Every design activity involves mixing and matching things
and doing so repeatedly until you have achieved the desired
goals.  The same thing is true of modern deep learning
networks.  When you are working with a new data domain, it
is likely that you would want to experiment with different
network layouts that may be a product of your own mind or
that you may have seen elsewhere in some publication or in
some webpage.

The goal of this module is to make it easier to engage in
this process.  The idea is that you should be able to drop
in a new network and, assuming that you are able to use,
say, the Torchvision data loaders, you should be able to see
right away the results with the new network.

This module also allows you to specify a network with just a
configuration string.  The module parses the string and
creates the network.

I expect this module to grow with new capabilities every
time I teach our Deep Learning class.  As currently
scheduled, this class will be taught in the Spring semester
of every year.
    
