- Moved the Language model and struct pruning tutorials from the Wiki to
the HTML documentation.  Love the ease of Wiki, but GitHub doesn't let
Google crawl these pages, and users can't open PRs on Wiki pages.

- Updated the pruning algorithms documentation

* A temporary fix for issue 36

The thinning code assumes that the sgraph it is using
is not data-parallel, because it (currently) accesses the
layer-name keys using a "normalized" name ("module." is removed).

The bug is that in thinning.py#L73 we create a data_parallel=True
model; and then give it to sgraph.
But in other places thinning code uses "normalized" keys.  For
example in thinning.py#L264.

The temporary fix configures data_parallel=False in thinning.py#L73.

A long term solution should have SummaryGraph know how to handle
both parallel and not-parallel models.  This can be done by having
SummaryGraph convert layer-names it receives in the API to
data_parallel=False using normalize_layer_name.  When returning
results, use the de-normalized format.

* Fix the documentation error from issue 36
* Move some logs to debug and show in logging.conf how to enable DEBUG logs.

* Implemented as a Policy
* Integrated in image classification sample
* Updated docs and README