mirror of
https://github.com/saymrwulf/onnxruntime.git
synced 2026-05-19 21:32:23 +00:00
ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
e2dd1315c7
### Fix build error on Windows when building with " --enable_language_interop_ops -cmake_extra_defines onnxruntime_DISABLE_ABSEIL=ON" This is a subsequent fix after https://github.com/microsoft/onnxruntime/pull/14309, which fixed build for onnxruntime_DISABLE_ABSEIL=ON build. Going furthur, if we enable --enable_language_interop_ops, there are following two errors: ``` test_symm_qgemm.cpp test_transpose.cpp onnxruntime_session.lib(inference_session.obj) : error LNK2019: unresolved external symbol "void __cdecl onnxruntime::L oadInterOp(class std::basic_string<wchar_t,struct std::char_traits<wchar_t>,class std::allocator<wchar_t> > const &,cla ss std::vector<struct Ort::CustomOpDomain,class std::allocator<struct Ort::CustomOpDomain> > &,class std::function<void __cdecl(char const *)> const &)" (?LoadInterOp@onnxruntime@@YAXAEBV?$basic_string@_WU?$char_traits@_W@std@@V?$allocato r@_W@2@@std@@AEAV?$vector@UCustomOpDomain@Ort@@V?$allocator@UCustomOpDomain@Ort@@@std@@@3@AEBV?$function@$$A6AXPEBD@Z@3 @@Z) referenced in function "public: __cdecl <lambda_f3a907e0b0a0e11d80d305605215cce8>::operator()(class std::shared_pt r<class onnxruntime::Model> &)const " (??R<lambda_f3a907e0b0a0e11d80d305605215cce8>@@QEBA@AEAV?$shared_ptr@VModel@onnxr untime@@@std@@@Z) [C:\Users\pengwa\dev\onnxruntime\build\Windows\RelWithDebInfo\onnxruntime_test_trainer.vcxproj] onnxruntime_session.lib(inference_session.obj) : error LNK2019: unresolved external symbol "void __cdecl onnxruntime::L oadInterOp(class onnx::ModelProto const &,class std::vector<struct Ort::CustomOpDomain,class std::allocator<struct Ort: :CustomOpDomain> > &,class std::function<void __cdecl(char const *)> const &)" (?LoadInterOp@onnxruntime@@YAXAEBVModelP roto@onnx@@AEAV?$vector@UCustomOpDomain@Ort@@V?$allocator@UCustomOpDomain@Ort@@@std@@@std@@AEBV?$function@$$A6AXPEBD@Z@ 5@@Z) referenced in function "public: __cdecl <lambda_340b7b787b9c0f81848d348e60fe6c91>::operator()(class std::shared_p tr<class onnxruntime::Model> &)const " (??R<lambda_340b7b787b9c0f81848d348e60fe6c91>@@QEBA@AEAV?$shared_ptr@VModel@onnx runtime@@@std@@@Z) [C:\Users\pengwa\dev\onnxruntime\build\Windows\RelWithDebInfo\onnxruntime_test_trainer.vcxproj] C:\Users\pengwa\dev\onnxruntime\build\Windows\RelWithDebInfo\RelWithDebInfo\onnxruntime_test_trainer.exe : fatal error LNK1120: 2 unresolved externals [C:\Users\pengwa\dev\onnxruntime\build\Windows\RelWithDebInfo\onnxruntime_test_trainer. vcxproj] onnxruntime.vcxproj -> C:\Users\pengwa\dev\onnxruntime\build\Windows\RelWithDebInfo\RelWithDebInfo\onnxruntime.dll onnxruntime_test_utils.vcxproj -> C:\Users\pengwa\dev\onnxruntime\build\Windows\RelWithDebInfo\RelWithDebInfo\onnxrun time_test_utils.lib CUDACOMPILE : nvcc warning : The 'compute_35', 'compute_37', 'sm_35', and 'sm_37' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning). [C:\Users\pengwa\dev\onnxruntime \build\Windows\RelWithDebInfo\custom_op_library.vcxproj] cuda_ops.cu CUDACOMPILE : nvcc warning : The 'compute_35', 'compute_37', 'sm_35', and 'sm_37' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning). [C:\Users\pengwa\dev\onnxruntime \build\Windows\RelWithDebInfo\onnxruntime_test_cuda_ops_lib.vcxproj] ``` ``` kernel_type_str_resolver_utils_test.cc local_kernel_registry_test.cc