# uwuify fastest text uwuifier in the west transforms ``` Hey, I think I really love you. Do you want a headpat? ``` into ``` hey, (ꈍᴗꈍ) i think i weawwy wuv you. ^•ﻌ•^ do y-you want a headpat? ``` there's an [uwu'd](README_UWU.txt) version of this readme ## faq ### what? u want large amounts of text uwu'd in a smol amount of time ### where? ur computer, if it has a recent x86 cpu (intel, amd) that supports sse4.1 ### why? why not? ### how? tldr: 128-bit simd vectorization plus some big brain algos
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after hours of research, i've finally understood the essence of uwu'd text there are a few transformations: 1. replace some words (`small` -> `smol`, etc.) 2. nya-ify (eg. `naruhodo` -> `nyaruhodo`) 3. replace `l` and `r` with `w` 4. stutter sometimes (`hi` -> `h-hi`) 5. add a text emoji after punctuation (`,`, `.`, or `!`) sometimes these transformation passes take advantage of sse4.1 vector intrinsics to process 16 bytes at once. for string searching, i'm using a custom simd implementation of the [bitap](https://en.wikipedia.org/wiki/Bitap_algorithm) algorithm for matching against multiple strings. for random number generation, i'm using [XorShift32](https://en.wikipedia.org/wiki/Xorshift). for most character-level detection within simd registers, its all masking and shifting to simulate basic state machines in parallel multithreading is supported, so u can exploit all of ur cpu cores for the noble goal of uwu-ing massive amounts of text utf-8 is handled elegantly by simply ignoring non-ascii characters in the input unfortunately, due to both simd parallelism and multithreading, some words may not be fully uwu'd if they were lucky enough to cross the boundary of a simd vector or a thread's buffer. *they won't escape so easily next time*

### ok i want uwu'd text, how do i run this myself? #### install command-line tool 1. install rust: run `curl https://sh.rustup.rs -sSf | sh` on unix, or go [here](https://www.rust-lang.org/tools/install) for more options 2. run `cargo install uwuify` 3. run `uwuify` which will read from stdin and output to stdout. make sure u press ctrl + d (unix) or ctrl + z and enter (windows) after u type stuff in stdin to send an EOF if you are having trouble running `uwuify`, make sure you have `~/.cargo/bin` in your `$PATH` it is possible to read and write from files by specifying the input file and output file, in that order. u can use `--help` for more info. pass in `-v` for timings this is on crates.io [here](https://crates.io/crates/uwuify) #### include as library 1. put `uwuify = "^0.2"` under `[dependencies]` in your `Cargo.toml` file 2. the library is called `uwuifier` (slightly different from the name of the binary!) use it like so: ```rust use uwuifier::uwuify_str_sse; assert_eq!(uwuify_str_sse("hello world"), "hewwo wowwd"); ``` documentation is [here](https://docs.rs/uwuify/latest/uwuifier/) #### build from this repo
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1. install rust 2. run `git clone https://github.com/Daniel-Liu-c0deb0t/uwu.git && cd uwu` 3. run `cargo run --release` ##### testing 1. run `cargo test` ##### benchmarking 1. run `mkdir test && cd test` *warning: large files of 100mb and 1gb, respectively* 2. run `curl -OL http://mattmahoney.net/dc/enwik8.zip && unzip enwik8.zip` 3. run `curl -OL http://mattmahoney.net/dc/enwik9.zip && unzip enwik9.zip` 4. run `cd .. && ./bench.sh`

### i don't believe that this is fast. i need proof!!1! tldr: can be almost as fast as simply copying a file
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raw numbers from running `./bench.sh` on a 2019 macbook pro with eight intel 2.3 ghz i9 cpus and 16 gb of ram are shown below. the dataset used is the first 100mb and first 1gb of english wikipedia. the same dataset is used for the [hutter prize](http://prize.hutter1.net/) for text compression ``` 1 thread uwu enwik8 time taken: 178 ms input size: 100000000 bytes output size: 115095591 bytes throughput: 0.55992 gb/s 2 thread uwu enwik8 time taken: 105 ms input size: 100000000 bytes output size: 115095591 bytes throughput: 0.94701 gb/s 4 thread uwu enwik8 time taken: 60 ms input size: 100000000 bytes output size: 115095591 bytes throughput: 1.64883 gb/s 8 thread uwu enwik8 time taken: 47 ms input size: 100000000 bytes output size: 115095591 bytes throughput: 2.12590 gb/s copy enwik8 real 0m0.035s user 0m0.001s sys 0m0.031s 1 thread uwu enwik9 time taken: 2087 ms input size: 1000000000 bytes output size: 1149772651 bytes throughput: 0.47905 gb/s 2 thread uwu enwik9 time taken: 992 ms input size: 1000000000 bytes output size: 1149772651 bytes throughput: 1.00788 gb/s 4 thread uwu enwik9 time taken: 695 ms input size: 1000000000 bytes output size: 1149772651 bytes throughput: 1.43854 gb/s 8 thread uwu enwik9 time taken: 436 ms input size: 1000000000 bytes output size: 1149772651 bytes throughput: 2.29214 gb/s copy enwik9 real 0m0.387s user 0m0.001s sys 0m0.341s ``` *//TODO: compare with other tools*

### why isn't this readme uwu'd? so its readable if u happen to find uwu'd text more readable, there's always an [uwu'd](README_UWU.txt) version ### ok but why aren't there any settings i can change?!1?!!1 free will is an illusion ### wtf this is so unprofessional how are u gonna get hired at faang now?! don't worry, i've got u covered #### Title: uwu is all you need #### Abstract Recent advances in computing have made strides in parallelization, whether at a fine-grained level with SIMD instructions, or at a high level with multiple CPU cores. Taking advantage of these advances, we explore how the useful task of performing an uwu transformation on plain text can be scaled up to large input datasets. Our contributions in this paper are threefold: first, we present, to our knowledge, the first rigorous definition of uwu'd text. Second, we show our novel algorithms for uwu-ing text, exploiting vectorization and multithreading features that are available on modern CPUs. Finally, we provide rigorous experimental results that show how our implementation could be the "fastest in the west." In our benchmarks, we observe that our implementation was almost as a fast as a simple file copy, which is entirely IO-bound. We believe our work has potential applications in various domains, from data augmentation and text preprocessing for natural language processing, to giving authors the ability to convey potentially wholesome or cute meme messages with minimal time and effort. *// TODO: write paper* *// TODO: write more about machine learning so i get funding* ### ok i need to use this for something and i need the license info mit license ### ok but i have an issue with this or a suggestion or a question not answered here open an issue, be nice ### projects using this * [uwu-tray](https://github.com/Olaren15/uwu-tray): a tray icon to uwuify your text * [uwubot](https://github.com/yaahc/uwubot): discord bot for uwuifying text * [uwupedia](http://uwupedia.org/): the uwuified encycwopedia * [discord uwu webhook](https://github.com/bs2kbs2k/discord-uwu-webhook): automatically uwuifies all sent messages on discord via webhooks * [twent weznowor](https://twitter.com/twent_weznowor): best twitter bot ever * let me know if you make a project with uwuify! i appreciate u all! ### references * https://honk.moe/tools/owo.html * https://github.com/IamRifki/uwuizer * https://github.com/deadshot465/owoify_rs * https://cutekaomoji.com/characters/uwu/ * https://cutekaomoji.com/characters/owo/ * https://cutekaomoji.com/characters/flower-girl/ * and many more; let me know if i missed anything