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Versioning Policy Update #21073

@speediedan

Description

@speediedan

Outline & Motivation

Firstly, thanks to Lightning team for your continued hard work and invaluable contributions to the open-source ecosystem!

As a follow-up to this issue, I’ve noticed that recent Lightning minor releases are no longer synchronized with PyTorch’s minor releases as they have been in the past:

PyTorch Version Release Date Release Artifact Lightning Version Release Date Release Artifact Lag (weeks: Lightning - PyTorch)
2.0 Mar 15, 2023 PyTorch 2.0.0 2.0.0 Mar 15, 2023 Lightning 2.0.0 0
2.1 Oct 4, 2023 PyTorch 2.1.0 2.1.0 Oct 12, 2023 Lightning 2.1.0 1
2.2 Jan 30, 2024 PyTorch 2.2.0 2.2.0 Feb 7, 2024 Lightning 2.2.0 1
2.3 Apr 24, 2024 PyTorch 2.3.0 2.3.0 Jun 13, 2024 Lightning 2.3.0 7 (50 days)
2.4 Jul 24, 2024 PyTorch 2.4.0 2.4.0 Aug 7, 2024 Lightning 2.4.0 2 (14 days)
2.5 Oct 17, 2024 PyTorch 2.5.0 2.5.0 Dec 20, 2024 Lightning 2.5.0 9 (64 days)
2.6 Jan 29, 2025 PyTorch 2.6.0 28 (197 days)
2.7 Apr 23, 2025 PyTorch 2.7.0 16 (113 days)
2.8 Aug 6, 2025 PyTorch 2.8.0 1 (8 days)

Pitch

I think both users and maintainers of downstream packages depending on Lightning (I'm the primary maintainer of a downstream Lightning package Fine-Tuning Scheduler) would benefit if this apparent versioning policy/cadence change were made explicit in the versioning documentation.

Can we update the versioning policy to clarify the current minor release policy/cadence for Lightning? E.g., 'minor releases are typically driven by key upstream PyTorch deprecations etc...' This would help the community better plan dependencies and upgrades.

Additional context

As a concrete example, Fine-Tuning Scheduler has a number of deprecations and enhancements aligned with various PyTorch minor versions that have been awaiting a Lightning minor release. If the release cadence of the last year is expected to be the new approach moving forward, it would be good to know so FTS can proceed with changing its release approach from being Lightning release synchronized to a PyTorch release alignment instead.
Thanks again!

@Borda @lantiga @iwr-redmond

cc @lantiga @Borda @justusschock

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