llama3 custom regex split (ggml-org#6965)

* 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 <[email protected]>

* 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 <[email protected]>
Co-authored-by: Kazim Abrar Mahi <[email protected]>
Co-authored-by: Georgi Gerganov <[email protected]>
Co-authored-by: jaime-m-p <>

Author: 4 people

convert-hf-to-gguf-update.py

@@ -261,6 +261,7 @@ def get_vocab_base_pre(self, tokenizer) -> str:
     "3333333",
     "33333333",
     "333333333",
+    # "Cửa Việt", # llama-bpe fails on this
     chktxt,
 ]
 

llama.cpp

@@ -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);

scripts/gen-unicode-data.py

@@ -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:
@@ -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