Can I define a deep neural network as an Awkward array of matrices of different sizes? It looks very promising to compute a backpropagation step without ping-ponging with the Python interpreter.
Used Dask for various research experiments and scripts, and it's very good when you have to handle larger-than-memory datasets. When coming to algorithm parallelization, some quirks emerged, and debugging sent me completely nuts. I love Dask, but I think that the problem of parallelizing Python code is not solvable by Dask alone.