gpt4all/gpt4all-backend/tokenizer/bpe.cpp
Aaron Miller bbcee1ced5 New tokenizer implementation for MPT and GPT-J
Improves output quality by making these tokenizers more closely
match the behavior of the huggingface `tokenizers` based BPE
tokenizers these models were trained with.

Featuring:
 * Fixed unicode handling (via ICU)
 * Fixed BPE token merge handling
 * Complete added vocabulary handling
2023-05-30 12:05:57 -04:00

258 lines
8.9 KiB
C++

#include "bpe.h"
#include <unicode/normalizer2.h>
#include <unicode/regex.h>
#include <unicode/schriter.h>
#include <unicode/unistr.h>
#include <regex>
#include <stdexcept>
#include <iostream>
namespace bpecpp {
const std::string_view BPE_PRETOK_REGEX =
R"('s|'t|'re|'ve|'m|'ll|'d| ?[[:alpha:]]+| ?[[:digit:]]+| ?[^\s[:alpha:][:digit:]]+|\s+(?!\S)|\s+)";
static void get_bigrams(const std::vector<icu::UnicodeString>& input,
std::unordered_set<UnicodeBigram, bigram_hash>& pairs) {
pairs.clear();
auto i = input.begin();
auto prev = *i++;
for (; i != input.end(); ++i) {
pairs.insert({prev, *i});
prev = *i;
}
}
BPE::BPE(const std::unordered_map<std::string_view, uint32_t>& vocab,
const std::vector<std::pair<std::string_view, std::string_view>>& merges) {
for (auto pair : vocab) {
icu::UnicodeString encd = icu::UnicodeString::fromUTF8(pair.first);
m_vocab[encd] = pair.second;
m_reverse_vocab[pair.second] = encd;
}
size_t n = 0;
for (auto merge : merges) {
auto left = icu::UnicodeString::fromUTF8(merge.first);
auto right = icu::UnicodeString::fromUTF8(merge.second);
m_merges[{left, right}] = n++;
}
}
std::vector<uint32_t> BPE::encode(const std::string& input) {
auto normalized = normalize_nfc(input);
auto pretokenized = pretokenize(normalized);
std::vector<icu::UnicodeString> tokens_merged;
for (auto &ptok : pretokenized) {
bpe(ptok, tokens_merged);
}
std::vector<uint32_t> final_tokens;
for (auto &mtok : tokens_merged) {
final_tokens.push_back(m_vocab[mtok]);
}
return final_tokens;
}
std::string BPE::decode(const std::vector<uint32_t>& tokens, bool valid_utf8) {
std::string out;
for (uint32_t t : tokens) {
icu::UnicodeString benc = m_reverse_vocab[t];
icu::StringCharacterIterator schriter(benc);
for (UChar32 c = schriter.first32(); schriter.hasNext();
c = schriter.next32()) {
out.push_back(m_bs_table.codepoint_to_byte((uint32_t)c));
}
}
// roundtrip through ICU to replace invalid utf8 with U+FFFD
if (valid_utf8) {
auto tmp = icu::UnicodeString::fromUTF8(out);
out.clear();
tmp.toUTF8String(out);
}
return out;
}
// https://github.com/karpathy/minGPT/blob/37baab71b9abea1b76ab957409a1cc2fbfba8a26/mingpt/bpe.py#L95
void BPE::bpe(icu::UnicodeString token_pretoked,
std::vector<icu::UnicodeString>& output) {
if (token_pretoked.length() < 2) {
output.push_back(token_pretoked);
return;
}
std::vector<icu::UnicodeString> words;
std::vector<icu::UnicodeString> words_update;
icu::StringCharacterIterator schriter(token_pretoked);
UChar32 c;
for (schriter.setToStart(); schriter.hasNext();) {
c = schriter.next32PostInc();
icu::UnicodeString w;
w.append(c);
words.push_back(w);
}
std::unordered_set<UnicodeBigram, bigram_hash> pairs;
get_bigrams(words, pairs);
while (true) {
size_t min_rank = SIZE_MAX;
UnicodeBigram to_merge;
for (auto &bigram : pairs) {
auto loc = m_merges.find(bigram);
if (loc != m_merges.end() && loc->second < min_rank) {
min_rank = loc->second;
to_merge = loc->first;
}
}
if (min_rank == SIZE_MAX) {
break;
} else {
auto i = words.begin();
while (i < words.end()) {
if (*i == to_merge.first) {
auto inext = i;
inext++;
if (inext != words.end() && *inext == to_merge.second) {
words_update.push_back(*i + *inext);
i = inext;
} else {
words_update.push_back(*i);
}
} else {
words_update.push_back(*i);
}
++i;
}
words.swap(words_update);
words_update.clear();
get_bigrams(words, pairs);
}
}
output.insert(output.end(), words.begin(), words.end());
}
