVTSS2SD` overhead in the generated inference loop. - Added GTest suite `TestSofieHardSigmoid` validating numerical correctness against SciPy data and verifying AVX-friendly code generation.
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This Pull Request
This PR implements the
HardSigmoidoperator for the SOFIE (System for Optimized Fast Inference code Emit) engine. This is a standalone operator implementation compliant with the ONNX specification (Opset 6+).The implementation is critical for supporting MobileNetV3 architectures (also for the
HardSwishactivation).Changes or fixes:
New Operator: Implemented
TMVA::Experimental::SOFIE::ROperator_HardSigmoid.std::fmaxandstd::fminwith specific hexfloat constants (0x0p+0f,0x1p+0f) to ensure the compiler emits pure AVXMAXSS/MINSSinstructions without intermediate double-precision conversions.It Enforces
f-suffix onalphaandbetacoefficients to prevent implicit promotion todoubleduring inference.Updated
RModelParser_ONNXto correctly parsealphaandbetaattributes (defaults are set to0.2,0.5).Validation: Added a new unit test suite
TestSofieHardSigmoid.Checklist:
TestSofieHardSigmoidpassing)This PR fixes # (No specific issue linked, strictly feature addition)
cc: @guitargeek @moneta @devajithvs @bellenot