Release 2.3.0 (#19954)

Author: awaelchli

src/lightning/data/README.md

@@ -15,7 +15,7 @@ We developed `StreamingDataset` to optimize training of large datasets stored on
 
 Specifically crafted for multi-gpu & multi-node (with [DDP](https://lightning.ai/docs/pytorch/stable/accelerators/gpu_intermediate.html), [FSDP](https://lightning.ai/docs/pytorch/stable/advanced/model_parallel/fsdp.html), etc...), distributed training with large models, it enhances accuracy, performance, and user-friendliness. Now, training efficiently is possible regardless of the data's location. Simply stream in the required data when needed.
 
-The `StreamingDataset` is compatible with any data type, including **images, text, video, audio, geo-spatial, and multimodal data** and it is a drop-in replacement for your PyTorch [IterableDataset](https://pytorch.org/docs/stable/data.html#torch.utils.data.IterableDataset) class. For example, it is used by [Lit-GPT](https://github.com/Lightning-AI/lit-gpt/blob/main/pretrain/tinyllama.py) to pretrain LLMs.
+The `StreamingDataset` is compatible with any data type, including **images, text, video, audio, geo-spatial, and multimodal data** and it is a drop-in replacement for your PyTorch [IterableDataset](https://pytorch.org/docs/stable/data.html#torch.utils.data.IterableDataset) class. For example, it is used by [Lit-GPT](https://github.com/Lightning-AI/lit-gpt/blob/main/litgpt/data/tinyllama.py) to pretrain LLMs.
 
 <br/>
 
@@ -284,7 +284,7 @@ for batch in tqdm(train_dataloader):
 
 Lightning Data provides a stateful `StreamingDataLoader`. This simplifies resuming training over large datasets.
 
