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// Generate Google foobar invite, go to any website, open console and paste and run the following | |
// NOTE: Disable popup blocker. | |
// On one of the tabs you'll see the foobar invite generated. | |
for(var i = 0; i < 10; i++){ | |
window.open("https://google.com/search?q=arraylist+java"); | |
} |
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<html> | |
<head> | |
<meta charset="UTF-8"> | |
<script language="javascript" type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/0.8.0/p5.min.js"></script> | |
<script language="javascript" src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/0.8.0/addons/p5.dom.min.js"></script> | |
<script language="javascript" src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/0.8.0/addons/p5.sound.min.js"></script> | |
<script language="javascript" type="text/javascript" src="vehicle.js"></script> | |
<script language="javascript" type="text/javascript" src="population.js"></script> | |
<script language="javascript" type="text/javascript" src="sketch.js"></script> | |
</head> |
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#include <iostream> | |
#include <vector> | |
#include <string> | |
#include <mlpack/core.hpp> | |
#include <mlpack/core/optimizers/sgd/sgd.hpp> | |
#include "../environment.hpp" | |
using namespace mlpack; | |
using namespace std; | |
using namespace arma; |
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// Break Timers on websites with ease. | |
function timerKiller(){ | |
var lastCleanedBorder = 0; | |
return function () { | |
var id = window.setTimeout(function() {}, 0); | |
for(var i = lastCleanedBorder; i <= id; i++) { | |
window.clearTimeout(i); | |
} | |
lastCleanedBorder = id + 1; |
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set number | |
set linebreak | |
set showbreak=+++ | |
set textwidth=100 | |
set showmatch | |
set visualbell | |
set hlsearch | |
set smartcase | |
set ignorecase |
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#include <cmath> | |
#include <mlpack/core.hpp> | |
#include <mlpack/core/optimizers/sgd/sgd.hpp> | |
#include <mlpack/methods/ann/layer/layer.hpp> | |
#include <mlpack/methods/ann/ffn.hpp> | |
#include <mlpack/methods/ann/layer/linear.hpp> | |
#include <mlpack/methods/ann/layer/dropout.hpp> | |
#include <mlpack/methods/ann/layer/leaky_relu.hpp> | |
#include <mlpack/methods/ann/layer/convolution.hpp> |
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batch_size = 128 | |
valid_dataset = valid_dataset[:batch_size] | |
valid_labels = valid_labels[:batch_size] | |
test_dataset = test_dataset[:batch_size] | |
test_labels = test_labels[:batch_size] | |
graph = tf.Graph() | |
with graph.as_default(): | |
# Input data. For the training data, we use a placeholder that will be fed |