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- Changes are consistent with the Python [Coding Style](https://github.com/google/styleguide/blob/gh-pages/pyguide.md).
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- Use pylint to check your Python code
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- Use flake8 and autopep8 to make Python code clean
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- Add unit tests in [Unit Tests](https://github.com/intel/lp-inference-kit/tree/master/tests) to cover the code you would like to contribute.
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- Run [Unit Tests](https://github.com/intel/lp-inference-kit/tree/master/tests).
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- Add unit tests in [Unit Tests](https://github.com/intel/lp-opt-tool/tree/master/tests) to cover the code you would like to contribute.
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- Run [Unit Tests](https://github.com/intel/lp-opt-tool/tree/master/tests).
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Intel® Low Precision Inference Toolkit (iLiT)
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Intel® Low Precision Optimization Tool (iLiT)
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=========================================
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Intel® Low Precision Inference Toolkit (iLiT) is an open-source python library which is intended to deliver a unified low-precision inference interface cross multiple Intel optimized DL frameworks on both CPU and GPU. It supports automatic accuracy-driven tuning strategies, along with additional objectives like performance, model size, or memory footprint. It also provides the easy extension capability for new backends, tuning strategies, metrics and objectives.
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Intel® Low Precision Optimization Tool (iLiT) is an open-source python library which is intended to deliver a unified low-precision inference interface cross multiple Intel optimized DL frameworks on both CPU and GPU. It supports automatic accuracy-driven tuning strategies, along with additional objectives like performance, model size, or memory footprint. It also provides the easy extension capability for new backends, tuning strategies, metrics and objectives.
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> **WARNING**
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