Open peterjc123 opened 4 years ago
Updated the title, since it's not specific to caffe2.
Updated the title, since it's not specific to caffe2.
You mean Windows, right?
There are two plans:
requirements.txt
and meta.yml
.caffe2.python
.What do you think, @ezyang @seemethere @malfet @soumith ?
@malfet was recently talking about how, for our binary builds, we should just not ship caffe2 by default (you have to build from source if you want caffe2). I think that definitely pushes us towards (2) here. I definitely don't want to add protobuf to the dependency list here.
we should just not ship caffe2 by default
So is it possible to stop compiling them through some CMake options? If we don't want to ship them, then it's just a waste of time building them (at least in release builds).
When it's no longer shipped by default, I think we should still compile caffe2(to avoid regressions), but perhaps for just one configuration on the platform.
@malfet What about still compiling them in PyTorch CI jobs but skipping them in binary jobs?
@peterjc123 sounds reasonable to me.
@malfet So the problem is how to do that using CMake?
Currently I could not find a CMake option to turn off the building of Caffe2 sources.
🐛 Bug
Related test runs: https://app.circleci.com/pipelines/github/peterjc123/pytorch_dll_load_smoketests/5/workflows/4acbc28f-a2c4-46c9-94a5-820697652370/jobs/11 https://app.circleci.com/pipelines/github/peterjc123/pytorch_dll_load_smoketests/5/workflows/4acbc28f-a2c4-46c9-94a5-820697652370/jobs/12 https://app.circleci.com/pipelines/github/peterjc123/pytorch_dll_load_smoketests/5/workflows/4acbc28f-a2c4-46c9-94a5-820697652370/jobs/13
To Reproduce
Steps to reproduce the behavior:
conda install -c pytorch-nightly pytorch torchvision
/pip install --pre torch torchvision -f https://download.pytorch.org/whl/nightly/cpu/torch_nightly.html
python -c "from caffe2.python import core"
Expected behavior
Import success.
Environment
Please copy and paste the output from our environment collection script (or fill out the checklist below manually).
You can get the script and run it with:
conda
,pip
, source): conda/pipAdditional context
@ezyang @seemethere
cc @malfet