Does Dask-ML support Custom Transformers to Use in Pipeline?

Thanks for this awesome project!

I have a scikit-learn pipeline combining some custom transformers for feature-engineering with a classifier at the end (xgboost). Does Dask-ML accept user-defined pipeline step/classes like Sklearn does? If so, what are the requirements (e.g. "implement fit, transform, and return a Dask Dataframe?")

And are there any classes a Dask-ML pipeline step should inherit from (e.g. in sklearn all my custom transforms inherit from `BaseEstimator` in order to get `get_params`... see: https://stackoverflow.com/a/39093021/1870832)

The Dask-ML docs are pretty great in general but I couldn't find an answer or example on this. Sorry if I'm missing it somewhere.