C:\Users\pengwa\dev\onnxruntime\onnxruntime\test\framework\allocation_planner_test.cc(1388,9): error C2220: the followin g warning is treated as an error [C:\Users\pengwa\dev\onnxruntime\build\Windows\RelWithDebInfo\onnxruntime_test_all.vcxp roj] C:\Users\pengwa\dev\onnxruntime\onnxruntime\test\framework\allocation_planner_test.cc(1388,9): warning C4067: unexpected tokens following preprocessor directive - expected a newline [C:\Users\pengwa\dev\onnxruntime\build\Windows\RelWithDebI nfo\onnxruntime_test_all.vcxproj] ``` ### Motivation and Context <!-- - Why is this change required? What problem does it solve? - If it fixes an open issue, please link to the issue here. --> |
||
|---|---|---|
| .config | ||
| .devcontainer | ||
| .gdn | ||
| .github | ||
| .pipelines | ||
| .vscode | ||
| cgmanifests | ||
| cmake | ||
| csharp | ||
| dockerfiles | ||
| docs | ||
| include/onnxruntime/core | ||
| java | ||
| js | ||
| objectivec | ||
| onnxruntime | ||
| orttraining | ||
| package/rpm | ||
| samples | ||
| test | ||
| tools | ||
| winml | ||
| .clang-format | ||
| .clang-tidy | ||
| .dockerignore | ||
| .flake8 | ||
| .gitattributes | ||
| .gitignore | ||
| .gitmodules | ||
| build.amd64.1411.bat | ||
| build.bat | ||
| build.sh | ||
| CITATION.cff | ||
| CODEOWNERS | ||
| CONTRIBUTING.md | ||
| lgtm.yml | ||
| LICENSE | ||
| NuGet.config | ||
| ort.wprp | ||
| ORT_icon_for_light_bg.png | ||
| packages.config | ||
| pyproject.toml | ||
| README.md | ||
| requirements-dev.txt | ||
| requirements-doc.txt | ||
| requirements-training.txt | ||
| requirements.txt.in | ||
| SECURITY.md | ||
| setup.py | ||
| ThirdPartyNotices.txt | ||
| VERSION_NUMBER | ||
ONNX Runtime is a cross-platform inference and training machine-learning accelerator.
ONNX Runtime inference can enable faster customer experiences and lower costs, supporting models from deep learning frameworks such as PyTorch and TensorFlow/Keras as well as classical machine learning libraries such as scikit-learn, LightGBM, XGBoost, etc. ONNX Runtime is compatible with different hardware, drivers, and operating systems, and provides optimal performance by leveraging hardware accelerators where applicable alongside graph optimizations and transforms. Learn more →
ONNX Runtime training can accelerate the model training time on multi-node NVIDIA GPUs for transformer models with a one-line addition for existing PyTorch training scripts. Learn more →
Get Started & Resources
-
General Information: onnxruntime.ai
-
Usage documention and tutorials: onnxruntime.ai/docs
-
YouTube video tutorials: youtube.com/@ONNXRuntime
-
Companion sample repositories:
- ONNX Runtime Inferencing: microsoft/onnxruntime-inference-examples
- ONNX Runtime Training: microsoft/onnxruntime-training-examples
Build Pipeline Status
| System | CPU | GPU | EPs |
|---|---|---|---|
| Windows | |||
| Linux | |||
| Mac | |||
| Android | |||
| iOS | |||
| WebAssembly |
Data/Telemetry
Windows distributions of this project may collect usage data and send it to Microsoft to help improve our products and services. See the privacy statement for more details.
Contributions and Feedback
We welcome contributions! Please see the contribution guidelines.
For feature requests or bug reports, please file a GitHub Issue.
For general discussion or questions, please use GitHub Discussions.
Code of Conduct
This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.
License
This project is licensed under the MIT License.