openvino

97909baf - Fix: Stable implementation for ReduceLogSumExp (ONNX frontend) (#32913)

Fix: Stable implementation for ReduceLogSumExp (ONNX frontend) (#32913) ### Summary #32839 This patch fixes numerical instability in the ONNX frontend’s `ReduceLogSumExp` operator. The previous implementation used a naïve `log(sum(exp(x)))` formulation, which overflowed to `Inf` for values near `log(MAX_FLOAT32)` (≈ 88.72). This caused incorrect results in the OpenVINO EP of ONNX Runtime, especially for float16 and float32 models. ### Fix Implemented a numerically stable LogSumExp computation: k = ReduceMax(x) lse = k + log( ReduceSum( exp(x - k) ) ) This matches the behavior of: - ONNX Runtime CPU EP - PyTorch and NumPy stable LogSumExp - OpenVINO PyTorch frontend implementation (`log.cpp`) The new implementation is applied to: - Opset 1–12 (`opset_1::reduce_log_sum_exp`) - Opset 13–17 (`opset_13::reduce_log_sum_exp`) - Opset 18+ (`opset_18::reduce_log_sum_exp`) ### Motivation Fixes incorrect `Inf` outputs for values ≥ 88.7 when using OpenVINOExecutionProvider. The issue was originally reported here: *[link to GitHub issue]*. ### Validation Tested using provided reproduction script from the issue: - Matches ONNX Runtime CPU EP for all tested values - No overflow observed for large positive inputs - Behavior consistent across float16/float32 models ### Notes This fix aligns ONNX frontend behavior with the already-correct PyTorch frontend implementation. --------- Co-authored-by: Maxim Vafin <maxim.vafin@intel.com>