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Better document how to rebuild only parts of the project. (#1796)

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Signed-off-by: Edward Z. Yang <ezyang@fb.com>
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Edward Z. Yang 2017-06-13 17:23:39 -04:00 committed by Soumith Chintala
parent 38a48729f0
commit 5a63a6d47f
1 changed files with 39 additions and 14 deletions
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CONTRIBUTING.md
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@ -72,17 +72,7 @@ For example:
You do not need to repeatedly install after modifying python files.
If you are working on C files, you will need to build your changes:
```
(rm -rf build; python setup.py develop)
```
We recommend removing the `build` directory before rebuilding because
setup.py's recompilation checking is not great, and it will often fail
to rebuild C code after you modify code in a `generic` directory.
#### Managing multiple build trees
## Managing multiple build trees
One downside to using `python setup.py develop` is that your development
version of pytorch will be installed globally on your account (e.g., if
@ -101,9 +91,36 @@ source activate pytorch-myfeature
python setup.py build develop
```
#### C++ Development tips
## C++ Development tips
When you are developing on the C++ side of things, the environment variables `DEBUG` and `NO_CUDA` are helpful.
If you are working on the C++ code, there are a few important things that you
will want to keep in mind:
1. How to rebuild only the code you are working on, and
2. How to make rebuilds in the absence of changes go faster.
### Build only what you need.
`python setup.py build` will build everything, but since our build system is
not very optimized for incremental rebuilds, this will actually be very slow.
Far better is to only request rebuilds of the parts of the project you are
working on:
- Working on `torch/csrc`? Run `python setup.py build_ext` to rebuild.
- Working on `torch/lib/TH`, did not make any cmake changes, and just want to
see if it compiles? Run `(cd torch/lib/build/TH && make install -j40)`. This
applies for any other subdirectory of `torch/lib`. **Warning: Changes you
make here will not be visible from Python.** See below.
- Working on `torch/lib` and want to run your changes / rerun cmake? Run
`python setup.py build_deps`. Note that this will rerun cmake for
every subdirectory in TH; if you are only working on one project,
consider editing `torch/lib/build_all.sh` and commenting out the
`build` lines of libraries you are not working on.
On the initial build, you can also speed things up with the environment
variables `DEBUG` and `NO_CUDA`.
- `DEBUG=1` will enable debug builds (-g -O0)
- `NO_CUDA=1` will disable compiling CUDA (in case you are developing on something not CUDA related), to save compile time.
@ -113,7 +130,15 @@ For example:
NO_CUDA=1 DEBUG=1 python setup.py build develop
```
Also, if you are developing a lot, using ccache is a real time-saver. By default, ccache does not properly support CUDA stuff, so here are the instructions for installing a custom `ccache` fork that has CUDA support:
Make sure you continue to pass these flags on subsequent builds.
### Make no-op build fast.
Python `setuptools` is pretty dumb, and always rebuilds every C file in a
project. Using ccache in a situation like this is a real time-saver. However, by
default, ccache does not properly support CUDA stuff, so here are the
instructions for installing a custom `ccache` fork that has CUDA support:
```
# install and export ccache
if ! ls ~/ccache/bin/ccache