Helios-ml

Breaking Changes
* Dependencies have been updated. Please see the README for more information.
* Helios now requires a minimum NumPY version of 2.0.0.
* The `TrainingState` struct was previously saved in checkpoints as a dictionary. This has now been changed to save the struct itself, so you **must** migrate your checkpoints to the new system.

Feature Changes
* Introduces a new plug-in system to extend the functionality of Helios.
* Introduces a new `safe_torch_load` function that wraps `torch.load` with `weights_only` set to true. This addresses the warnings coming from PyTorch starting with 2.4.0.
* Introduces a way to have the trainer ignore certain exception types when training so they can be caught by the calling code.
* Adds a multi-processing queue to the trainer (available only in distributed mode) that allows data to be passed back to the main process.
* Adds native integration with Optuna through the new `OptunaPlugin`.
* Adds a new `CUDAPlugin` that automatically moves batches to the set GPU device.
*

Bug Fixes
* When setting both CPU and GPU for the trainer, an exception is now raised instead of silently ignoring the CPU flag.
* Unit tests are now expanded to cover all supported versions of Python.
* Protobuf is no longer fixed to be less than 5.0.0.

First official release of Helios

Updates
* Adds new unit tests to ensure device and map locations are correct.
* Adds a way to add text to the default Helios banner.
* Adds a tool to migrate checkpoints created by previous versions of Helios.
* Cleans up and updates all documentation

Breaking Changes
* Checkpoints created with prior versions of Helios will no longer work. You may migrate them to the latest version using `python -m helios.chkpt_migrator <chkpt-root>`

Full Changelog
https://github.com/marovira/helios-ml/compare/0.3.0...1.0.0

Updates

* Adds a new set of callbacks to the `Model` class that are called at the start/end of each epoch.
* Adds a way to set a custom `collate_fn` for the dataloader.
* The `Model` no longer contains abstract methods.
* Changes the call site of `model.on_training_start` so print statements don't interfere with the progress bar.
* Extend the list of optimizers and schedulers so all the ones provided by PyTorch are registered by default.
* Extend the `should_training_stop` functionality to allow breaking out of the loop after a training step.
* Adds documentation with Sphinx.
* Allow `__version__` to be directly imported from the `helios` package.

Breaking Changes
* `ToTensor` has been renamed as `ToImageTensor` in order to be more explicit about what the class does.

Full Changelog
https://github.com/marovira/helios-ml/compare/0.2.0...0.3.0

Updates
* Fixes the way epochs are numbered. This should ensure that all epoch counts are now consistent with each other regardless of training type.
* Fixes an issue where training with iterations and gradient accumulation resulted in half iterations being run after training should've stopped.
* Removes F1, recall, and precision metrics. The implementations were not generic enough to be shipped with Helios.
* Refactors the MAE implementation to make it more generic in terms of the types of tensors it accepts.
* Adds a numpy version of MAE.

Full Changelog
https://github.com/marovira/helios-ml/compare/0.1.9...0.2.0

Update
* Adds a flag to disable the printing of the banner.

Full Changelog
https://github.com/marovira/helios-ml/compare/0.1.8...0.1.9

Updates
* Allow easy access to the datasets held by the `DataModule`. Previously there was no direct way of accessing them without having to go through the private members of the `DataModule`. This complicated certain cases where the length of the dataset was required.
* Added a way to halt training based on arbitrary conditions. The main use-case for this is to allow the `Model` sub-classes to halt training when the trained network has converged to a value or if the network is diverging and there's no reason to continue.
* Addresses a potential crash that occurs whenever training occurs on a `None` checkpoint path.

Full Changelog
https://github.com/marovira/helios-ml/compare/0.1.7...0.1.8