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@CristinaSolana
CristinaSolana / gist:1885435
Created February 22, 2012 14:56
Keeping a fork up to date

1. Clone your fork:

git clone [email protected]:YOUR-USERNAME/YOUR-FORKED-REPO.git

2. Add remote from original repository in your forked repository:

cd into/cloned/fork-repo
git remote add upstream git://github.com/ORIGINAL-DEV-USERNAME/REPO-YOU-FORKED-FROM.git
git fetch upstream
private boolean isServiceRunning() {
ActivityManager manager = (ActivityManager) getSystemService(ACTIVITY_SERVICE);
for (RunningServiceInfo service : manager.getRunningServices(Integer.MAX_VALUE)){
if("com.example.MyNeatoIntentService".equals(service.service.getClassName())) {
return true;
}
}
return false;
}
@JamesChevalier
JamesChevalier / mac_utf8_insanity.md
Last active December 6, 2024 07:17
Unicode on Mac is insane. Mac OS X uses NFD while everything else uses NFC. This fixes that.

convmv manpage

Install convmv if you don't have it

sudo apt-get install convmv

Convert all files in a directory from NFD to NFC:

convmv -r -f utf8 -t utf8 --nfc --notest .

@bennadel
bennadel / app-error.js
Created May 5, 2015 13:14
Creating Custom Error Objects In Node.js With Error.captureStackTrace()
// Require our core node modules.
var util = require( "util" );
// Export the constructor function.
exports.AppError = AppError;
// Export the factory function for the custom error object. The factory function lets
// the calling context create new AppError instances without calling the [new] keyword.
exports.createAppError = createAppError;
@karpathy
karpathy / min-char-rnn.py
Last active December 20, 2024 19:43
Minimal character-level language model with a Vanilla Recurrent Neural Network, in Python/numpy
"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np
# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)
@zeroseis
zeroseis / disable-auto-android-file-transfer.md
Created September 14, 2015 17:28
Disable auto start for Android File Transfer
  • Close Android File Transfer
  • Open Activity Monitor and kill “Android File Transfer Agent”
  • Go to where you installed “Android File Transfer.app” (I have it under /Applications)
  • Ctrl+click –> “Show package contents”
  • Go to Contents/Resources
  • Rename “Android File Transfer Agent” to e.g. “Android File Transfer Agent_DISABLED”
  • Then go to “/Users/username/Library/Application Support/Google/Android File Transfer” and again rename the Agent app.
@mikehearn
mikehearn / KotlinDuckTyping.kt
Created December 18, 2015 13:46
Kotlin duck typing / type classing fiddle
class A {
fun shout() = println("go team A!")
}
class B {
fun shout() = println("go team B!")
}
interface Shoutable {
fun shout()
@claymcleod
claymcleod / pycurses.py
Last active November 30, 2024 16:08
Python curses example
import sys,os
import curses
def draw_menu(stdscr):
k = 0
cursor_x = 0
cursor_y = 0
# Clear and refresh the screen for a blank canvas
stdscr.clear()
@yrevar
yrevar / imagenet1000_clsidx_to_labels.txt
Last active December 23, 2024 02:34
text: imagenet 1000 class idx to human readable labels (Fox, E., & Guestrin, C. (n.d.). Coursera Machine Learning Specialization.)
{0: 'tench, Tinca tinca',
1: 'goldfish, Carassius auratus',
2: 'great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias',
3: 'tiger shark, Galeocerdo cuvieri',
4: 'hammerhead, hammerhead shark',
5: 'electric ray, crampfish, numbfish, torpedo',
6: 'stingray',
7: 'cock',
8: 'hen',
9: 'ostrich, Struthio camelus',
@karpathy
karpathy / pg-pong.py
Created May 30, 2016 22:50
Training a Neural Network ATARI Pong agent with Policy Gradients from raw pixels
""" Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """
import numpy as np
import cPickle as pickle
import gym
# hyperparameters
H = 200 # number of hidden layer neurons
batch_size = 10 # every how many episodes to do a param update?
learning_rate = 1e-4
gamma = 0.99 # discount factor for reward