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Document faster builds for C++ changes (#102316)

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Update `CONTRIBUTING.md` with tip on how to avoid rebuilding/copying libs every time one makes a small change to the native code.

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> _`setup.py` docs_
> _Link to source and build dirs_
> _Winter of testing_

Pull Request resolved: https://github.com/pytorch/pytorch/pull/102316
Approved by: https://github.com/kit1980, https://github.com/huydhn
This commit is contained in:
Nikita Shulga
2023-05-26 14:11:08 +00:00
committed by PyTorch MergeBot
parent c05a317371
commit efd774a295
1 changed files with 12 additions and 2 deletions
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CONTRIBUTING.md
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@ -83,12 +83,22 @@ Follow the instructions for [installing PyTorch from source](https://github.com/
* If you want to have no-op incremental rebuilds (which are fast), see [Make no-op build fast](#make-no-op-build-fast) below.
* When installing with `python setup.py develop` (in contrast to `python setup.py install`) you will symlink
the Python files from the current local source-tree into the Python install.
* When installing with `python setup.py develop` (in contrast to `python setup.py install`) Python runtime will use
the current local source-tree when importing `torch` package. (This is done by creating [`.egg-link`](https://wiki.python.org/moin/PythonPackagingTerminology#egg-link) file in `site-packages` folder)
This way you do not need to repeatedly install after modifying Python files (`.py`).
However, you would need to reinstall if you modify Python interface (`.pyi`, `.pyi.in`) or
non-Python files (`.cpp`, `.cc`, `.cu`, `.h`, ...).
One way to avoid running `python setup.py develop` every time one makes a change to C++/CUDA/ObjectiveC files on Linux/Mac,
is to create a symbolic link from `build` folder to `torch/lib`, for example, by issuing following:
```bash
pushd torch/lib; sh -c "ln -sf ../../build/lib/libtorch_cpu.* ."; popd
```
Afterwards rebuilding a library (for example to rebuild `libtorch_cpu.so` issue `ninja torch_cpu` from `build` folder),
would be sufficient to make change visible in `torch` package.
To reinstall, first uninstall all existing PyTorch installs. You may need to run `pip
uninstall torch` multiple times. You'll know `torch` is fully
uninstalled when you see `WARNING: Skipping torch as it is not