releasing 2.0.8

Author: Borda

docs/source-app/levels/basic/build_a_lightning_component.rst

@@ -55,7 +55,7 @@ Organizing your code into Lightning components offers these benefits:
 
  if you know what you are doing, Lightning gives you full control to manage your own
  scaling logic, fault-tolerance and even pre-provisioning, all from Python. We even give you
- full flexibility to use tools like `terraform <../../cloud/customize_a_lightning_cluster.html>`_ to optimize cloud clusters for your Lightning apps.
+ full flexibility to use tools like :doc:`terraform <../../cloud/customize_a_lightning_cluster>` to optimize cloud clusters for your Lightning apps.
 
 .. collapse:: Integrate into your current workflow tools
 

src/lightning/app/CHANGELOG.md

@@ -4,16 +4,13 @@ All notable changes to this project will be documented in this file.
 
 The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
-## [UnREleased] - 2023-08-DD
+## [2.0.8] - 2023-08-29
 
-## Canaged
+## Changed
 
 - Change top folder ([#18212](https://github.com/Lightning-AI/lightning/pull/18212))
-
-
 - Remove `_handle_is_headless` calls in app run loop ([#18362](https://github.com/Lightning-AI/lightning/pull/18362))
 
-
 ### Fixed
 
 - refactor path to root preventing circular import ([#18357](https://github.com/Lightning-AI/lightning/pull/18357))

src/lightning/fabric/CHANGELOG.md

@@ -4,24 +4,17 @@ All notable changes to this project will be documented in this file.
 
 The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
-## [UnReleased] - 2023-08-DD
+## [2.0.8] - 2023-08-29
 
-### Chnaged
+### Changed
 
 - On XLA, avoid setting the global rank before processes have been launched as this will initialize the PJRT computation client in the main process ([#16966](https://github.com/Lightning-AI/lightning/pull/16966))
 
-
 ### Fixed
 
 - Fixed model parameters getting shared between processes when running with `strategy="ddp_spawn"` and `accelerator="cpu"`; this has a necessary memory impact, as parameters are replicated for each process now ([#18238](https://github.com/Lightning-AI/lightning/pull/18238))
-
-
 - Removed false positive warning when using `fabric.no_backward_sync` with XLA strategies ([#17761](https://github.com/Lightning-AI/lightning/pull/17761))
-
-
 - Fixed issue where Fabric would not initialize the global rank, world size, and rank-zero-only rank after initialization and before launch ([#16966](https://github.com/Lightning-AI/lightning/pull/16966))
-
-
 - Fixed FSDP full-precision `param_dtype` training (`16-mixed`, `bf16-mixed` and `32-true` configurations) to avoid FSDP assertion errors with PyTorch < 2.0 ([#18278](https://github.com/Lightning-AI/lightning/pull/18278))
 
 

src/lightning/pytorch/CHANGELOG.md

@@ -5,33 +5,20 @@ All notable changes to this project will be documented in this file.
 The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 
-## [UnRaleased] - 2023-08-DD
+## [2.0.8] - 2023-08-29
 
-### Chnaged
+### Changed
 
 - On XLA, avoid setting the global rank before processes have been launched as this will initialize the PJRT computation client in the main process ([#16966](https://github.com/Lightning-AI/lightning/pull/16966))
-
-
 - Fix inefficiency in rich progress bar ([#18369](https://github.com/Lightning-AI/lightning/pull/18369))
 
-
 ### Fixed
 
 - Fixed FSDP full-precision `param_dtype` training (`16-mixed` and `bf16-mixed` configurations) to avoid FSDP assertion errors with PyTorch < 2.0 ([#18278](https://github.com/Lightning-AI/lightning/pull/18278))
-
-
 - Fixed an issue that prevented the use of custom logger classes without an `experiment` property defined ([#18093](https://github.com/Lightning-AI/lightning/pull/18093))
-
-
 - Fixed setting the tracking uri in `MLFlowLogger` for logging artifacts to the MLFlow server ([#18395](https://github.com/Lightning-AI/lightning/pull/18395))
-
-
 - Fixed redundant `iter()` call to dataloader when checking dataloading configuration ([#18415](https://github.com/Lightning-AI/lightning/pull/18415))
-
-
 - Fixed model parameters getting shared between processes when running with `strategy="ddp_spawn"` and `accelerator="cpu"`; this has a necessary memory impact, as parameters are replicated for each process now ([#18238](https://github.com/Lightning-AI/lightning/pull/18238))
-
-
 - Properly manage `fetcher.done` with `dataloader_iter` ([#18376](https://github.com/Lightning-AI/lightning/pull/18376))
 
 

src/lightning/pytorch/_graveyard/_torchmetrics.py

@@ -17,7 +17,7 @@ def compare_version(package: str, op: Callable, version: str, use_base_version:
 # https://github.com/Lightning-AI/metrics/blob/v0.7.3/torchmetrics/metric.py#L96
 with contextlib.suppress(AttributeError):
  if hasattr(torchmetrics.utilities.imports, "_compare_version"):
- torchmetrics.utilities.imports._compare_version = compare_version
+ torchmetrics.utilities.imports._compare_version = compare_version # type: ignore[assignment]
 
 with contextlib.suppress(AttributeError):
  if hasattr(torchmetrics.metric, "_compare_version"):

src/version.info

@@ -1 +1 @@
-2.0.7
+2.0.8