// This check is new and seems buggy (possibly with PyO3 interaction)
#![allow(clippy::borrow_deref_ref)]
use std::collections::HashSet;
use std::thread;
use fancy_regex::Regex;
use pyo3::exceptions;
use pyo3::prelude::*;
use pyo3::types::{PyBytes, PyList, PyTuple};
use pyo3::PyResult;
use rustc_hash::FxHashMap as HashMap;
fn _byte_pair_merge<T>(
piece: &[u8],
ranks: &HashMap<Vec<u8>, usize>,
f: impl Fn(std::ops::Range<usize>) -> T,
) -> Vec<T> {
// This is a vector of (start, rank).
// The rank is of the byte pair starting at position start.
// The rank of the last item in the vector is not a valid value.
let mut parts: Vec<(usize, usize)> = (0..piece.len() + 1).map(|i| (i, usize::MAX)).collect();
let get_rank = {
#[inline(always)]
|parts: &Vec<(usize, usize)>, start_idx: usize, skip: usize| {
if (start_idx + skip + 2) < parts.len() {
ranks
.get(&piece[parts[start_idx].0..parts[start_idx + skip + 2].0])
.copied()
} else {
None
}
}
};
// We look up the ranks once in the beginning and iteratively update
// them during each merge, which reduces the number of rank lookups.
for i in 0..parts.len() - 2 {
match get_rank(&parts, i, 0) {
Some(rank) => {
// usize::MAX is a sentinel value and cannot be a valid rank
debug_assert!(rank != usize::MAX);
parts[i].1 = rank;
}
None => {
continue;
}
};
}
// If you have n parts and m merges, this does O(mn) work.
// We could do something with a heap and do O(m log n) work.
// It is important to consider that n is often small (<100), and as such
// the cache-locality benefits outweigh the algorithmic complexity downsides
// of the `parts` vector data structure above.
// Note that we hash bytes, not token pairs. As long as we train BPE the way we
// currently do, this is equivalent. An easy way to break this would be to decouple
// merge priority from token index or to prevent specific token merges.
loop {
if parts.len() == 1 {
break;
}
// usize::MAX is a sentinel rank value allowing us to
// take the min more quickly
let mut min_rank: (usize, usize) = (usize::MAX, 0);
for (i, &(_, rank)) in parts[..parts.len() - 1].iter().enumerate() {
if rank < min_rank.0 {
min_rank = (rank, i);
}
}
if min_rank.0 != usize::MAX {
let i = min_rank.1;
// NOTE: We are about to remove parts[i + 1]. We do not do it
// yet because there are cache-locality benefits to updating
// parts[i] and parts[i-1] before removing, which could thrash
// the cache. Thus, we update the rank calculation by skipping over
// parts[i + 1], by invoking `get_rank!` with `skip = 1`.
parts[i].1 = get_rank(&parts, i, 1).unwrap_or(usize::MAX);
if i > 0 {
parts[i - 1].1 = get_rank(&parts, i - 1, 1).unwrap_or(usize::MAX);
}
parts.remove(i + 1);
} else {
break;
}
}
let mut out: Vec<T> = Vec::with_capacity(parts.len() - 1);
for i in 0..parts.len() - 1 {
out.push(f(parts[i].0..parts[i + 1].0));
}
out
}
pub fn byte_pair_encode(piece: &[u8], ranks: &HashMap<Vec<u8>, usize>) -> Vec<usize> {
if piece.len() == 1 {
return vec![ranks[piece]];
}
_byte_pair_merge(piece, ranks, |p| ranks[&piece[p.start..p.end]])
}
pub fn byte_pair_split<'a>(piece: &'a [u8], ranks: &HashMap<Vec<u8>, usize>) -> Vec<&'a [u8]> {
if piece.len() == 1 {
return vec![piece];
}
_byte_pair_merge(piece, ranks, |p| &piece[p.start..p.end])
}
// Various performance notes:
//
// Regex
// =====
// Most of the time is spent in regex. The easiest way to speed this up is by using less fancy
// regex features. For instance, using a regex parse-able by `regex` crate is 3x faster than
// the usual regex we use.
//
// However, given that we're using a regex parse-able by `regex`, there isn't much difference
// between using the `regex` crate and using the `fancy_regex` crate.
//
// There is an important interaction between threading, `regex` and `fancy_regex`.
