onnxruntime

0b278bbf - Update optimizer opset version checks for latest ONNX opset 26 (#28966)

Update optimizer opset version checks for latest ONNX opset 26 (#28966) This pull request expands support for additional ONNX opset versions in the attention fusion optimization code, making the optimizer compatible with newer and more diverse ONNX models. The changes primarily update the accepted opset versions for various operators such as `Transpose`, `Reshape`, `Squeeze`, `Unsqueeze`, `Shape`, and others across multiple functions. This ensures broader model compatibility and improves the robustness of the fusion logic. **Expanded opset version support for attention fusion:** * Updated accepted opset versions for key operators (`Transpose`, `Reshape`, `Squeeze`, `Unsqueeze`, `Shape`, `Add`, `Mul`, `Sub`, `Div`, `Cast`, etc.) in the main attention fusion logic (`attention_fusion.cc`), allowing matching and fusion of newer ONNX models using these operators at opsets up to 25. [[1]](diffhunk://#diff-2d859229c1824649bd6a37eaefa52306394bc6c3aa341d6deff1d4f2fb9902f3L352-R367) [[2]](diffhunk://#diff-2d859229c1824649bd6a37eaefa52306394bc6c3aa341d6deff1d4f2fb9902f3L382-R384) [[3]](diffhunk://#diff-2d859229c1824649bd6a37eaefa52306394bc6c3aa341d6deff1d4f2fb9902f3L394-R395) [[4]](diffhunk://#diff-2d859229c1824649bd6a37eaefa52306394bc6c3aa341d6deff1d4f2fb9902f3L405-R405) [[5]](diffhunk://#diff-2d859229c1824649bd6a37eaefa52306394bc6c3aa341d6deff1d4f2fb9902f3L463-R471) [[6]](diffhunk://#diff-2d859229c1824649bd6a37eaefa52306394bc6c3aa341d6deff1d4f2fb9902f3L500-R500) [[7]](diffhunk://#diff-2d859229c1824649bd6a37eaefa52306394bc6c3aa341d6deff1d4f2fb9902f3L514-R514) [[8]](diffhunk://#diff-2d859229c1824649bd6a37eaefa52306394bc6c3aa341d6deff1d4f2fb9902f3L923-R927) [[9]](diffhunk://#diff-2d859229c1824649bd6a37eaefa52306394bc6c3aa341d6deff1d4f2fb9902f3L956-R958) [[10]](diffhunk://#diff-2d859229c1824649bd6a37eaefa52306394bc6c3aa341d6deff1d4f2fb9902f3L1073-R1074) [[11]](diffhunk://#diff-2d859229c1824649bd6a37eaefa52306394bc6c3aa341d6deff1d4f2fb9902f3L1166-R1166) [[12]](diffhunk://#diff-2d859229c1824649bd6a37eaefa52306394bc6c3aa341d6deff1d4f2fb9902f3L1268-R1275) **Helper and mask subgraph matching improvements:** * Broadened opset version checks for subgraph matching in helper functions, including those for Gemm subgraphs, unidirectional mask subgraphs, input mask subgraphs, and past subgraph matching, to support additional opset versions and operator variants. [[1]](diffhunk://#diff-97696a1ea660259af1c02da793abf7a807de115421a0ec32f1e36f39371e4e16L77-R84) [[2]](diffhunk://#diff-97696a1ea660259af1c02da793abf7a807de115421a0ec32f1e36f39371e4e16L169-R171) [[3]](diffhunk://#diff-97696a1ea660259af1c02da793abf7a807de115421a0ec32f1e36f39371e4e16L378-R379) [[4]](diffhunk://#diff-97696a1ea660259af1c02da793abf7a807de115421a0ec32f1e36f39371e4e16L395-R402) [[5]](diffhunk://#diff-97696a1ea660259af1c02da793abf7a807de115421a0ec32f1e36f39371e4e16L457-R458) [[6]](diffhunk://#diff-97696a1ea660259af1c02da793abf7a807de115421a0ec32f1e36f39371e4e16L485-R487) [[7]](diffhunk://#diff-97696a1ea660259af1c02da793abf7a807de115421a0ec32f1e36f39371e4e16L635-R637) [[8]](diffhunk://#diff-97696a1ea660259af1c02da793abf7a807de115421a0ec32f1e36f39371e4e16L769-R769) [[9]](diffhunk://#diff-97696a1ea660259af1c02da793abf7a807de115421a0ec32f1e36f39371e4e16L794-R796) [[10]](diffhunk://#diff-97696a1ea660259af1c02da793abf7a807de115421a0ec32f1e36f39371e4e16L812-R814) [[11]](diffhunk://#diff-97696a1ea660259af1c02da793abf7a807de115421a0ec32f1e36f39371e4e16L890-R890) These changes collectively future-proof the attention fusion optimizer for a wider range of ONNX models and operator versions, reducing the likelihood of unsupported patterns during optimization.