GitLab

Fix distributed seeding behavior

This adds workers=True to the Lightning seed_everything function which guarantees different random states across all processes in distributed training. Prior to that some processes on different GPUs with the same worker ID could share the same random state.

Note that this will break reproducibility between runs prior to and after this change.

Also removes the seed and supress_output modules that were not used anymore in OpenFold.

Full multimer merge

Type fixes and README changes for multimer branch

fixed a typo in the readme for soloseq params path

Bumps [actions/setup-python](https://github.com/actions/setup-python) from 4 to 5.
- [Release notes](https://github.com/actions/setup-python/releases)
- [Commits](https://github.com/actions/setup-python/compare/v4...v5

)

---
updated-dependencies:
- dependency-name: actions/setup-python
  dependency-type: direct:production
  update-type: version-update:semver-major
...
Signed-off-by: dependabot[bot] <support@github.com>

fixed a typo in the readme for soloseq params path

Change test_compare_model in deepspeed test to use mean instead of max

Readme changes