// When using `fancy_regex`, we hit `regex.find_at`. It turns out that this causes contention on
// some mutable scratch space inside of `regex`. This absolutely kills performance. When using plain
// old `regex`, we don't hit this, because `find_iter` has a different code path.
// Related: https://github.com/rust-lang/regex/blob/master/PERFORMANCE.md
// Anyway, the way we get around this is with having a (mostly) thread local clone of the regex for
// each thread.
//
// Threading
// =========
// I tried using `rayon`. It wasn't really faster than using Python threads and releasing the GIL.
// So goodbye `rayon`! Let thread count etc be in control of our Python users.
//
// Caching
// =======
// The reference tokeniser has an lru cache over the equivalent of `byte_pair_encode`.
// Originally, we had one too! Without it, we were only vaguely faster than Python.
// I used an RWLock to protect the cache. This didn't seem to hurt single threaded performance
// noticeably, but it did affect multi-threaded performance. Weirdly, it seemed to affect
// multi-threaded performance even when I only had readers (maybed I messed something up?).
// Anyway, I realised that we could get rid of the cache, if we treat the set of tokens as a cache!
// These are exactly the set or merges that are likely to be hot. And now we don't have to think
// about interior mutability, memory use, or cloning.
//
// Hashing
// =======
// We use FxHashMap instead of the standard HashMap. This is maybe like a 5-10% win?
// The current implementation ends up doing a lot of hashing of bytes. In theory, this could be made
// to be hashing of two-tuples of ints, which looks like it may also be a couple percent faster.
use std::num::NonZeroU64;
pub struct FakeThreadId(NonZeroU64);
fn hash_current_thread() -> usize {
// It's easier to use unsafe than to use nightly. Rust has this nice u64 thread id counter
// that works great for our use case of avoiding collisions in our array. Unfortunately,
// it's private. However, there are only so many ways you can layout a u64, so just transmute
// https://github.com/rust-lang/rust/issues/67939
const _: [u8; 8] = [0; std::mem::size_of::<std::thread::ThreadId>()];
const _: [u8; 8] = [0; std::mem::size_of::<FakeThreadId>()];
let x = unsafe {
std::mem::transmute::<std::thread::ThreadId, FakeThreadId>(thread::current().id()).0
};
u64::from(x) as usize
}
const MAX_NUM_THREADS: usize = 128;
#[pyclass]
struct CoreBPE {
encoder: HashMap<Vec<u8>, usize>,
special_tokens_encoder: HashMap<String, usize>,
decoder: HashMap<usize, Vec<u8>>,
special_tokens_decoder: HashMap<usize, Vec<u8>>,
regex_tls: Vec<Regex>,
special_regex_tls: Vec<Regex>,
sorted_token_bytes: Vec<Vec<u8>>,
}
impl CoreBPE {
fn _get_tl_regex(&self) -> &Regex {
// See performance notes above for what this is about
// It's also a little janky, please make a better version of it!
// However, it's nice that this doesn't leak memory to short-lived threads
&self.regex_tls[hash_current_thread() % MAX_NUM_THREADS]
}
fn _get_tl_special_regex(&self) -> &Regex {
&self.special_regex_tls[hash_current_thread() % MAX_NUM_THREADS]
}
fn _decode_native(&self, tokens: &[usize]) -> Vec<u8> {
let mut ret = Vec::with_capacity(tokens.len() * 2);
for token in tokens {
let token_bytes = self
.decoder
.get(token)
.unwrap_or_else(|| &self.special_tokens_decoder[token]);
ret.extend(token_bytes);
}
ret
}
fn _encode_ordinary_native(&self, text: &str) -> Vec<usize> {
// This is the core of the encoding logic; the other functions in here
// just make things complicated :-)
let regex = self._get_tl_regex();
let mut ret = vec![];
for mat in regex.find_iter(text) {
let piece = mat.unwrap().as_str().as_bytes();
if let Some(token) = self.encoder.get(piece) {
ret.push(*token);
continue;
}
ret.extend(&byte_pair_encode(piece, &self.encoder));
}
ret
}
fn _encode_native(&self, text: &str, allowed_special: &HashSet<&str>) -> (Vec<usize>, usize) {
let special_regex = self._get_tl_special_regex();
let regex = self._get_tl_regex();
let mut ret = vec![];
let mut start = 0;
let mut last_piece_token_len = 0;
loop {
let mut next_special;
let mut start_find = start;
loop {
// Find the next allowed special token, if any
next_special = special_regex.find_from_pos(text, start_find).unwrap();
match next_special {
Some(m) => {
if allowed_special.contains(&text[m.start()..m.end()]) {
