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llama3 custom regex split (#6965)
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* merged the changes from deepseeker models to main branch

* Moved regex patterns to unicode.cpp and updated unicode.h

* Moved header files

* Resolved issues

* added and refactored unicode_regex_split and related functions

* Updated/merged the deepseek coder pr

* Refactored code

* Adding unicode regex mappings

* Adding unicode regex function

* Added needed functionality, testing remains

* Fixed issues

* Fixed issue with gpt2 regex custom preprocessor

* unicode : fix? unicode_wstring_to_utf8

* lint : fix whitespaces

* tests : add tokenizer tests for numbers

* unicode : remove redundant headers

* tests : remove and rename tokenizer test scripts

* tests : add sample usage

* gguf-py : reader prints warnings on duplicate keys

* llama : towards llama3 tokenization support (wip)

* unicode : shot in the dark to fix tests on Windows

* unicode : first try custom implementations

* convert : add "tokenizer.ggml.pre" GGUF KV (wip)

* llama : use new pre-tokenizer type

* convert : fix pre-tokenizer type writing

* lint : fix

* make : add test-tokenizer-0-llama-v3

* wip

* models : add llama v3 vocab file

* llama : adapt punctuation regex + add llama 3 regex

* minor

* unicode : set bomb

* unicode : set bomb

* unicode : always use std::wregex

* unicode : support \p{N}, \p{L} and \p{P} natively

* unicode : try fix windows

* unicode : category support via std::regex

* unicode : clean-up

* unicode : simplify

* llama3 custom regex split

* convert : add convert-hf-to-gguf-update.py

ggml-ci

* lint : update

* convert : add falcon

ggml-ci

* unicode : normalize signatures

* lint : fix

* lint : fix

* convert : remove unused functions

* convert : add comments

* convert : exercise contractions

ggml-ci

* Using char32_t for codepoints

* lint : fix

* already exists unicode_tolower()

* Typing

* Restore BOM

* cmake : refactor test targets

* tests : refactor vocab tests

ggml-ci

* tests : add more vocabs and tests

ggml-ci

* unicode : cleanup

* scripts : ignore new update script in check-requirements.sh

* Fix merge

* models : add phi-3, mpt, gpt-2, starcoder

* tests : disable obsolete

ggml-ci

* tests : use faster bpe test

ggml-ci

* llama : more prominent warning for old BPE models

* tests : disable test-tokenizer-1-bpe due to slowness

ggml-ci

* Move unused variable value

* GPT2 custom regex split

* Add alternative regex for custom aplit llama3

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* Style

* Add bruteforce random tests for token encoding

* wip: fixing unicode codepoint ranges

* Fix merge

* Unicode tables: separator, lowercase, uppercase and whitespace

* llama3 custom regex split: fix \s

* Restore BOM

* Style

* wip: generate NDF table

* Ignore special tokens for testing

* Clean gen-unicode-data.py

* Refactor random tokenizer test

* lint : fix

* tests : add fail test for llama-bpe

---------

Co-authored-by: Jaggzh <jaggz.h@gmail.com>
Co-authored-by: Kazim Abrar Mahi <kazimabrarmahi135@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: jaime-m-p <>
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4 people committed May 9, 2024
1 parent a743d76 commit 43248e5
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Showing 8 changed files with 1,463 additions and 544 deletions.
1 change: 1 addition & 0 deletions convert-hf-to-gguf-update.py
Original file line number Diff line number Diff line change
Expand Up @@ -261,6 +261,7 @@ def get_vocab_base_pre(self, tokenizer) -> str:
"3333333",
"33333333",
"333333333",
# "Cửa Việt", # llama-bpe fails on this
chktxt,
]

