benbotto

#include <array>
using std::array;
#include <bitset>
using std::bitset;
#include <iostream>
using std::cout;
using std::endl;

unsigned factorial(unsigned n)
{

benbotto

#include <array>
using std::array;
#include <iostream>
using std::cout;
using std::endl;

unsigned factorial(unsigned n)
{
  return n <= 1 ? 1 : n * factorial(n - 1);
}

benbotto

def huber_loss(y_true, y_pred, clip_delta=1.0):
  error = y_true - y_pred
  cond  = tf.keras.backend.abs(error) < clip_delta

  squared_loss = 0.5 * tf.keras.backend.square(error)
  linear_loss  = clip_delta * (tf.keras.backend.abs(error) - 0.5 * clip_delta)

  loss = tf.where(cond, squared_loss, linear_loss)

  return tf.keras.backend.mean(loss)

benbotto

import java.awt.Dimension;

public class Temp {
  public static void main(String[] args) {
    VIgui gui = new VIgui();
    gui.pack();
    gui.setSize(new Dimension(1024, 768));
    gui.setVisible(true);
  }
}

benbotto

@function gcd($a, $b) {
  @if $b == 0 {
    @return $a;
  }
  
  @return gcd($b, $a%$b);
}

@for $i from 1 through 11 {
  @for $j from $i+1 through 12 {