Add MDN with support for parameter transformations

[Álvaro Tejero-Cantero]

Building on Marcel's work, add an MDN (Mixture Density Network) implementation that can play well with e.g. SNPE-A proposal posterior corrections.

This is the wishlist

• basic MDN that works and is useable from sbi (mixture of full-covariance Gaussians)
• MDN becomes highly compositional - only last layer implemented (MDN layer), the rest is built e.g. using Sequential and possibly heuristics given data dimensions, etc.
• MDN layer returns a MixtureSameFamily density (becoming part of PyTorch, PR)
• (long term) MDN layer can self-configure given the particulars of the desired MixtureSameFamily
• Building the whole MDN does not require specification of redundant information, much like Keras s sequential (or look at thinc for a more functional take).