break;
}
start_find = m.start() + 1;
}
None => break,
}
}
let end = next_special.map_or(text.len(), |m| m.start());
// Okay, here we go, compare this logic to _encode_ordinary_native
for mat in regex.find_iter(&text[start..end]) {
let piece = mat.unwrap().as_str().as_bytes();
if let Some(token) = self.encoder.get(piece) {
last_piece_token_len = 1;
ret.push(*token);
continue;
}
let tokens = byte_pair_encode(piece, &self.encoder);
last_piece_token_len = tokens.len();
ret.extend(&tokens);
}
match next_special {
// And here we push the special token
Some(m) => {
let piece = m.as_str();
let token = self.special_tokens_encoder[piece];
ret.push(token);
start = m.end();
last_piece_token_len = 0;
}
None => break,
}
}
// last_piece_token_len is how many tokens came from the last regex split. This is used
// for determining unstable tokens, since you can't merge across (stable) regex splits
(ret, last_piece_token_len)
}
fn _increase_last_piece_token_len(
&self,
tokens: Vec<usize>,
mut last_piece_token_len: usize,
) -> (Vec<usize>, usize) {
// Unfortunately, the locations where our regex splits can be unstable.
// For the purposes of determining unstable tokens, unstable regex splitting
// is only a problem if a split that was present disappears, since this can
// lead to merging of tokens otherwise thought to be stable.
// cl100k_base makes our life hard by including the \s*[\r\n]+
// pattern. This can e.g. cause "\n" + " " to become "\n \n".
// Here is a quick and dirty fix:
{
let token_is_all_space = |token| {
self.decoder
.get(token)
.map(|token_bytes| {
token_bytes
.iter()
.rev()
.all(|&b| [b' ', b'\n', b'\t'].contains(&b))
})
.unwrap_or(false)
};
if last_piece_token_len > 0
&& token_is_all_space(&tokens[tokens.len() - last_piece_token_len])
{
while (last_piece_token_len < tokens.len())
&& token_is_all_space(&tokens[tokens.len() - last_piece_token_len - 1])
{
last_piece_token_len += 1;
}
}
}
debug_assert!(last_piece_token_len <= tokens.len());
(tokens, last_piece_token_len)
}
fn _encode_unstable_native(
&self,
text: &str,
allowed_special: &HashSet<&str>,
) -> (Vec<usize>, HashSet<Vec<usize>>) {
let (tokens, last_piece_token_len) = self._encode_native(text, allowed_special);
if last_piece_token_len == 0 {
// If last_piece_token_len is zero, the last token was a special token and we have
// no unstable bytes
return (tokens, HashSet::new());
}
let (mut tokens, last_piece_token_len) =
self._increase_last_piece_token_len(tokens, last_piece_token_len);
let unstable_bytes = self._decode_native(&tokens[tokens.len() - last_piece_token_len..]);
tokens.truncate(tokens.len() - last_piece_token_len);
// TODO: we should try harder to find additional stable tokens
// This would reduce the amount of retokenising when determining completions
// Refer to the logic in an older version of this file
let mut completions = HashSet::new();
if unstable_bytes.is_empty() {
return (tokens, completions);
}
// This is the easy bit. Just find all single tokens that start with unstable_bytes
// (including tokens that exactly match unstable_bytes)
// Separating this from the loop below helps with performance in a common case.
let mut point = self
.sorted_token_bytes
.partition_point(|x| x.as_slice() < unstable_bytes.as_slice());
while point < self.sorted_token_bytes.len()
&& self.sorted_token_bytes[point].starts_with(&unstable_bytes)
{
completions.insert(vec![
self.encoder[self.sorted_token_bytes[point].as_slice()],
]);
point += 1;
}
// Now apply even more brute force. At every (other) possible position for the straddling
// token, concatenate additional bytes from that token (if any) to unstable_bytes,
// and retokenise the whole thing and see what we get.
for i in 1..unstable_bytes.len() {
let prefix = &unstable_bytes[..i];
let suffix = &unstable_bytes[i..];
let mut point = self
.sorted_token_bytes
.partition_point(|x| x.as_slice() < suffix);
// TODO: Perf optimisation if suffix starts with " "?
while point < self.sorted_token_bytes.len()
&& self.sorted_token_bytes[point].starts_with(suffix)
{
let possibility = [prefix, self.sorted_token_bytes[point].as_slice()].concat();
let encoded = match std::str::from_utf8(&possibility) {
// Morally, this is byte_pair_encode(&possibility, &self.encoder)
// But we might have introduced a regex split which would prevent merges.
