ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
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Adrian Lizarraga e42f7487df
Add logging APIs for custom operators (#14416)
### Description
Add logging APIs for custom ops.

This PR introduces a `OrtLogger` type, which can be retrieved from a
`OrtKernelInfo` or `OrtKernelContext`. The kernel info's logger is the session logger stored
in the execution provider. The kernel context's logger is a run logger.



### Motivation and Context
Allows custom ops to log information in a manner consistent with
built-in ops.

Example usage in custom op:
```C++
struct MyCustomKernel {
  MyCustomKernel(const OrtApi& api, const OrtKernelInfo* info) {
    Ort::ConstKernelInfo kinfo(info);
    this->logger_ = kinfo.GetLogger();
    // ...
    ORT_CXX_LOGF_NOEXCEPT(this->logger_, OrtLoggingLevel::ORT_LOGGING_LEVEL_ERROR, "Error: %s", err_msg);
  }

  void Compute(OrtKernelContext* context) {
    ORT_CXX_LOG(this->logger_, OrtLoggingLevel::ORT_LOGGING_LEVEL_VERBOSE, "Calling compute...");
    // ...
  }

  // ...
 private:
  Ort::Logger logger_;
};
```
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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

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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.