Ddsp

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

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

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

* 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

Release for reproducing the results from the 2020 ICML SAS workshop paper (https://openreview.net/forum?id=RlVTYWhsky7).

WIP code from the paper added with EXPERIMENTAL disclaimers.
Gin configs and details provided in `ddsp/training/gin/papers/icml2020`

v.0.10.0
* Custom cumsum operation to avoid phase accumulation errors for generating long sequences.
* Script to automatically update old gin configs.