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I've implemented a double-bridge (or 4-opt) move in place, i.e. without any additional containers than the original. I'm sharing it with you first because I would like to know if it's correct or if I can improve it and second because I thought it could be helpful to someone else (since I have not found anything on the web).

/*
 * DOUBLE-BRIDGE-COMPUTE-GAIN
 *
 * Computes and returns the gain of a random double-bridge move.
 * The indices of the vertices used are also returnd as 2nd, 3rd and 4th parametrs of the array returned.
 * */
std::array<int, 4> double_bridge_in_place_compute_gain(const MatrixGraph &m, const VectorTour &t) {

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import numpy as np

E = EMPTY = 0
B = BLOCKED = 1
G = GOAL = 2

# The maze from the assignment
MAZE = np.array(
    [[0, 0, 0, 0, 0, 0, 0],
     [0, 0, B, 0, 0, 0, 0],

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channel operator quick reference

direct discussion about administrative action away from the main channel and into #reddit-diabetes-ops to minimise disruption. our -ops channel is the place where users should come to ask for our help. examples:

• any sort of operator request or discussion of channel administration in the main channel
• PMs asking why a ban was set
• reports of harassment (unless the user is confiding in you)
• any request for operator action

changing channel access permissions

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\begin{tikzpicture}[-, >=stealth', level/.style={sibling distance = 8cm/#1, level distance = 2cm}] 
\node [circle_node] (A) {$+$}
	child { node [square_node] (B) {-} 	
		child { node [circle_node] (E) {+}
			child { node [square_node] (L) {-}
				child [sibling distance = 1cm] { node [circle_node] (V) {$7$} }
				child [sibling distance = 1cm] { node [circle_node] (W) {$4$} }
			}
			child { node [square_node] (M) {-}
				child [sibling distance = 1cm] { node [circle_node] (X) {$2$} }

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\documentclass{article}

\usepackage{tikz}
\usetikzlibrary{arrows}
\usepackage[margin=0.6in]{geometry}

% Define a few styles for the nodes
\tikzset{
  tree_node/.style = {align=center, inner sep=0pt, text centered, font=\sffamily},
  square_node/.style = {tree_node, rectangle, draw=black, minimum width=1.5em, minimum height=1.5em, very thick},

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\def\alphabetadiagram{
\begin{tikzpicture}[-, >=stealth', level/.style={sibling distance = 8cm/#1, level distance = 2cm}] 

\node [circle_node] (A) {$+$}
	child { node [square_node] (B) {-} 	
		child { node [circle_node] (E) {+}
			child { node [square_node] (L) {-}
				child [sibling distance = 1cm] { node [circle_node] (V) {$7$} }
				child [sibling distance = 1cm] { node [circle_node] (W) {$4$} }
			}

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# It takes about 8 minutes to train this model and obtain 99% accuracy.
from __future__ import print_function
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torchvision import datasets, transforms
import time
import datetime
import argparse

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Mounting VirtualBox shared folders on Ubuntu Server 16.04 LTS

This guide will walk you through steps on how to setup a VirtualBox shared folder inside your Ubuntu Server guest. Tested on Ubuntu Server 16.04.3 LTS (Xenial Xerus)

Steps:

1. Open VirtualBox
2. Right-click your VM, then click Settings
3. Go to Shared Folders section
4. Add a new shared folder
5. On Add Share prompt, select the Folder Path in your host that you want to be accessible inside your VM.

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def example1():
    # TensorFlow 2.1
    import tensorflow as tf
    import numpy as np

    Input_1 = tf.keras.layers.Input(shape=(1,))

    x = tf.keras.layers.Dense(100, activation='relu')(Input_1)

    targets = ["out1", "out2", "out3"]

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import numpy as np
import matplotlib.pyplot as plt
import tensorflow as tf
import tensorflow.keras.layers as tfkl
from tensorflow.keras import backend as K
import tensorflow_probability as tfp
tfd = tfp.distributions
tfpl = tfp.layers
tfb = tfp.bijectors