News

Unreleased

Added

Support for Optimisers.jl #114.

[0.3.0] - 04.04.2022

Added

Short-hand Learner method Learner(model, lossfn[; data, optim, callbacks, kwargs...]). The old method still exists but use is discouraged.
Compatibility with Flux.jl v0.13 once released
Pollen.jl doucmentation frontend

Changed

(BREAKING) Hyperparameter scheduling now uses ParameterSchedules.jl instead of Animations.jl for defining schedules. See the docs.
Fixes on documentation pages

[0.2.0]

Added

New training loop API that is easier to extend. Defining a Phase and step! is all you need. See the new tutorial and the new reference.
- Relevant functions: epoch!, step!, runstep, runepoch
Added CHANGELOG.md (this file)
AbstractValidationPhase as supertype for validation phases
Documentation for callback helpers on reference page

Changed

Batch* renamed to Step*:
- events: BatchBegin now StepBegin, BatchEnd now StepEnd
- CancelBatchException now CancelStepException.
- field Learner.batch now Learner.step
Learner.step/batch is no longer a special struct but now a PropDict, allowing you to set arbitrary fields.
Learner.model can now be a NamedTuple/Tuple of models for use in custom training loops. Likewise, learner.params now resembles the structure of learner.model, allowing separate access to parameters of different models.
Callbacks
- Added init! method for callback initilization, replacing the Init event which required a Phase to implement.
- Scheduler now has internal step counter and no longer relies on Recorder's history. This makes it easier to replace the scheduler without needing to offset the new schedules.
- EarlyStopping callback now uses criteria from EarlyStopping.jl

Removed

Removed old training API. Methods fitbatch!, fitbatchphase!, fitepoch!, fitepochphase! have all been removed.