-Note: The `StreamingDataLoader` is used by [Lit-GPT](https://github.com/Lightning-AI/lit-gpt/blob/main/pretrain/tinyllama.py) to pretrain LLMs. The statefulness still works when using a mixture of datasets with the `CombinedStreamingDataset`.
+Note: The `StreamingDataLoader` is used by [Lit-GPT](https://github.com/Lightning-AI/lit-gpt/blob/main/litgpt/data/tinyllama.py) to pretrain LLMs. The statefulness still works when using a mixture of datasets with the `CombinedStreamingDataset`.
 
 ```python
 import os

src/lightning/fabric/CHANGELOG.md

@@ -5,63 +5,33 @@ 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] - 2024-MM-DD
+## [2.3.0] - 2024-06-13
 
 ### Added
 
 - Added sanitization for classes before logging them as hyperparameters ([#19771](https://github.com/Lightning-AI/pytorch-lightning/pull/19771))
-
 - Enabled consolidating distributed checkpoints through `fabric consolidate` in the new CLI ([#19560](https://github.com/Lightning-AI/pytorch-lightning/pull/19560))
-
 - Added the ability to explicitly mark forward methods in Fabric via `_FabricModule.mark_forward_method()` ([#19690](https://github.com/Lightning-AI/pytorch-lightning/pull/19690))
-
 - Added support for PyTorch 2.3 ([#19708](https://github.com/Lightning-AI/pytorch-lightning/pull/19708))
-
 - Added `ModelParallelStrategy` to support 2D parallelism ([#19846](https://github.com/Lightning-AI/pytorch-lightning/pull/19846), [#19852](https://github.com/Lightning-AI/pytorch-lightning/pull/19852), [#19870](https://github.com/Lightning-AI/pytorch-lightning/pull/19870), [#19872](https://github.com/Lightning-AI/pytorch-lightning/pull/19872))
-
 - Added a call to `torch.distributed.destroy_process_group` in atexit handler if process group needs destruction ([#19931](https://github.com/Lightning-AI/pytorch-lightning/pull/19931))
-
 - Added support for configuring hybrid-sharding by passing a tuple for the `FSDPStrategy(device_mesh=...)` argument ([#19504](https://github.com/Lightning-AI/pytorch-lightning/pull/19504))
 
-
 ### Changed
 
 - Renamed `lightning run model` to `fabric run` ([#19442](https://github.com/Lightning-AI/pytorch-lightning/pull/19442), [#19527](https://github.com/Lightning-AI/pytorch-lightning/pull/19527))
-
-
 - The `Fabric.rank_zero_first` context manager now uses a barrier without timeout to avoid long-running tasks to be interrupted ([#19448](https://github.com/Lightning-AI/lightning/pull/19448))
-
-
 - Fabric now raises an error if you forget to call `fabric.backward()` when it is needed by the strategy or precision selection ([#19447](https://github.com/Lightning-AI/lightning/pull/19447), [#19493](https://github.com/Lightning-AI/lightning/pull/19493))
-
-
 - `_BackwardSyncControl` can now control what to do when gradient accumulation is disabled ([#19577](https://github.com/Lightning-AI/lightning/pull/19577))
 
-
-### Deprecated
-
--
-
--
-
--
-
 ### Removed
 
 - Removed support for PyTorch 1.13 ([#19706](https://github.com/Lightning-AI/lightning/pull/19706))
 
--
-
--
-
 ### Fixed
 
 - Fixed a matrix shape mismatch issue when running a model loaded from a quantized checkpoint (bitsandbytes) ([#19886](https://github.com/Lightning-AI/lightning/pull/19886))
 
--
-
--
-
 
 ## [2.2.2] - 2024-04-11
 

src/lightning/pytorch/CHANGELOG.md

@@ -4,65 +4,36 @@ 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] - 2024-MM-DD
+## [2.3.0] - 2024-06-13
 
 ### Added
 
 - The `ModelSummary` and `RichModelSummary` callbacks now display the training mode of each layer in the column "Mode" ([#19468](https://github.com/Lightning-AI/lightning/pull/19468))
-
 - Added `load_from_checkpoint` support for `LightningCLI` when using dependency injection ([#18105](https://github.com/Lightning-AI/lightning/pull/18105))
-
 - Added robust timer duration parsing with an informative error message when parsing fails ([#19513](https://github.com/Lightning-AI/pytorch-lightning/pull/19513))
-
 - Added `on_exception` hook to `LightningDataModule` ([#19601](https://github.com/Lightning-AI/pytorch-lightning/pull/19601))
-
 - Added support for PyTorch 2.3 ([#19708](https://github.com/Lightning-AI/pytorch-lightning/pull/19708))
-
 - Added `ModelParallelStrategy` to support 2D parallelism ([#19878](https://github.com/Lightning-AI/pytorch-lightning/pull/19878), [#19888](https://github.com/Lightning-AI/pytorch-lightning/pull/19888))
-
 - Added a call to `torch.distributed.destroy_process_group` in atexit handler if process group needs destruction ([#19931](https://github.com/Lightning-AI/pytorch-lightning/pull/19931))
-
 - Added support for configuring hybrid-sharding by passing a tuple for the `FSDPStrategy(device_mesh=...)` argument ([#19504](https://github.com/Lightning-AI/pytorch-lightning/pull/19504))
 
-
 ### Changed
 
 - The `prepare_data()` hook in `LightningModule` and `LightningDataModule` is now subject to a barrier without timeout to avoid long-running tasks to be interrupted ([#19448](https://github.com/Lightning-AI/lightning/pull/19448))
-
 - Relaxed the requirement for custom batch samplers to expose `drop_last` for prediction ([#19678](https://github.com/Lightning-AI/pytorch-lightning/pull/19678))
-
 - It is no longer allowed to skip `training_step()` by returning `None` in distributed training ([#19918](https://github.com/Lightning-AI/pytorch-lightning/pull/19918))
 
-
-### Deprecated
-
--
-
--
-
--
-
 ### Removed
 
 - Removed the Bagua integration (`Trainer(strategy="bagua")`) ([#19445](https://github.com/Lightning-AI/lightning/pull/19445))
-
 - Removed support for PyTorch 1.13 ([#19706](https://github.com/Lightning-AI/lightning/pull/19706))
 
--
-
 ### Fixed
 
 - Fixed a matrix shape mismatch issue when running a model loaded from a quantized checkpoint (bitsandbytes) ([#19886](https://github.com/Lightning-AI/lightning/pull/19886))
-
-
 - Fixed `WandbLogger.log_hyperparameters()` raising an error if hyperparameters are not JSON serializable ([#19769](https://github.com/Lightning-AI/pytorch-lightning/pull/19769))
-
-
 - Fixed an issue with the LightningCLI not being able to set the `ModelCheckpoint(save_last=...)` argument ([#19808](https://github.com/Lightning-AI/pytorch-lightning/pull/19808))
-
 - Fixed an issue causing ValueError for certain object such as TorchMetrics when dumping hyperparameters to YAML ([#19804](https://github.com/Lightning-AI/pytorch-lightning/pull/19804))
-
-
 - Fixed resetting `epoch_loop.restarting` to avoid full validation run after `LearningRateFinder` ([#19818](https://github.com/Lightning-AI/pytorch-lightning/issues/19818))
 
 

src/version.info

@@ -1 +1 @@
-2.3.0dev
+2.3.0