Upload the metadata file for wheels for pep658 https://peps.python.org/pep-0658/ Using a python script but using bash might be easier... -- Testing Example run https://github.com/pytorch/pytorch/actions/runs/12550595201/job/34994883276 without actual upload, just dry run Lightly tested the script to make sure it uploads to s3, but integration with the bash script + workflow is untested Pull Request resolved: https://github.com/pytorch/pytorch/pull/143677 Approved by: https://github.com/seemethere |
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|---|---|---|
| .. | ||
| anaconda-prune | ||
| promote | ||
| apply-release-changes.sh | ||
| cut-release-branch.sh | ||
| README.md | ||
| restore-backup.sh | ||
| tag-docker-images.sh | ||
| upload_metadata_file.py | ||
PyTorch Release Scripts
These are a collection of scripts that are to be used for release activities.
NOTE: All scripts should do no actual work unless the
DRY_RUNenvironment variable is set todisabled. The basic idea being that there should be no potential to do anything dangerous unlessDRY_RUNis explicitly set todisabled.
Requirements to actually run these scripts
- AWS access to pytorch account
- Access to upload conda packages to the
pytorchconda channel - Access to the PyPI repositories
Promote
These are scripts related to promotion of release candidates to GA channels, these can actually be used to promote pytorch, libtorch, and related domain libraries.
Usage
Usage should be fairly straightforward and should actually require no extra variables if you are running from the correct git tags. (i.e. the GA tag to promote is currently checked out)
PACKAGE_TYPE and PACKAGE_NAME can be swapped out to promote other packages.
Promoting pytorch wheels
promote/s3_to_s3.sh
Promoting libtorch archives
PACKAGE_TYPE=libtorch PACKAGE_NAME=libtorch promote/s3_to_s3.sh
Promoting conda packages
promote/conda_to_conda.sh
Promoting wheels to PyPI
WARNING: These can only be run once and cannot be undone, run with caution
promote/wheel_to_pypi.sh
Restoring backups
All release candidates are currently backed up to s3://pytorch-backup/${TAG_NAME} and
can be restored to the test channels with the restore-backup.sh script.
Which backup to restore from is dictated by the RESTORE_FROM environment variable.
Usage
RESTORE_FROM=v1.5.0-rc5 ./restore-backup.sh