joblib parallel_backend with dask resources
As of 2019-02-19, there is no way to do this.
Whenever I submit a dask task, I can specify the requisite resources for that task.  e.g. client.submit(process, d, resources={'GPU': 1})
However, If I abstract my dask scheduler away as a joblib.parallel_backend, it is not clear how to specify resources when I do so.
How do I call joblib.parallel_backend('dask') and still specify requisite resources?