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[M1] Install "jpeg<=9b" rather than OpenJpeg #6122
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SGTM
Hey @malfet! You merged this PR, but no labels were added. The list of valid labels is available at https://github.com/pytorch/vision/blob/main/.github/process_commit.py |
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Summary: Explicitly set PATH to point to `conda` binary, otherwise libjpeg detection logic does not work Pin libjpeg to the same version on x86 and m1 Add simple tests that jpeg can be decoded by a generated wheel Reviewed By: NicolasHug Differential Revision: D36931836 fbshipit-source-id: d8a3bcc4f7ec513b95cd325e33bdf2aa695500e4
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Explicitly set PATH to point to `conda` binary, otherwise libjpeg detection logic does not work Pin libjpeg to the same version on x86 and m1 Add simple tests that jpeg can be decoded by a generated wheel
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* Add M1 wheels binary builds (#5948) * [M1] Set build version and delocate wheels (#6110) This would package libpng and libjpeg.dylib into wheel files Add a very simple test step, copied from https://github.com/pytorch/pytorch.github.io/blob/1eaa33a3d3f1b83b64c5031c6dd04dbb238d6105/scripts/test_install.py#L78 Cherry-picked from https://github.com/pytorch/builder/blob/d0bc74cc363a9da5a8b6a40e883d40d25d050036/build_m1_domains.sh#L22 * [BE] Unify version computation (#6117) * [BE] Unify version computation Instead of hardcoding dev version in various script, use one from `version.txt` if `setup_build_version` is called without arguments Also, pass `--pre` option to M1 build/test pip install commands to build TorchVision against nightly pytorch * Pin torchvision dependency to a specific pytorch version * [M1] Install "jpeg<=9b" rather than OpenJpeg (#6122) Explicitly set PATH to point to `conda` binary, otherwise libjpeg detection logic does not work Pin libjpeg to the same version on x86 and m1 Add simple tests that jpeg can be decoded by a generated wheel * Add unit-tests for M1 (#6132) * Add M1 testing job * libjpeg -> jpeg<=9b in test-m1.yml * Added export PATH=~/miniconda3/bin... from 6122 * Tests were OK, let's see if we can remove the pinning * GH: Add M1 conda build workflows (#6135) Clean up Conda build folder before every run Enable artifact upload to GitHub for every workflow run, but upload to Conda/S3 only on nightly pushes Test plan: `conda install -c pytorch-nightly torchvision; python -c "import torchvision;print(torchvision.io.read_image('hummingbird.jpg').shape)"` * Fix `Test M1` workflow By passing `--pre` option to `pip install`, otherwise torchvision were always tested against last PyTorch release * Adding tagged builds for M1 (#6140) * Adding tagged builds * Testing * Testing * Testing * Testing * Adding conda builds * Fix `if` condition for s3/conda uploads (#6146) Replace `steps.extract_branch.outputs.branch` (which were probably taken from https://stackoverflow.com/questions/58033366/how-to-get-the-current-branch-within-github-actions ) with straightforward `github.event.ref` Tested in https://github.com/malfet/deleteme/runs/6822647720?check_suite_focus=true and https://github.com/malfet/deleteme/runs/6822691158?check_suite_focus=true * Fix typo in GHA nightly build condition (#6158) s#ref/heads/#refs/heads/# I should have noticed it while copy-n-pasting the condition. Unfortunately there are no way to test is other than in prod, but nightly builds are still not getting pushed, see https://github.com/pytorch/vision/runs/6860407007?check_suite_focus=true for example * Making sure we are building against release * Testing Testing Testing Testing testing Testing Testing Testing Testing Testing Testing Testing * Testing * Testing * Cleanup * Refactoring logic Co-authored-by: Nikita Shulga <nshulga@fb.com> Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>
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