shurain

<?php

$jsonCacheFile  = './quickfix.json';
$gimmieFeed     = 'https://gimmebar.com/api/v0/public/assets/phpquickfix';
$wgetCmd        = 'wget -O'.$jsonCacheFile.' '.$gimmieFeed;

// look for the cache file
if(!is_file($jsonCacheFile) || (is_file($jsonCacheFile) && filemtime($jsonCacheFile)<strtotime('-1 minute')) ){
        // fetch the latest content from gimmiebar
        exec($wgetCmd);

shurain

#!/usr/bin/env python
# Quick and dirty demonstration of CVE-2014-0160 by
# Jared Stafford (jspenguin@jspenguin.org)
# Modified so that it finds cookies

import sys
import struct
import socket
import time
import select

shurain

{
  "lines.linewidth": 2.0,
  "examples.download": true,
  "patch.linewidth": 0.5,
  "legend.fancybox": true,
  "axes.color_cycle": [
    "#30a2da",
    "#fc4f30",
    "#e5ae38",
    "#6d904f",

shurain

Copy nbflatten.py to somewhere on $PATH. Then, in the root of a git repository, run these commands:

echo "*.ipynb diff=ipynb" >> .gitattributes 
git config diff.ipynb.textconv nbflatten.py

When you change a notebook and run git diff, you'll see the diff of flattened, simplified notebooks, rather than the full JSON. This does lose some information (metadata, non-text output), but it makes it easier to see simple changes in the notebook.

This doesn't help with merging conflicting changes in notebooks. For that, see nbdiff.org.

shurain

'''
Non-parametric computation of entropy and mutual-information

Adapted by G Varoquaux for code created by R Brette, itself
from several papers (see in the code).

These computations rely on nearest-neighbor statistics
'''
import numpy as np

shurain

"""
A deep neural network with or w/o dropout in one file.

License: Do What The Fuck You Want to Public License http://www.wtfpl.net/
"""

import numpy, theano, sys, math
from theano import tensor as T
from theano import shared
from theano.tensor.shared_randomstreams import RandomStreams

shurain

# Alec Radford, Indico, Kyle Kastner
# License: MIT
"""
Convolutional VAE in a single file.
Bringing in code from IndicoDataSolutions and Alec Radford (NewMu)
Additionally converted to use default conv2d interface instead of explicit cuDNN
"""
import theano
import theano.tensor as T
from theano.sandbox.rng_mrg import MRG_RandomStreams as RandomStreams

shurain

on replace_chars(this_text, search_string, replacement_string)
  set AppleScript's text item delimiters to the search_string
  set the item_list to every text item of this_text
  set AppleScript's text item delimiters to the replacement_string
  set this_text to the item_list as string
  set AppleScript's text item delimiters to ""
  return this_text 
end replace_chars

tell application "Google Chrome"

shurain

# Authors: Kyle Kastner
# License: BSD 3-clause
import theano.tensor as T
import numpy as np
import theano


class rmsprop(object):
    """
    RMSProp with nesterov momentum and gradient rescaling

shurain

"""
This is a batched LSTM forward and backward pass
"""
import numpy as np
import code

class LSTM:
  
  @staticmethod
  def init(input_size, hidden_size, fancy_forget_bias_init = 3):