// (particularly possible in the presence of unstable regex splits)
// So convert to UTF-8 and do regex splitting.
// E.g. with cl100k_base " !" gets split to " " + " !",
// but byte_pair_encode(" !") != byte_pair_encode(" ")
Ok(s) => self._encode_ordinary_native(s),
// Technically, whether or not this arm is correct depends on whether there
// would be a regex split before the UTF-8 truncation point.
// Probably niche enough that no one will ever notice (after all, people didn't
// notice all the big holes in the previous unstable token implementation)
Err(_) => byte_pair_encode(&possibility, &self.encoder),
// Something like the following is intriguing but incorrect:
// Err(e) => self._encode_ordinary_native(unsafe {
// std::str::from_utf8_unchecked(&possibility[..e.valid_up_to()])
// }),
};
let mut seq = Vec::new();
let mut seq_len = 0;
for token in encoded {
seq.push(token);
seq_len += self.decoder[&token].len();
if seq_len >= unstable_bytes.len() {
break;
}
}
completions.insert(seq);
point += 1;
}
}
// This is also not straightforward. While we generally assume that regex splits are stable,
// unfortunately, they are not. That is, if adding bytes were to make a split appear in
// unstable_bytes, this could make tokens possible which our logic would otherwise think
// would be merged.
// For example, with gpt2, the use of \s+(?!\S) means that "\n\n" could
// develop a split, e.g. "\n\n0" splits into "\n"+"\n"+"0", making "\n" a possible token.
// Here is a quick and dirty fix:
// This isn't right if we ever remove \s+(?!\S)
if unstable_bytes.len() > 1 {
let last_decoded = bstr::decode_last_utf8(unstable_bytes.as_slice());
if unstable_bytes.len() - last_decoded.1 > 0
&& last_decoded.0.map_or(false, |c| c.is_whitespace())
{
let mut reencoded = byte_pair_encode(
&unstable_bytes[..unstable_bytes.len() - last_decoded.1],
&self.encoder,
);
reencoded.extend(byte_pair_encode(
&unstable_bytes[unstable_bytes.len() - last_decoded.1..],
&self.encoder,
));
completions.insert(reencoded);
}
}
(tokens, completions)
}
}
#[pymethods]
impl CoreBPE {
#[new]
fn new(
encoder: HashMap<Vec<u8>, usize>,
special_tokens_encoder: HashMap<String, usize>,
pattern: &str,
) -> PyResult<Self> {
let regex = Regex::new(pattern)
.map_err(|e| PyErr::new::<exceptions::PyValueError, _>(e.to_string()))?;
let special_regex = {
let _parts = special_tokens_encoder
.keys()
.map(|s| fancy_regex::escape(s))
.collect::<Vec<_>>();
Regex::new(&_parts.join("|"))
.map_err(|e| PyErr::new::<exceptions::PyValueError, _>(e.to_string()))?
};
let decoder: HashMap<usize, Vec<u8>> =
encoder.iter().map(|(k, v)| (*v, k.clone())).collect();
assert!(
encoder.len() == decoder.len(),
"Encoder and decoder must be of equal length; maybe you had duplicate token indices in your encoder?"
