mangoliou

# Install x-related to compile x11vnc from source code.
sudo apt-get update 
sudo apt-get install -y libxtst-dev libssl-dev libjpeg-dev

# Grep source code.
wget http://x11vnc.sourceforge.net/dev/x11vnc-0.9.14-dev.tar.gz
gzip -dc x11vnc-0.9.14-dev.tar.gz | tar -xvf -
cd x11vnc-0.9.14/
./configure --prefix=/usr/local CFLAGS='-g -O2 -fno-stack-protector -Wall'

iambrian

Getting Setup: Follow the instruction on https://gym.openai.com/docs

git clone https://github.com/openai/gym
cd gym
pip install -e . # minimal install

Basic Example using CartPole-v0:

smoser

Set up a ssh tunnel only user

In order to give someone access to hosts that are available only by ssh "bouncing" (ProxyJump), add a user for this specific purpose.

We have an internal openstack where instances get IPs on per-tenant networks. Each tenant has a 'bastion' host that has a "public" ip (floating ip). You can access other instances by bouncing through the bastion. From time to time I want to let someone else into an instance. This could be done either with:

a.) just give them shell access to the bastion and let them hop through. Sharing an unrestricted shell account on my bastion is less than ideal. b.) assign a floating/"public" IP to the instance so they could go directly in. Floating IPs are limited, so this is less than ideal.

So instead, I have set up a single user as described here that can only be used for ProxyJump. It allows others proxied access to my instances but without granting them full shell access.

deehzee

Module autoreload

To auto-reload modules in jupyter notebook (so that changes in files *.py doesn't require manual reloading):

# for auto-reloading external modules
# see http://stackoverflow.com/questions/1907993/autoreload-of-modules-in-ipython
%load_ext autoreload
%autoreload 2

bmmalone

\documentclass[a4paper,10pt]{article}

% make writing commands easier
\usepackage{xparse}

% colored text
\usepackage{color}

% include eps, pdf graphics
\usepackage{graphicx}

Mahedi-61

#!/bin/bash

### steps ####
# Verify the system has a cuda-capable gpu
# Download and install the nvidia cuda toolkit and cudnn
# Setup environmental variables
# Verify the installation
###

### to verify your gpu is cuda enable check