onnxruntime

ad11f7cf - Fix OOB reads in SoftmaxCrossEntropyLoss via label bounds validation (#28004)

Fix OOB reads in SoftmaxCrossEntropyLoss via label bounds validation (#28004) ### Description Fix out-of-bounds reads in `SoftmaxCrossEntropyLoss` and `SoftmaxCrossEntropyLossGrad` (CPU EP) when label values are outside `[0, C)`. Same class of bug fixed in #27568 for `SparseSoftmaxCrossEntropy`. The CUDA kernels currently only validate labels via `CUDA_KERNEL_ASSERT`, which is a no-op in release builds. CUDA hardening is not part of this PR. ### Changes - Forward: bounds check folded into the three per-sample loops (after `ignore_index` skip, before any `weight_data[label]` / `log_prob_data[i*C + label]` access). - Backward: single upfront serial bounds check (parallel-for lambdas cannot return Status); comment explains why. - Validate `weight_shape[0] == C`. - Move `weight_data[label]` access after `ignore_index` check in grad weighted paths. - `N_D * C` wrapped in `SafeInt`; `gsl::narrow<int>` for `N_D` and `C`. Overflow / truncation returns `INVALID_ARGUMENT`. - `Eigen::Index` size guard: `ORT_ENFORCE` -> `ORT_RETURN_IF`. - `IsScalar(ignore_index)` check: `ORT_ENFORCE` -> `ORT_RETURN_IF_NOT` in both forward and backward. - Pre-existing wrong-sized `memset` in backward (`sizeof(T1) * N_D`) corrected to `sizeof(T1) * probability_shape.Size()`. The previous code was effectively redundant (subsequent parallel-for paths overwrite all `N_D * C` entries) so this is cleanup, not an active OOB. - Renamed `weight_smaple` -> `weight_sample`. ### Tests 11 regression tests in `cross_entropy_test.cc`: - Label too large (forward + grad, int64 + int32) - Negative label - Label too large with weights (MEAN and SUM reductions) - Higher-dim logit `[2,4,2,3]` with label `[2,2,3]` - `SoftmaxCrossEntropyLossInternal` and `SoftmaxCrossEntropyLossInternalGrad` with `ignore_index` as a runtime tensor input --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>