v3.5.1

Support for training and exporting DDSP-VST models.
Fixes to build.

v3.1.0

Major fixes to loudness/power calculations, and standardized padding (center/same/valid). Dataset loaders allow for centered datasets.
Breaks loading/training on older models (twice --> v3), but important to get straightened out before VST release.

v1.9.0

What's Changed

• Inference models for VST by @copybara-service in #403
• Add UrmpMidiUnbatched for unsegmented tfrecords in ddsp.training.data. by @lukewys in #404
• Fix aliasing in streaming synthesis. by @copybara-service in #408
• Add Viterbi decoding to PretrainedCREPE, allows hmm decoding during training. by @copybara-service in #406

Full Changelog: v1.7.0...v1.9.0

v1.7.0

• MultiDatasetProvider
• Default upload() to mix down to mono for timbre_transfer
• OnlinePreprocessor
• Small changes for compatibility with MIDI-DDSP

v1.6.2

• Replace "master" branch with "main"
• Move dataset statistics from colab_utils to postprocessing. NB: dataset statistics files will need be regenerated for any models trained before this release.
• Several small changes for the VST plugin (named outputs of saved model, adding metadata to tflite models, gin config for VST).

v1.3.0

Updated SavedModels interface. Scripts for conversion of SavedModels to TFLite and TFJS. Updates to data preparation pipeline to handle very long input files, and enable creating train / eval splits.

v1.2.0

Fix bug in DictLayer / PowerPreprocessor that could not handle multiple optional tensors in the call() input signature.

v1.1.0

• Common Base Class for inference models
• Option for different amplitude interpolation on Harmonic synth

v1.0.0

Major (breaking) change

• New base classes
  • ProcessorGroup and LossGroup inherit from DAGLayer (dags.py)
  • All ddsp.training layers [decoders, encoders, preprocessors] inherit from DictLayer (nn.py)
• Renamed classes to more precise terms
  • Additive -> Harmonic
  • DefaultPreprocessor -> F0LoudnessPreprocessor
  • TranscribingAutoencoder -> Inverse Synthesis
• New experimental MidiAutoencoder model (WIP)
• Evaluator classes in eval_util (now configurable from gin instead of a big long series of if statements)
• Minor bug fixes

v0.14.0 (breaking change)

• Cloud training scripts
• Model API refactor (no more model.get_controls(), model() now returns a dictionary of output tensors instead of audio. Audio can be retrieved with model.get_audio_from_outputs(outputs)
• Separate files for each model
• Minor bug fixes