rspeer

soumith

import torch
import torch.nn as nn
import torch.nn.parallel

class DCGAN_D(nn.Container):
    def __init__(self, isize, nz, nc, ndf, ngpu, n_extra_layers=0):
        super(DCGAN_D, self).__init__()
        self.ngpu = ngpu
        assert isize % 16 == 0, "isize has to be a multiple of 16"

adamstegman

#!/usr/bin/env ruby

require 'json'
require 'logger'
require 'net/http'

require 'addressable/template'
require 'mechanize'
require 'nokogiri'

austinhappel

How to connect an iOS device to your computer via a SOCKS proxy

Say you're running a virtual machine on your work computer. Say this machine, for whatever reason, can only connect to the internet over NAT - as in, it does not get it's own IP address. Say this VM is running a webserver, and you need a device outside of your computer to connect to it.

If only there was a way to get your work computer to 'share' it's network, so that you could get at that VM… Here's how you do it!

For all instructions, I assume your work computer is a mac

1. Get your computer's IP address:

endolith

# https://github.com/matplotlib/matplotlib/issues/881
# Several of the ColorBrewer maps are "qualitative", meaning
# they are just a group of colors that can be used together 
# for categories of data.  So I remapped Accent to segments 
# instead of continuous:

# Actually, these should be used with ListedColormap, and 
# the number of colors should depend on the number of 
# categories in the data, with colors removed from the 
# list in a certain order?

erikh

#!/usr/bin/env sh

##
# This is script with usefull tips taken from:
#   https://github.com/mathiasbynens/dotfiles/blob/master/.osx
#
# install it:
#   curl -sL https://raw.github.com/gist/2108403/hack.sh | sh
#

GaelVaroquaux

Cython example of exposing C-computed arrays in Python without data copies

The goal of this example is to show how an existing C codebase for numerical computing (here c_code.c) can be wrapped in Cython to be exposed in Python.

The meat of the example is that the data is allocated in C, but exposed in Python without a copy using the PyArray_SimpleNewFromData numpy