v0.2.0 release with TF static graph optimization

Highlights

The following aspects of ngc-learn were revamped/revised (the list is not exhaustive):

• the ngc graph and projection graph simulation objects, as well as all nodes and cables, were revised to utilize a ".compile()" routine to allow for Tensorflow 2 static graph optimized calculations (as well as to generate "property" hash tables to allow post-compilation examination). Internal modules, such as nodes, now use in-place memory calculations to further speed up simulation (a 5-7.5 times simulation speed improvement was observed) and elements of cables, such as the symbol flags used to indicate what type of transformation is to be applied have been edits (for example, in the shared_param_path, "symm_tied" is now "A^T" and the "point_to" argument has been folded into shared_param_path where direct synapse sharing is indicated simply with the symbol "A")
• documentation was added/improved (and edited to reflect the API alterations), and two new demonstrations/tutorials (Demonstrations 4 and 5) were included (see both docs and examples/)
• node and cable system internally rewritten (with only a few alterations to the surface-level API) to better facilitate future expansions and community contributions
• community guidelines was built/published