* initial public refactor

* add uniform

* simplify code

* split uniform-factor

* fix prior

* working version

* more documentation

* clean up done for InfoGAN

* updated other examples to match changes in GAN.py

* final edits from my side

* docs changes in base class

* more docs and interface name

* some changes in name scope and docs

* use property for _dim

* visualization & gradient scale according to the paper

* update the demo img

* Add example for several embedding methods

This also includes an animate script using avconv and app-util to
reduce repeating code (DRY).

* some docs

* use average for cosine-loss. add some math.

* move data to embedding_data.py; fix inference

* simplify data code

* Change rnn-cell to fix #103

* Add example for extracting saliency using ResNet-50 with tfSlim

* use existing mean. document the symbolic functions

* move function out of utils.py

* further simplify code. move saliency back to symbolic_functions.

* rename the script. add stacked demo image.

* remove cat.jpg

Use travis-ci to run some tests under the latest release of
TensorFlow and nightly releases in python 2.7 and 3.5.

Add PrintData to verify the shapes of incoming data from the dataflow it is good
to actually output them for debugging reasons.