gregjhogan

# docker run -runtime=nvidia --rm -ti -v "${PWD}:/app" tensorflow/tensorflow:latest-gpu python /app/test.py gpu 10000

import sys
import numpy as np
import tensorflow as tf
from datetime import datetime

device_name = sys.argv[1]  # Choose device from cmd line. Options: gpu or cpu
shape = (int(sys.argv[2]), int(sys.argv[2]))
if device_name == "gpu":

gregjhogan

# setup
sudo tc qdisc add dev $1 root tbf rate 1.0mbit latency 50ms burst 50kb mtu 10000
# remove
sudo tc qdisc del dev $1 root

gregjhogan

ps -ef | grep <filter-here> | grep -v grep | awk '{print $2}' | xargs kill -9

gregjhogan

#!/bin/bash
set -e

LOGIN=<USER>
NEWUID=<NEWUID>
NEWGID=<NEWGID>
OLDUID=<OLDUID>
OLDGID=<OLDGID>

usermod -u $NEWUID $LOGIN

gregjhogan

sudo apt install virtualbox virtualbox-ext-pack

gregjhogan

TZ=America/Los_Angeles date -d @1524291778

gregjhogan

#!/usr/bin/env python

# plug in grey panda
# open Lefebure NTRIP Client android app
# configure it:
# - Receiver Settings -> External via TCP/IP (enter the IP of the machine running this script and port 3001)
# - Receiver Settings -> GPS Mock Locations (check checkbox)
# - NTRIP Settings -> Caster IP/Port/Username Password for your local RTK network
# - NTRIP Settings -> Data Stream needs to be an RTCM3 source
# go into android developer settings and select the Lefebure NTRIP Client app to use for mock locations

gregjhogan

#!/usr/bin/env python
import sys
import time
import struct
from panda import Panda

DEBUG = False

def main():
  logfile = sys.argv[1]

gregjhogan

const fs = require('fs');

const content = fs.readFileSync('./data.csv', 'utf8');
const messages = content
    .split('\n')
    .map(line => line.trim())
    .filter(line => line.length > 0 && line !== 'time,addr,bus,data')
    .map(line => line.split(','))
    .map(msg => ({
        addr: parseInt(msg[1]),

gregjhogan

sudo apt-get -y install python python-setuptools
sudo easy_install pip