The code will by default auto-download it during the build process. It's about 800 kbytes, which seems very reasonable for something that will reduce the generated code size by gigabytes for a large codebase.
Note that the open-source-ness is dubious... They say it was trained using an optimizer which isn't opensource, and that the results are significantly better ('more generalizable') than using the open source one. In my view, if the code that makes a binary blob isn't opensource, then the project isn't opensource...
Yes - the default model really needs to be trained with an opensource optimizer on a corpus of open source code (ie. with a license at least as permissive as llvm itself).
A blob trained with proprietary google tech on a proprietary google codebase isn't opensource. Even if it were, Google C++ differs in style quite widely from typical C++, so the model probably isn't as good as a model trained on all of github.
https://github.com/google/ml-compiler-opt/releases/tag/inlin...
The code will by default auto-download it during the build process. It's about 800 kbytes, which seems very reasonable for something that will reduce the generated code size by gigabytes for a large codebase.
Note that the open-source-ness is dubious... They say it was trained using an optimizer which isn't opensource, and that the results are significantly better ('more generalizable') than using the open source one. In my view, if the code that makes a binary blob isn't opensource, then the project isn't opensource...