onnxruntime

12916e9e - Check weight shape dimensions in ConvTranspose shape inference msrc116345 (#28524)

Check weight shape dimensions in ConvTranspose shape inference msrc116345 (#28524) This pull request introduces comprehensive validation and error handling improvements for the ConvTranspose operator across CPU, CUDA, WebGPU, and XNNPACK backends, as well as in shape inference and unit tests. The main focus is to ensure that invalid input shapes (especially rank-0 or rank-1 tensors) are properly detected and reported, preventing undefined behavior and improving robustness. Additionally, error messages are clarified, and several helper functions now return `Status` for better error propagation. **Validation and Error Handling Improvements:** * All ConvTranspose implementations (CPU, CUDA, WebGPU) now explicitly check that input `X` and filter `W` tensors have at least 3 dimensions, returning clear error messages if not. (`[[1]](diffhunk://#diff-72fa27d94d5d92dd1e78ff510ef9a84d1ad74426c19af9722cf6511f8d38a5a8R65-R79)`, `[[2]](diffhunk://#diff-d1bbcb0542b5acea587ac929cd6362cfd11172c522505c6db8b457a9d470c63dR273-R289)`, `[[3]](diffhunk://#diff-b615243d0702e9613bd815173108306495b0f690294001e606823b77322f6fafR22-L28)`) * The shape inference function for `ConvTransposeWithDynamicPads` now fails gracefully with descriptive errors if input or weight tensors have fewer than 2 dimensions. (`[onnxruntime/core/graph/contrib_ops/contrib_defs.ccL62-R67](diffhunk://#diff-81f57d9adc2cce94f85a2949a895b7ff82efcc13d05e23ee6567661f0fecb7c0L62-R67)`) * Additional validation ensures that `output_padding` and dynamic pads have correct sizes, and that `output_padding` values are within ONNX-specified limits. (`[[1]](diffhunk://#diff-72fa27d94d5d92dd1e78ff510ef9a84d1ad74426c19af9722cf6511f8d38a5a8R138-R153)`, `[[2]](diffhunk://#diff-72fa27d94d5d92dd1e78ff510ef9a84d1ad74426c19af9722cf6511f8d38a5a8R171-R187)`) **Refactoring for Robustness:** * Helper functions such as `ComputePadsAndOutputShape` and `ComputeTransposePadAndOutputShape` now return `Status`, allowing errors to propagate and be handled appropriately rather than causing crashes or silent failures. (`[[1]](diffhunk://#diff-72fa27d94d5d92dd1e78ff510ef9a84d1ad74426c19af9722cf6511f8d38a5a8L165-R234)`, `[[2]](diffhunk://#diff-72fa27d94d5d92dd1e78ff510ef9a84d1ad74426c19af9722cf6511f8d38a5a8L194-R262)`, `[[3]](diffhunk://#diff-72fa27d94d5d92dd1e78ff510ef9a84d1ad74426c19af9722cf6511f8d38a5a8L220-R282)`, `[[4]](diffhunk://#diff-72fa27d94d5d92dd1e78ff510ef9a84d1ad74426c19af9722cf6511f8d38a5a8R291-R302)`) * All call sites (CPU, CUDA, WebGPU, XNNPACK) are updated to handle and propagate these errors using `ORT_RETURN_IF_ERROR` or `ORT_THROW_IF_ERROR`. (`[[1]](diffhunk://#diff-72fa27d94d5d92dd1e78ff510ef9a84d1ad74426c19af9722cf6511f8d38a5a8R171-R187)`, `[[2]](diffhunk://#diff-d1bbcb0542b5acea587ac929cd6362cfd11172c522505c6db8b457a9d470c63dL362-R379)`, `[[3]](diffhunk://#diff-b615243d0702e9613bd815173108306495b0f690294001e606823b77322f6fafL48-R60)`, `[[4]](diffhunk://#diff-6a2f8672090f25850b90b266aff3c7212552fc81b14bb7b539e9e5161c9fd526L494-R497)`) **Unit Test Enhancements:** * New negative tests are added to verify that rank-0 and rank-1 weight tensors are properly rejected and produce the expected error messages, increasing test coverage and