Taiyaki

Version numbers: major.minor.patch

Major version bump indicates a substantial change, e.g. file formats or removal of functionality.
Minor version bump indicates a change in functionality that may affect users.
Patch version bump indicates bug-fixes or minor improvements not expected to affect users.

v5.3.0

Based on pytorch version 1.5
Acceleration loss function lead to signifcant performance improvement
Many bug fixes

v5.0.0

Based on pytorch version 1.2
Improved training stability: gradient capping and warm-up
Merged mod-base and canonical entry points
- Custom model definitions should now take an alphabet_info argument rather than outsize
Improved RNA support: tools can reverse references and basecalls
Basecaller changes:
- chunk size argument now matches guppy
- CPU calling enabled
- lower memory usage
Multi-GPU training enabled
Bug fixes

v4.1.0

Ab initio ("bootstrap") training of models

v4.0.0

Modified base training and basecalling
Minor changes to input format to trainer, use misc/upgrade_mapped_signal.py to upgrade old data

v3.1.0

Basecaller script that uses GPU
Training walk-through
Tweaks to optimisation parameters

v3.0.2

Improved training parameters
Use orthonormal initialisation of starting weights

v3.0.1

Bug fix: package version did not work in github's source releases

v3.0.0

Initial release:

Prepare data for training basecallers by remapping signal to reference sequence
Train neural networks for flip-flop basecalling and squiggle prediction
Export basecaller models for use in Guppy