[example] finetuning CaffeNet on Flickr Style data

This example shows how to fine-tune the BVLC-distributed CaffeNet model on a different dataset: [Flickr Style](http://sergeykarayev.com/files/1311.3715v3.pdf), which has style category labels.
The dataset is distributed as a list of URLs with corresponding labels.
Using a script, we will download a small subset of the data, split it into train and val portinos, and use the ImageDataLayer to load images directly from the filesystem.
How about inline comments to reflect the text? For instance "Reduce base LR 10x from pretraining rate." and so on.