GoogLeNet training in Caffe

This is the GoogLeNet (as devised by Szegedy at al) train/test definition in Caffe I did as part of my work at Superfish Ltd.

I've trained it on large scale dataset we have here at Superfish and it's very robust. The attached solver is a default one. One can go ahead and follow the original paper for a more specific implementation of the solver.

The network definition is a bit cumbersome, one might want to implement an Inception module to make things simpler.

I did my best to follow the original paper.
 
Add `loss_weight: 0.3`

From [the paper](http://arxiv.org/abs/1409.4842) (page 6):

> During training, their loss gets added to the total loss of the network with a discount weight (the losses of the auxiliary classifiers were weighted by 0.3).