gngdb

import torch
from torch.nn.functional import conv2d

def pointwise(X, W):
    n,c_in,h,w = X.size() # (n examples, c_in channels, height, width)
    c_out,c_in,_,_ = W.size() # (c_out channels, c_in channels, 1, 1)
    W = W.view(c_out,c_in) # squeeze size 1 dims, shape=(c_out, c_in)
    X = X.view(n,c_in,h*w) # flatten spatial dims
    X = X.permute(0,2,1) # transpose, shape=(n,h*w, c_in)
    K = X.reshape(n*h*w,c_in) # kernel matrix, shape=(n*h*w, c_in)

gngdb

# for making lockscreen images
set-i3lock-bg() { 
        if [ ! -f ~/lock.png ]; then
            curl https://raw.githubusercontent.com/meskarune/i3lock-fancy/master/icons/lock.png > ~/lock.png
        fi
        SIZE=`xdpyinfo | grep dimensions | cut -d " "  -f 7`
        convert $1 -font Liberation-Sans \
       -geometry $SIZE -gravity center\
       -pointsize 26 -fill white -extent $SIZE -gravity center \
       -annotate +0+160 "Type Password to Unlock" ~/lock.png \

gngdb

• OPT2019
• MLCB
• Queer in AI
• LatinX in AI
• WiML
• Black in AI
• EMC2
• Advances in Approximate Bayesian Inference
• New In ML

gngdb

#!/bin/bash
ALGO_IP=`ip addr | awk '
/^[0-9]+:/ {
  sub(/:/,"",$2); iface=$2 }
/^[[:space:]]*inet / {
  split($2, a, "/")
  print iface" : "a[1]
}' | grep tun | cut -b 8- | cut -d "." -f 1-3 | sed 's/$/.1/'`
mosh --ssh="ssh -i algo.pem" ubuntu@$ALGO_IP

gngdb

sudo apt-get update && sudo apt-get install \
    build-essential \
    libssl-dev \
    libffi-dev \
    python-dev \
    python-pip \
    python-setuptools \
    python-virtualenv -y
sudo pip2 install -r requirements.txt

gngdb

! 6/23/2019 https://twitter.com
twitter.com##.trends.Trends.module
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twitter.com##div.r-1adg3ll.r-qklmqi.r-my5ep6.css-1dbjc4n:nth-of-type(2) > .r-6416eg.r-o7ynqc.r-1w50u8q.r-utggzx.r-6koalj.r-1loqt21.css-1dbjc4n
twitter.com##.r-1l5qxre.css-1dbjc4n

! 6/24/2019 https://twitter.com
twitter.com##div.r-1adg3ll.r-qklmqi.r-my5ep6.css-1dbjc4n:nth-of-type(3) > .r-6416eg.r-o7ynqc.r-1xtiow5.r-5f36wq.r-6koalj.r-1loqt21.css-1dbjc4n
twitter.com##div.r-1adg3ll.r-qklmqi.r-my5ep6.css-1dbjc4n:nth-of-type(4) > .r-6416eg.r-o7ynqc.r-1xtiow5.r-5f36wq.r-6koalj.r-1loqt21.css-1dbjc4n
twitter.com##div.r-1adg3ll.r-qklmqi.r-my5ep6.css-1dbjc4n:nth-of-type(5) > .r-6416eg.r-o7ynqc.r-1xtiow5.r-5f36wq.r-6koalj.r-1loqt21.css-1dbjc4n

gngdb

So, you want to be able to work from anywhere. You want to be on a mountain somewhere, two bars of 3G signal, and you forward that to your laptop with a WiFi hotspot. Open your laptop and your shell on remote is already open and as responsive as possible. Work/life balance? With power like this, who cares?

Problem Scenario

Often, in academic institutions at least, you have the following situation:

gngdb

import os
import boto3

if __name__ == '__main__':
    session = boto3.Session()
    ec2 = session.resource('ec2')
    ec2c = session.client('ec2')
    # add active instances to the user's ssh config file
    instances = ec2.instances.filter(
                Filters=[{'Name': 'instance-state-name', 'Values': ['running']}])

gngdb

import boto3

class Session(boto3.Session):
    def __enter__(self):
        return self
    def __exit__(self, *args):
        del self

with Session() as sess:
    # get names of regions

gngdb

# dependencies
import re
import os
import argparse
import torch
from tqdm import tqdm
#import cv2
import numpy as np
import torch.utils.data
import torchnet as tnt