Do snapshot after computing loss and test accuracy
Merge pull request #51 from sguada/solver_test

Do snapshot after computing loss and test accuracy
default power_wrapper batch size to 10 (aeca741a69 cont'd)

default command line arg and function arg to 10
remove global BATCH_SIZE in favor of arg
give batch size efficiency advice
compute pixelwise gradients w.r.t. to classes
classify + localize, with notebook

- define nets for classification and gradient backprop on imagenet 1k
- given an image, classify then compute pixelwise gradients w.r.t.
  top activation
- demo in notebook
drop deprecated compute_gradients()
input + output pd data frames, adopt compute_feats_grads
stow gradient localization demo with other notebooks