A neural network designs Halloween costumes

It’s hard to come up with ideas for Halloween costumes, especially when it seems like all the good ones are taken. And don’t you hate showing up at a party only to discover that there’s *another* pajama cardinalfish?

I train neural networks, a type of machine learning algorithm, to write humor by giving them datasets that they have to teach themselves to mimic. They can sometimes do a surprisingly good job, coming up with a metal band called Chaosrug, a craft beer called Yamquak and another called The Fine Stranger (which now exists!), and a My Little Pony called Blue Cuss.

So, I wanted to find out if a neural network could help invent Halloween costumes. I couldn’t find a big enough dataset, so I crowdsourced it by asking readers to list awesome Halloween costumes. I got over 4,500 submissions.

The most popular submitted costumes are the classics (42 witches, 32 ghosts, 30 pirates, 22 Batmans, 21 cats (30 incl sexy cats), 19 vampires, and 17 each of pumpkins and sexy nurses). There are about 300 costumes with “sexy” in their names; some of the most eyebrow-raising include sexy anglerfish, sexy Dumbledore, sexy golden pheasant, sexy eyeball, sexy Mothra, Sexy poop emoji, Sexy Darth Vader, Sexy Ben Franklin, Sexy TARDIS, Sexy Cookie Monster, and Sexy DVORAK keyboard. In the “technical challenge” department, we have costumes like Invisible Pink Unicorn, Whale-frog, Glow Cloud, Lake Michigan, Toaster Oven, and Garnet.

All this is to say that humans are very creative, and this task was going to be tricky for a neural network. The sensible approach would be to try to use a neural network that actually knows what the words mean - there are such things, trained by reading, for example, all of Google News and figuring out which words are used in similar ways. There’s a fun demo of this here. It doesn’t have an entry for “Sexy_Gandalf” but for “sexy” it suggests “saucy” and “sassy”, and for “Gandalf” it suggests “Frodo”, “Gollum”, and “Voldemort”, so you could use this approach to go from “Sexy Gandalf” to “Sassy Voldemort”.

I wanted something a bit weirder. So, I used a neural network that learns words from scratch, letter by letter, with no knowledge of their meaning, an open-source char-rnn neural network written in Torch. I simply dumped the 4500 Halloween costumes on it, and told the neural network to figure it out.

Early in the training process, I decided to check in to see how it was doing.

Sexy sexy Dombie Sexy Cat

Sexy A stare Rowan

Sexy RoR A the Rog

Sexy Cot

Sexy Purbie Lampire

Poth Rat

Sexy Por Man

The Wombue

Pombie Con A A Cat

The Ran Spean Sexy Sexy Pon Sexy Dander

Sexy Cat

The Gull Wot

Sexy Pot

Hot

In retrospect, I should have expected this. With a dataset this varied, the words the neural network learns first are the most common ones.

I checked in a little later, and things had improved somewhat. (Omitted: numerous repetitions of “sexy nurse”). Still the only thing that makes sense is the word Sexy.

Sexy The Carding Ging

Farbat of the Cower

Sexy The Hirler

A costume

Sexy Menus

Sexy Sure

Frankenstein’s Denter

A cardian of the Pirate

Ging butter

Sexy the Girl Pirate

By the time I checked on the neural network again, it was not only better, but astoundingly good. I hadn’t expected this. But the neural network had found its niche: costume mashups. These are actually comprehensible, if a bit hard to explain:

Punk Tree

Disco Monster

Spartan Gandalf

Starfleet Shark

A masked box

Martian Devil

Panda Clam

Potato man

Shark Cow

Space Batman

The shark knight

Snape Scarecrow

Gandalf the Good Witch

Professor Panda

Strawberry shark

Vampire big bird

Samurai Angel

lady Garbage

Pirate firefighter

Fairy Batman



Other costumes were still a bit more random.

Aldonald the Goddess of the Chicken

Celery Blue Frankenstein

Dancing Bellyfish

Dragon of Liberty

A shark princess

Statue of Witch

Cupcake pants

Bird Scientist

Giant Two butter

The Twin Spider Mermaid

The Game of Nightmare Lightbare

Share Bat

The Rocky Monster

Mario lander

Spork Sand

Statue of pizza

The Spiding hood

A card Convention

Sailor Potter

Shower Witch

The Little Pond

Spice of pokeman

Bill of Liberty

A spock

Count Drunk Doll of Princess

Petty fairy

Pumpkin picard

Statue of the Spice of the underworker

It still was fond of using made-up words, though. You’d be the only one at the party dressed as whatever these are.

Sparra

A masked scorby-babbersy

Scormboor

Magic an of the foand tood-computer

A barban

The Gumbkin

Scorbs Monster

A cat loory Duck

The Barboon

Flatue doctor

Sparrow Plapper

Grankenstein

The Spongebog

Minional marty clown

Count Vorror Rairol Mencoon

A neaving hold

Sexy Avical Ster of a balana Aly

Huntle starber pirate



And it ended up producing a few like this.

Sports costume

Sexy scare costume

General Scare construct



The reason? Apparently someone decided to help out by entering an entire costume store’s inventory. (”What are you supposed to be?” “Oh, I’m Mens Deluxe IT Costume - Size Standard.”)

There were also some like this:

Rink Rater Ginsburg

A winged boxer Ginsburg

Bed ridingh in a box Buther Ginsburg

Skeleton Ginsburg

Zombie Fire Cith Bader Ginsburg



Because someone had entered about 50 variations on Ruth Bader Ginsberg puns (Ruth Tater Ginsberg, Sleuth Bader Ginsber, Rock Paper Ginsberg).

It invented some awesome new superheroes/supervillains.

Glow Wonder Woman

The Bunnizer

Ladybog

Light man

Bearley Quinn

Glad woman

robot Werewolf

super Pun

Super of a bog

Space Pants

Barfer

buster pirate

Skull Skywolk lady

Skynation the Goddess

Fred of Lizard



And oh, the sexy costumes. Hundreds of sexy costumes, yet it never quite got the hang of it.



Sexy Scare

Sexy the Pumpkin

Saxy Pumpkins

Sexy the Pirate

Sexy Pumpkin Pirate

Sexy Gumb Man

Sexy barber

Sexy Gargles

Sexy humblebee

Sexy The Gate

Sexy Lamp

Sexy Ducty monster

Sexy conchpaper

Sexy the Bumble

Sexy the Super bass

Pretty zombie Space Suit

sexy Drangers

Sexy the Spock



You bet there are bonus names - and oh please go read them because they are so good and it was so hard to decide which ones to fit into the main article. Includes the poop jokes. You’re welcome.

I’ve posted the entire dataset as open-source on GitHub.

And you can contribute more costumes, for a possible future neural net upgrade (no email address necessary).