std::string BPE::normalize_nfc(const std::string& input) {
UErrorCode uerror = U_ZERO_ERROR;
auto nfcnorm = icu::Normalizer2::getNFCInstance(uerror);
if (!U_SUCCESS(uerror))
throw std::runtime_error("could not get ICU NFC normalizer");
auto icu_ti = icu::UnicodeString::fromUTF8(input);
std::string out;
nfcnorm->normalize(icu_ti, uerror).toUTF8String(out);
if (!U_SUCCESS(uerror))
throw std::runtime_error("ICU string normalization failed");
return out;
}
std::vector<icu::UnicodeString> BPE::pretokenize(const std::string& input) {
UParseError pe;
UErrorCode uerror = U_ZERO_ERROR;
auto bpe_re_icustr = icu::UnicodeString::fromUTF8(BPE_PRETOK_REGEX);
if (m_pretok_re == nullptr) {
m_pretok_re = std::unique_ptr<icu::RegexPattern>(
icu::RegexPattern::compile(bpe_re_icustr, pe, uerror));
if (!U_SUCCESS(uerror))
throw std::runtime_error("Compiling BPE pretokenizer regex failed");
}
auto uinput = icu::UnicodeString::fromUTF8(input);
std::unique_ptr<icu::RegexMatcher> pretok_matcher(
m_pretok_re->matcher(uinput, uerror));
std::vector<icu::UnicodeString> pretoks;
if (!U_SUCCESS(uerror))
throw std::runtime_error("Creating BPE pretokenizer matcher failed");
while (pretok_matcher->find()) {
auto match = pretok_matcher->group(uerror);
if (!U_SUCCESS(uerror))
throw std::runtime_error(
"Getting BPE pretokenizer regex match failed");
std::string s;
icu::UnicodeString out;
match.toUTF8String(s);
for (char c : s) {
uint32_t codepoint = m_bs_table.byte_to_codepoint((uint8_t)c);
out.append((UChar32)codepoint);
}
pretoks.push_back(out);
}
return pretoks;
}
static std::string regex_escape(const std::string_view inp) {
std::string s(inp);
static const std::regex metacharacters(R"([\.\^\$\-\+\(\)\[\]\{\}\|\?\*])");
return std::regex_replace(s, metacharacters, "\\$&");
}
AdditionalVocabAdapter::AdditionalVocabAdapter(
const std::vector<additional_vocab_item>& vocab) {
std::string addedtoken_regex;
for (const additional_vocab_item& item : vocab) {
if (!addedtoken_regex.empty()) {
addedtoken_regex += "|";
}
addedtoken_regex += regex_escape(item.content);
m_token_to_id[item.content] = item.id;
m_id_to_token[item.id] = item.content;
if (item.special) {
m_special_ids.insert(item.id);
}
}
m_addedtoken_re = std::regex(addedtoken_regex);
}
std::vector<uint32_t> AdditionalVocabAdapter::encode(
const std::string& input,
BPE& bpemodel,
bool encode_special_tokens) {
if (m_token_to_id.empty()) {
return bpemodel.encode(input);
}
std::vector<uint32_t> out;
std::string work = input;
std::smatch m;
while (std::regex_search(work, m, m_addedtoken_re)) {
auto tokloc = m_token_to_id.find(m.str());
if (tokloc != m_token_to_id.end()) {
auto tokid = tokloc->second;
auto prefix_decoded = bpemodel.encode(m.prefix());
out.insert(out.end(), prefix_decoded.begin(), prefix_decoded.end());
bool special = m_special_ids.find(tokid) != m_special_ids.end();
if (!special || encode_special_tokens) {
out.push_back(tokid);
}
work = m.suffix();
}
}
if (!work.empty()) {
auto rest_decoded = bpemodel.encode(work);
out.insert(out.end(), rest_decoded.begin(), rest_decoded.end());
}
return out;
}
std::string AdditionalVocabAdapter::decode(const std::vector<uint32_t>& tokens,
BPE& bpemodel,
bool decode_special_tokens,
bool valid_utf8) {
std::string out;
std::vector<uint32_t> to_decode;
for (auto tokid : tokens) {
auto tokloc = m_id_to_token.find(tokid);
if (tokloc != m_id_to_token.end()) { // is an added token
if (!to_decode.empty()) {
out += bpemodel.decode(to_decode, valid_utf8);
to_decode.clear();
}
bool special = m_special_ids.find(tokid) != m_special_ids.end();
// only include non-special tokens unless decode_special_tokens
if (!special || decode_special_tokens) {
out += tokloc->second;
}
} else {
// non-added, regular token.
to_decode.push_back(tokid);
}
}
if (!to_decode.empty()) {
out += bpemodel.decode(to_decode, valid_utf8);
}
return out;
}
} // namespace bpecpp