nicklockwood

/// Withable is a simple protocol to make constructing
/// and modifying objects with multiple properties
/// more pleasant (functional, chainable, point-free)
public protocol Withable {
  init()
}

public extension Withable {
  /// Construct a new instance, setting an arbitrary subset of properties
  init(with config: (inout Self) -> Void) {

danielctull

extension UICollectionViewFlowLayout {

    typealias DelegateMethod<Key, Value> = ((UICollectionView, UICollectionViewLayout, Key) -> Value)

    private var delegate: UICollectionViewDelegateFlowLayout? {
        return collectionView?.delegate as? UICollectionViewDelegateFlowLayout
    }

    func retrieve<Key, Value>(

illescasDaniel

#include <iostream>
#define guard(_condition) if (bool(_condition)){}

using namespace std;

// Example inside a function
template <typename Type>
Type biggestNumber(Type* numbers, const size_t& size) {
	
	guard(numbers != nullptr) else {

vinhkhuc

# Implementation of a simple MLP network with one hidden layer. Tested on the iris data set.
# Requires: numpy, sklearn>=0.18.1, tensorflow>=1.0

# NOTE: In order to make the code simple, we rewrite x * W_1 + b_1 = x' * W_1'
# where x' = [x | 1] and W_1' is the matrix W_1 appended with a new row with elements b_1's.
# Similarly, for h * W_2 + b_2
import tensorflow as tf
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split

kylefox

/*

Distributed under The MIT License:
http://opensource.org/licenses/mit-license.php

Permission is hereby granted, free of charge, to any person obtaining
a copy of this software and associated documentation files (the
"Software"), to deal in the Software without restriction, including
without limitation the rights to use, copy, modify, merge, publish,
distribute, sublicense, and/or sell copies of the Software, and to