CapCap

#!/bin/bash


# Don't require you to constantly enter password for sudo:
sudo visudo
# In the bottom of the file, paste the following (without the `#`):
# paperspace ALL=(ALL) NOPASSWD: ALL
# Then press `ctl+o` then `enter` to save your changes, and `ctr+x` to exit nano

# Allow connection from your IP to any port- default seems to be just 22 (ssh)

CreatCodeBuild

pizzarob

import React from 'react';
import PropTypes from 'prop-types';
import classNames from 'classnames';

const ANIMATION_DURATION = 1000;

class BatchDropZone extends React.Component {

  static propTypes = {

Mistobaan

These instructions will explain how to install tensorflow on mac with cuda enabled GPU suport. I assume you know what tensorflow is and why you would want to have a deep learning framework running on your computer.

Prerequisites

Make sure to update your homebrew formulas

brew update

stephenturner

Installing gcc 4.8 and Linuxbrew on CentOS 6

The GCC distributed with CentOS 6 is 4.4.7, which is pretty outdated. I'd like to use gcc 4.8+. Also, when trying to install Linuxbrew you run into a dependency loop where Homebrew's gcc depends on zlib, which depends on gcc. Here's how I solved the problem.

Note: Requires sudo privileges.

Resources:

• http://superuser.com/a/676337/88393: Forum response on using CERN's open Scientific Linux distribution of RHEL's developer toolset.
• http://linux.web.cern.ch/linux/devtoolset/: CERN's developer toolset installation instructions.

baraldilorenzo

##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

karpathy

"""
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)

gaearon

// ------------
// counterStore.js
// ------------

import {
  INCREMENT_COUNTER,
  DECREMENT_COUNTER
} from '../constants/ActionTypes';

const initialState = { counter: 0 };

oscarrenalias

This gist is an implementation of http://sirile.github.io/2015/05/18/using-haproxy-and-consul-for-dynamic-service-discovery-on-docker.html on top of Docker Machine and Docker Swarm.

tmcw

var Dispatcher = require('the-dispatcher'),
  Immutable = require('immutable'),
  NotificationConstants = require('../constants/notification_constants'),
  UserConstants = require('../constants/user_constants'),
  UploadConstants = require('../constants/upload_constants'),
  StylesheetConstants = require('../constants/stylesheet_constants'),
  makeStore = require('makestore');

/**
 * The Notification Store does nothing but store recent actions