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2 changes: 1 addition & 1 deletion llama.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -12488,7 +12488,7 @@ struct llm_tokenizer_wpm {
continue;
}
code = unicode_tolower(code);
if (type == CODEPOINT_TYPE_WHITESPACE) {
if (type == CODEPOINT_TYPE_SEPARATOR) {
code = ' ';
}
std::string s = unicode_cpt_to_utf8(code);
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78 changes: 38 additions & 40 deletions scripts/gen-unicode-data.py
Original file line number Diff line number Diff line change
@@ -1,31 +1,14 @@
import regex


def cpt_to_utf8_str(cpt):
if cpt <= 0xFF:
return bytes([cpt, 0, 0, 0])
elif cpt <= 0xFFFF:
return bytes([cpt & 0xFF, cpt >> 8, 0, 0])
elif cpt <= 0xFFFFFF:
return bytes([cpt & 0xFF, (cpt >> 8) & 0xFF, (cpt >> 16) & 0xFF, 0])
else:
return bytes([cpt & 0xFF, (cpt >> 8) & 0xFF, (cpt >> 16) & 0xFF, cpt >> 24])


def is_match(codepoint, regex_expr):
try:
res = regex.match(regex_expr, cpt_to_utf8_str(codepoint).decode('utf-32'))
return res is not None
except Exception:
return False


def get_matches(regex_expr):
regex_expr_compiled = regex.compile(regex_expr)
unicode_ranges = []
current_range = None

for codepoint in range(0x110000):
if is_match(codepoint, regex_expr):
char = chr(codepoint)
if regex_expr_compiled.match(char):
if current_range is None:
current_range = [codepoint, codepoint]
else:
Expand All @@ -40,27 +23,42 @@ def get_matches(regex_expr):
return unicode_ranges


def print_cat(cat, ranges):
print("const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_{} = {{".format(cat)) # noqa: NP100
cnt = 0
for start, end in ranges:
if cnt % 4 != 0:
print(" ", end="") # noqa: NP100
print("{{0x{:08X}, 0x{:08X}}},".format(start, end), end="") # noqa: NP100
if cnt % 4 == 3:
print("") # noqa: NP100
cnt += 1

if cnt % 4 != 0:
print("") # noqa: NP100
def print_cat(mode, cat, ranges):
if mode == "range":
print("const std::vector<std::pair<uint32_t, uint32_t>> unicode_ranges_{} = {{".format(cat)) # noqa: NP100
if mode == "map":
print("const std::map<uint32_t, uint32_t> unicode_map_{} = {{".format(cat)) # noqa: NP100
for i, values in enumerate(ranges):
end = ",\n" if (i % 4 == 3 or i + 1 == len(ranges)) else ", "
values = ["0x%08X" % value for value in values]
print("{" + ", ".join(values) + "}", end=end) # noqa: NP100
print("};") # noqa: NP100
print("") # noqa: NP100


print_cat("number", get_matches(r'\p{N}'))
print_cat("letter", get_matches(r'\p{L}'))
print_cat("whitespace", get_matches(r'\p{Z}'))
print_cat("accent_mark", get_matches(r'\p{M}'))
print_cat("punctuation", get_matches(r'\p{P}'))
print_cat("symbol", get_matches(r'\p{S}'))
print_cat("control", get_matches(r'\p{C}'))
print_cat("range", "number", get_matches(r'\p{N}'))
print_cat("range", "letter", get_matches(r'\p{L}'))
print_cat("range", "separator", get_matches(r'\p{Z}'))
print_cat("range", "accent_mark", get_matches(r'\p{M}'))
print_cat("range", "punctuation", get_matches(r'\p{P}'))
print_cat("range", "symbol", get_matches(r'\p{S}'))
print_cat("range", "control", get_matches(r'\p{C}'))

print_cat("range", "whitespace", get_matches(r'\s'))


map_lowercase = []
map_uppercase = []
for codepoint in range(0x110000):
char = chr(codepoint)
lower = ord(char.lower()[0])
upper = ord(char.upper()[0])
if codepoint != lower:
map_lowercase.append((codepoint, lower))
if codepoint != upper:
map_uppercase.append((codepoint, upper))
print_cat("map", "lowercase", map_lowercase)
print_cat("map", "uppercase", map_uppercase)


# TODO: generate unicode_map_nfd

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