return

TEX = pdflatex -interaction nonstopmode
BIB = bibtex
GS = gs -q -dNOPAUSE -dBATCH -sDEVICE=pdfwrite 

COVER = cover
PAPER = paper_main
SUPP = paper_supp
BIBFILE = temp.bib
BUNDLE = paper_bundle.pdf

return

##VGG16 model for Keras

This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.

It has been obtained by directly converting the Caffe model provived by the authors.

Details about the network architecture can be found in the following arXiv paper:

Very Deep Convolutional Networks for Large-Scale Image Recognition

K. Simonyan, A. Zisserman

return

# In order for gpg to find gpg-agent, gpg-agent must be running, and there must be an env
# variable pointing GPG to the gpg-agent socket. This little script, which must be sourced
# in your shell's init script (ie, .bash_profile, .zshrc, whatever), will either start
# gpg-agent or set up the GPG_AGENT_INFO variable if it's already running.

# Add the following to your shell init to set up gpg-agent automatically for every shell
if [ -f ~/.gnupg/.gpg-agent-info ] && [ -n "$(pgrep gpg-agent)" ]; then
    source ~/.gnupg/.gpg-agent-info
    export GPG_AGENT_INFO
else

return

using System;
using System.Net;
using System.IO;
using System.IO.Compression;
using System.Collections.Generic;
using System.Text.RegularExpressions;
using System.Diagnostics;
using System.Text;
using System.Security.Cryptography;
using System.Security.Permissions;