vision: 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

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About this issue

Original URL
State: closed
Created 3 years ago
Comments: 27 (5 by maintainers)

Most upvoted comments

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 on Jul 19, 2022

Let’s open a new issue for this.

pmeier on Mar 24, 2023

@skroon We are not maintaining the conda forge package. Please raise an error to the team that is: https://github.com/conda-forge/torchvision-feedstock

I can confirm however that 0.2.2 seems to be missing.

❯ conda search -c conda-forge torchvision | grep '0\.2'
torchvision                    0.2.0          py27_0  pkgs/main           
torchvision                    0.2.0          py35_0  pkgs/main           
torchvision                    0.2.0          py36_0  pkgs/main           
torchvision                    0.2.1          py27_0  pkgs/main           
torchvision                    0.2.1          py35_0  pkgs/main           
torchvision                    0.2.1          py36_0  pkgs/main           
torchvision                    0.2.1          py37_0  pkgs/main

pmeier on Mar 23, 2023

I’m not too knowledgeable on conda packaging. Are you saying that marking them as “broken” means even if someone specifies torchvision==0.2.2 in their environment, they can’t be installed? If yes, I agree this is not a good way forward.

Yes, conda works differently here than yanked packages. If a package is marked broken, it cannot be installed even with a hard pin, unless specifying an additional channel that enables installation of packages that have been marked broken, i.e.

# normal case, package not broken
conda install -c conda-forge some_package=some_version

# installing a package that has been marked broken
conda install -c conda-forge -c conda-forge/label/broken some_package=some_version

This is an escape hatch to enable reproducibility even in cases of a package having been marked broken, but it’s not widely known (my impression), and so - de facto - marking builds that have been around a while as broken is equivalent to breaking the reproducibility of any environments that make use of those builds.

h-vetinari on Dec 21, 2022

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/

hmaarrfk on Jul 19, 2022

Another instance is at https://github.com/pytorch/vision/issues/5374

I think it would help a lot of debugging time to simply remove version 0.2.2 from all package managers, it is massively outdated and hides other dependency issues. I think a installation error is preferable to silent installation of such outdated versions

vadimkantorov on Feb 19, 2022

If it’s again a problem with Python 3.10 released and conda trying to use it, can we delete torchvision 0.2.2 from conda altogether? Better have an error than a crippled install

vadimkantorov on Oct 20, 2021