mirror of
https://github.com/ggml-org/llama.cpp.git
synced 2025-11-04 09:32:00 +00:00
f4ab2a4147
* 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
* 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
* lint : fix
* 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
* 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
---------
Co-authored-by: Jaggzh <jaggz.h@gmail.com>
Co-authored-by: Kazim Abrar Mahi <kazimabrarmahi135@gmail.com>
118 lines
3.4 KiB
Python
118 lines
3.4 KiB
Python
# tests with BPE tokenizer
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#
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# sample usage:
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#
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# python3 tests/test-tokenizer-0-bpe.py ~/Data/huggingface/Meta-Llama-3-8B-Instruct/
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# python3 tests/test-tokenizer-0-bpe.py ~/Data/huggingface/falcon-7b/
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# python3 tests/test-tokenizer-0-bpe.py ~/Data/huggingface/deepseek-coder-6.7b-instruct/
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#
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import argparse
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from transformers import AutoTokenizer
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parser = argparse.ArgumentParser()
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parser.add_argument("dir_tokenizer", help="directory containing 'tokenizer.model' file")
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parser.add_argument("--fname-tok", help="path to a text file to tokenize")
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args = parser.parse_args()
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dir_tokenizer = args.dir_tokenizer
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tokenizer = AutoTokenizer.from_pretrained(dir_tokenizer)
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tests = [
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"",
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" ",
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" ",
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" ",
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"\t",
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"\n",
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"\n\n",
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"\n\n\n",
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"\t\n",
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"Hello world",
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" Hello world",
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"Hello World",
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" Hello World",
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" Hello World!",
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"Hello, world!",
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" Hello, world!",
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" this is 🦙.cpp",
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"w048 7tuijk dsdfhu",
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"нещо на Български",
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"កាន់តែពិសេសអាចខលចេញ",
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"🚀 (normal) 😶🌫️ (multiple emojis concatenated) ✅ (only emoji that has its own token)",
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"Hello",
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" Hello",
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" Hello",
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" Hello",
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" Hello",
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" Hello\n Hello",
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" (",
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"\n =",
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"' era",
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"Hello, y'all! How are you 😁 ?我想在apple工作1314151天～",
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"3",
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"33",
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"333",
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"3333",
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"33333",
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"333333",
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"3333333",
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"33333333",
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"333333333",
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]
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for text in tests:
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print('text: ', text)
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print(tokenizer.encode(text))
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print(tokenizer.decode(tokenizer.encode(text)))
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print("\n\ntests for C++:\n")
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for text in tests:
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res = tokenizer.encode(text)
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k = text.replace('\n', '\\n')
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k = k.replace('\t', '\\t')
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k = '"' + k + '"'
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print("{ %-24s, { " % k, end='')
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for x in res:
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print("%7d," % x, end='')
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print(" }, },")
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print(tokenizer.encode('hello'))
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print(tokenizer.encode('world'))
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print(tokenizer.encode(' world'))
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print(tokenizer.encode('hello world'))
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fname_tok = args.fname_tok
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if fname_tok:
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print('tokenizing file: ', fname_tok)
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fname_out = fname_tok + '.tok'
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with open(fname_tok, 'r', encoding='utf-8') as f:
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lines = f.readlines()
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s = ''.join(lines)
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res = tokenizer.encode(s)
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# write to file
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with open(fname_out, 'w', encoding='utf-8') as f:
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for x in res:
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# LLaMA v3 for some reason strips the space for these tokens (and others)
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# if x == 662:
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# f.write(str(x) + ' \' ' + tokenizer.decode(x) + '\'\n')
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# elif x == 1174:
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# f.write(str(x) + ' \' ' + tokenizer.decode(x) + '\'\n')
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# elif x == 2564:
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# f.write(str(x) + ' \' ' + tokenizer.decode(x) + '\'\n')
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# elif x == 758:
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# f.write(str(x) + ' \' ' + tokenizer.decode(x) + '\'\n')
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# elif x == 949:
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# f.write(str(x) + ' \' ' + tokenizer.decode(x) + '\'\n')
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# elif x == 5354:
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# f.write(str(x) + ' \' ' + tokenizer.decode(x) + '\'\n')
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# else:
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# f.write(str(x) + ' \'' + tokenizer.decode(x) + '\'\n')
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f.write(str(x) + ' \'' + tokenizer.decode(x).strip() + '\'\n')
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print('len(res): ', len(res))
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print('len(lines): ', len(lines))
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print('results written to: ', fname_out)
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