ADC (Automatic Deep Compression) example + features, tests, bug fixes (#28)

This is a merge of the ADC branch and master.
ADC (using a DDPG RL agent to compress image classifiers) is still WiP and requires
An unreleased version of Coach (https://github.com/NervanaSystems/coach).

Small features in this commit:
-Added model_find_module() - find module object given its name
- Add channel ranking and pruning: pruning/ranked_structures_pruner.py
- Add a CIFAR10 VGG16 model: models/cifar10/vgg_cifar.py
- Thinning: change the level of some log messages – some of the messages were
moved to ‘debug’ level because they are not usually interesting.
- Add a function to print nicely formatted integers - distiller/utils.py
- Sensitivity analysis for channels-removal
- compress_classifier.py – handle keyboard interrupts
- compress_classifier.py – fix re-raise of exceptions, so they maintain call-stack

-Added tests:
-- test_summarygraph.py: test_simplenet() - Added a regression test to target a bug that occurs when taking the predecessor of the first node in a graph
-- test_ranking.py - test_ch_ranking, test_ranked_channel_pruning
-- test_model_summary.py - test_png_generation, test_summary (sparsity/ compute/model/modules)

- Bug fixes in this commit:
-- Thinning bug fix: handle zero-sized 'indices' tensor
During the thinning process, the 'indices' tensor can become zero-sized,
and will have an undefiend length. Therefore, we need to check for this
situation when assessing the number of elements in 'indices'
-- Language model: adjust main.py to new distiller.model_summary API