Drop torchvision 0.2.2 from conda-forge as it's often a silent indicator of major package conflicts

🐛 Describe the bug

Running the following triggers install of torchvision 0.2.2.

We need a stable conda install recipes and suggestions that deal with common bugged dependencies such as OpenCV and ffmpeg given all the mess with glibc / python versions etc. At least some known working commands (even if not the latest python).

I understand that it can’t be the job of pytorch maintainers to test all conda packages, but the combination of torch / opencv / ffmpeg (also maybe some packages for 3d vision) is super-common one. If someone succeeds in installing them together, it is super-valuable to collect and publish these experiences. Or maybe some mamba recipes?

cc @malfet

PREFIX=/path/lab/vadim/prefix
mkdir -p $PREFIX

curl -L -so $PREFIX/miniconda.sh https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh && chmod +x $PREFIX/miniconda.sh && $PREFIX/miniconda.sh -b -p $PREFIX/miniconda && rm $PREFIX/miniconda.sh

export PATH=$PREFIX/miniconda/bin:$PATH

conda install -y opencv pytorch torchvision cudatoolkit=11.1 -c pytorch -c conda-forge

Versions

N/A

[hmaarrfk]

severe package conflicts and is always an indication/cover-up/hiding of larger problems

Correct.

I am sympathetic with your challenges. I wanted to bring attention that you are likely asking the wrong community for help.

In either case, you did get the attention of the conda-forge community (myself). If you do raise an issue at conda-forge, my first ask would be to check that it still occurs today (I patched up a few releases) and likely submit a patch to mentionned repository in the link i sent you asking me to review.

Ultimately, I do think it is important that Meta/Facebook/Pytorch be aware that users are using conda-forge and that it may be useful for them to help maintain it.

[hmaarrfk]

That is an opinion. But people are moving toward making science more reproducible, and “pulling” packages is somewhat counter to that.

~We~ conda-forge (we) have guidelines on how to deal with broken packages, and generally conda-forge has solutions, for this, outlined https://conda-forge.org/docs/orga/guidelines.html?highlight=broken#fixing-broken-packages

I guess ultimately, conda-forge and pytorch are two different community organizations. I was mostly trying to point to maybe a more sustainable collaborations. I’m not sure what your affiliation is vadimkantorov but if you are speaking about the conda-forge channel, I think you want to cross reference your issue on https://github.com/conda-forge/pytorch-cpu-feedstock/