reliability. (`[onnxruntime/test/contrib_ops/conv_transpose_with_dynamic_pads_test.ccR22-R56](diffhunk://#diff-cb5bfc51d0c8096922eb674d142f0e970d5becd140b47bdfd7729a06a818b598R22-R56)`) **Minor Code Quality Improvements:** * Improved memory management in the CPU implementation by wrapping the allocated buffer in `BufferUniquePtr` immediately to prevent leaks if exceptions are thrown. (`[onnxruntime/core/providers/cpu/nn/conv_transpose.ccR79-R89](diffhunk://#diff-0dcb5a9c8ba0c4e67940e9d77f77cb706bbf82d67bf6757967099b0a69c797b5R79-R89)`) * Minor includes and type safety improvements (e.g., use of `SafeInt` for overflow protection). (`[[1]](diffhunk://#diff-72fa27d94d5d92dd1e78ff510ef9a84d1ad74426c19af9722cf6511f8d38a5a8R22)`, `[[2]](diffhunk://#diff-72fa27d94d5d92dd1e78ff510ef9a84d1ad74426c19af9722cf6511f8d38a5a8R291-R302)`) **Summary of Most Important Changes:** **1. Validation and Error Handling** - All ConvTranspose implementations now check that input and filter tensors have at least 3 dimensions, returning clear errors if not. (`[[1]](diffhunk://#diff-72fa27d94d5d92dd1e78ff510ef9a84d1ad74426c19af9722cf6511f8d38a5a8R65-R79)`, `[[2]](diffhunk://#diff-d1bbcb0542b5acea587ac929cd6362cfd11172c522505c6db8b457a9d470c63dR273-R289)`, `[[3]](diffhunk://#diff-b615243d0702e9613bd815173108306495b0f690294001e606823b77322f6fafR22-L28)`) - Shape inference for `ConvTransposeWithDynamicPads` fails with descriptive errors for invalid input or weight tensor ranks. (`[onnxruntime/core/graph/contrib_ops/contrib_defs.ccL62-R67](diffhunk://#diff-81f57d9adc2cce94f85a2949a895b7ff82efcc13d05e23ee6567661f0fecb7c0L62-R67)`) - Additional checks for `output_padding` and dynamic pads sizes and values, with ONNX spec compliance. (`[[1]](diffhunk://#diff-72fa27d94d5d92dd1e78ff510ef9a84d1ad74426c19af9722cf6511f8d38a5a8R138-R153)`, `[[2]](diffhunk://#diff-72fa27d94d5d92dd1e78ff510ef9a84d1ad74426c19af9722cf6511f8d38a5a8R171-R187)`) **2. Error Propagation and Refactoring** - Helper functions now return `Status` and propagate errors; all call sites updated to handle these errors. (`[[1]](diffhunk://#diff-72fa27d94d5d92dd1e78ff510ef9a84d1ad74426c19af9722cf6511f8d38a5a8L165-R234)`, `[[2]](diffhunk://#diff-72fa27d94d5d92dd1e78ff510ef9a84d1ad74426c19af9722cf6511f8d38a5a8L194-R262)`, `[[3]](diffhunk://#diff-72fa27d94d5d92dd1e78ff510ef9a84d1ad74426c19af9722cf6511f8d38a5a8L220-R282)`, `[[4]](diffhunk://#diff-72fa27d94d5d92dd1e78ff510ef9a84d1ad74426c19af9722cf6511f8d38a5a8R291-R302)`, `[[5]](diffhunk://#diff-d1bbcb0542b5acea587ac929cd6362cfd11172c522505c6db8b457a9d470c63dL362-R379)`, `[[6]](diffhunk://#diff-b615243d0702e9613bd815173108306495b0f690294001e606823b77322f6fafL48-R60)`, `[[7]](diffhunk://#diff-6a2f8672090f25850b90b266aff3c7212552fc81b14bb7b539e9e5161c9fd526L494-R497)`) **3. Unit Testing** - Added tests to ensure invalid weight tensor ranks are rejected with proper error messages. (`[onnxruntime/test/contrib_ops/conv_transpose_with_dynamic_pads_test.ccR22-R56](diffhunk://#diff-cb5bfc51d0c8096922eb674d142f0e970d5becd140b47bdfd7729a06a818b598R22-R56)`) **4. Code Quality** - Improved buffer management and type safety in CPU backend. (`[[1]](diffhunk://#diff-0dcb5a9c8ba0c4e67940e9d77f77cb706bbf82d67bf6757967099b0a69c797b5R79-R89)`, `[[2]](diffhunk://#diff-72fa27d94d5d92dd1e78ff510ef9a84d1ad74426c19af9722cf6511f8d38a5a8R22)`, `[[3]](diffhunk://#diff-72fa27d94d5d92dd1e78ff510ef9a84d1ad74426c19af9722cf6511f8d38a5a8R291-R302)`)