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ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
5d3992f999
If the output has a symbolic dimension
* Infer the shape if it is a loop state variable as we have the input value, and the shape from the subgraph output must match
* Use a temporary MLValue for the first subgraph execution if it is a subgraph output with a symbolic dimension.
* After the first execution make the overall output shape concrete and allocate the full output buffer.
* Use slices of the full output buffer for all other subgraph executions to avoid copies.
Add unit test to validate.
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| cmake | ||
| csharp | ||
| docs | ||
| include/onnxruntime/core | ||
| onnxruntime | ||
| package/rpm | ||
| tools | ||
| .clang-format | ||
| .clang-tidy | ||
| .gitattributes | ||
| .gitignore | ||
| .gitmodules | ||
| build.amd64.1411.bat | ||
| build.bat | ||
| BUILD.md | ||
| build.sh | ||
| CONTRIBUTING.md | ||
| LICENSE | ||
| README.md | ||
| rename_manylinux.sh | ||
| requirements-dev.txt | ||
| requirements.txt | ||
| setup.py | ||
| ThirdPartyNotices.txt | ||
| VERSION_NUMBER | ||
ONNX Runtime
ONNX Runtime is the runtime for ONNX.
Engineering Design
API
| API | CPU package | GPU package |
|---|---|---|
| Python | Windows Linux Mac |
Windows Linux |
| C# | Windows | Not available |
| C | Windows Linux |
Not available |
Build
Contribute
Versioning
Feedback
- File a bug in GitHub Issues
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.