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Splitting python bindings and cpp in ttnn library (#17957)
Now we will have to libraries, ttnncpp and ttnn, where ttnncpp will work as c++ backend while the tin library is the wrapper for python ### Ticket #16418 ### Problem description Our implementation of ttnn was coupled to python, so if anybody wanted to use the api directly from cpp, it could generate some linking issues. ### What's changed With ttnn divided in two, a user could link to the cpp backend without having to link to python, or use the python wrapper, depending on the use case. This gives more flexibility to our users to decide the way they decide to interact with the backend ### Checklist - [x] [All post commit](https://github.com/tenstorrent/tt-metal/actions/workflows/all-post-commit-workflows.yaml) CI passes - [x] [Blackhole Post commit](https://github.com/tenstorrent/tt-metal/actions/workflows/blackhole-post-commit.yaml) CI passes (if applicable) - [X ] [Model regression](https://github.com/tenstorrent/tt-metal/actions/workflows/perf-models.yaml) CI passes (if applicable) - [x] [Device performance regression](https://github.com/tenstorrent/tt-metal/actions/workflows/perf-device-models.yaml) CI passes (if applicable) - [ ] **(For models and ops writers)** Full [new models tests](https://github.com/tenstorrent/tt-metal/actions/workflows/full-new-models-suite.yaml) CI passes (if applicable) - [ ] New/Existing tests provide coverage for changes
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