16eba537a8
### Description Remove unnecessary cargo:rerun-if-changed declaration. ### Motivation and Context 'cargo:rerun-if-changed' declarations tell Cargo when to re-run the build script. The intention is that if the build script depends on other files, then Cargo knows to re-run if those files change. It stores the output and checks it before each build. The intention is that one emits the declarations for _inputs_ of the build. This rerun-if-changed declaration is a declaration on the _output_ of the build, and stores the absolute path of the output. This is not a useful declaration because the output path is unique to the build script - there is no way for anything else to change it. However, this does generate unnecessary rebuilds in some cases, for example if the dependent repository is moved in the filesystem. This causes me some issues when using https://crane.dev, as due to some implementation details, if a crate being moved triggers a rebuild, by default the build is broken. To summarise: - declaration is redundant - causes issues in niche cases. |
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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
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General Information: onnxruntime.ai
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Usage documention and tutorials: onnxruntime.ai/docs
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YouTube video tutorials: youtube.com/@ONNXRuntime
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Companion sample repositories:
- ONNX Runtime Inferencing: microsoft/onnxruntime-inference-examples
- ONNX Runtime Training: microsoft/onnxruntime-training-examples
Builtin Pipeline Status
| System | Inference | Training |
|---|---|---|
| Windows | ||
| Linux | ||
| Mac | ||
| Android | ||
| iOS | ||
| Web | ||
| Other |
Third-party Pipeline Status
| System | Inference | Training |
|---|---|---|
| Linux |  |
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.