Finetuning-scheduler

Added

- Support for Lightning and PyTorch ``2.3.0``
- Introduced the ``frozen_bn_track_running_stats`` option to the FTS callback constructor, allowing the user to override the default Lightning behavior that disables ``track_running_stats`` when freezing BatchNorm layers. Resolves[13](https://github.com/speediedan/finetuning-scheduler/issues/13).

Deprecated

- removed support for PyTorch `1.13`

Added

- Support for Lightning ``2.2.4`` and PyTorch ``2.2.2``

Added

- Support for Lightning ``2.2.1``

Added

- Support for Lightning and PyTorch ``2.2.0``
- FTS now inspects any base `EarlyStopping` or `ModelCheckpoint` configuration passed in by the user and applies that configuration when instantiating the required FTS callback dependencies (i.e., `FTSEarlyStopping` or `FTSCheckpoint`). Part of the resolution to [12](https://github.com/speediedan/finetuning-scheduler/issues/12).

Changed

- updated reference to renamed `FSDPPrecision`
- increased `jsonargparse` minimum supported version to `4.26.1`

Fixed

- Explicitly `rank_zero_only`-guarded `ScheduleImplMixin.save_schedule` and `ScheduleImplMixin.gen_ft_schedule`. Some codepaths were incorrectly invoking them from non-`rank_zero_only` guarded contexts. Resolved [11](https://github.com/speediedan/finetuning-scheduler/issues/11).
- Added a note in the documentation indicating more clearly the behavior of FTS when no monitor metric configuration is provided. Part of the resolution to [12](https://github.com/speediedan/finetuning-scheduler/issues/12).

Deprecated

- removed support for PyTorch `1.12`
- removed legacy FTS examples

Added

- Support for Lightning ``2.1.4``

Changed

- bumped `sphinx` requirement to `>5.0,<6.0`

Deprecated

- removed deprecated lr `verbose` init param usage
- removed deprecated `tensorboard.dev` references

Added

- Support for Lightning ``2.1.3``