);
let special_tokens_decoder: HashMap<usize, Vec<u8>> = special_tokens_encoder
.iter()
.map(|(k, v)| (*v, k.as_bytes().to_vec()))
.collect();
// Clone because I don't know how to tell Rust I'm not going to change the map
let mut sorted_token_bytes: Vec<Vec<u8>> = encoder.keys().cloned().collect();
sorted_token_bytes.sort();
Ok(CoreBPE {
encoder,
special_tokens_encoder,
decoder,
special_tokens_decoder,
regex_tls: (0..MAX_NUM_THREADS).map(|_| regex.clone()).collect(),
special_regex_tls: (0..MAX_NUM_THREADS)
.map(|_| special_regex.clone())
.collect(),
sorted_token_bytes,
})
}
// ====================
// Encoding
// ====================
fn encode_ordinary(&self, py: Python, text: &str) -> Vec<usize> {
py.allow_threads(|| self._encode_ordinary_native(text))
}
fn encode(&self, py: Python, text: &str, allowed_special: HashSet<&str>) -> Vec<usize> {
py.allow_threads(|| self._encode_native(text, &allowed_special).0)
}
fn _encode_bytes(&self, py: Python, bytes: &[u8]) -> Vec<usize> {
py.allow_threads(|| {
match std::str::from_utf8(bytes) {
Ok(text) => self._encode_ordinary_native(text),
Err(e) => {
let text = unsafe { std::str::from_utf8_unchecked(&bytes[..e.valid_up_to()]) };
let (tokens, last_piece_token_len) = self._encode_native(text, &HashSet::new());
let (mut tokens, last_piece_token_len) =
self._increase_last_piece_token_len(tokens, last_piece_token_len);
if !tokens.is_empty() && last_piece_token_len > 0 {
// Lop off the tokens from the last piece and run BPE on the remaining bytes
// Somewhat niche, but this may not be correct if we'd have had a regex
// split between the valid UTF-8 and the invalid bytes, which is why this
// method is private
let mut unstable_bytes =
self._decode_native(&tokens[tokens.len() - last_piece_token_len..]);
unstable_bytes.extend_from_slice(&bytes[e.valid_up_to()..]);
tokens.truncate(tokens.len() - last_piece_token_len);
tokens.extend(byte_pair_encode(&unstable_bytes, &self.encoder));
}
tokens
}
}
})
}
fn encode_with_unstable(
&self,
py: Python,
text: &str,
allowed_special: HashSet<&str>,
) -> Py<PyTuple> {
let (tokens, completions) =
py.allow_threads(|| self._encode_unstable_native(text, &allowed_special));
let py_completions =
PyList::new(py, completions.iter().map(|seq| PyList::new(py, &seq[..])));
(tokens, py_completions).into_py(py)
}
fn encode_single_token(&self, piece: &[u8]) -> PyResult<usize> {
if let Some(token) = self.encoder.get(piece).copied() {
return Ok(token);
}
if let Ok(piece_str) = std::str::from_utf8(piece) {
if let Some(token) = self.special_tokens_encoder.get(piece_str).copied() {
return Ok(token);
}
}
Err(PyErr::new::<exceptions::PyKeyError, _>(piece.to_owned()))
}
fn encode_single_piece(&self, piece: &[u8]) -> Vec<usize> {
if let Some(token) = self.encoder.get(piece) {
return vec![*token];
}
byte_pair_encode(piece, &self.encoder)
}
// ====================
// Decoding
// ====================
fn decode_bytes(&self, py: Python, tokens: Vec<usize>) -> Py<PyBytes> {
let bytes = py.allow_threads(|| self._decode_native(&tokens));
PyBytes::new(py, &bytes).into()
}
fn decode_single_token_bytes(&self, py: Python, token: usize) -> PyResult<Py<PyBytes>> {
if let Some(bytes) = self.decoder.get(&token) {
return Ok(PyBytes::new(py, bytes).into());
}
if let Some(bytes) = self.special_tokens_decoder.get(&token) {
return Ok(PyBytes::new(py, bytes).into());
}
Err(PyErr::new::<exceptions::PyKeyError, _>(token.to_string()))
}
// ====================
// Miscellaneous
// ====================
fn token_byte_values(&self, py: Python) -> Vec<Py<PyBytes>> {
self.sorted_token_bytes
.iter()
.map(|x| PyBytes::new(py, x).into())
.collect()
}
}
#[pymodule]
fn _tiktoken(_py: Python, m: &PyModule) -> PyResult<()> {
m.add_class::<CoreBPE>()?;
Ok(())
}
#[cfg(test)]
mod tests {
use rustc_hash::FxHashMap as HashMap;
use crate::byte_pair_split;
#[test]
fn very_simple_test() {
let mut ranks = HashMap::default();
ranks.insert(b"ab".to_vec(), 1);
ranks.insert(b"cd".to_vec(), 2);
let res = byte_pair_split(b"abcd", &ranks);
assert_eq!(res, vec![b"ab", b"cd"]);
}
}openai/tiktoken
Publicmirrored fromhttps://github.com/openai/tiktokenAvailable
src/lib.rs
608lines · modepreview