update cache GC in demo and add vocab expansion example
yangapku
1 year ago
parent
343017c4ce
commit
cbfaada8de
@ -0,0 +1,226 @@
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import argparse
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import base64
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import collections
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import logging
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import unicodedata
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from pathlib import Path
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import regex as re
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from tqdm.contrib.logging import tqdm_logging_redirect
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PAT_STR = r"""(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+"""
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logger = logging.getLogger(__name__)
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logging.basicConfig(
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level=logging.DEBUG, format="[%(asctime)s] %(levelname)s - %(message)s"
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)
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def load_tiktoken_bpe(tiktoken_bpe_file: str) -> "dict[bytes, int]":
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contents = open(tiktoken_bpe_file, "rb").read()
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return {
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base64.b64decode(token): int(rank)
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for token, rank in (line.split() for line in contents.splitlines() if line)
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}
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def dump_tiktoken_bpe(bpe_ranks: "dict[bytes, int]", tiktoken_bpe_file: str) -> None:
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with open(tiktoken_bpe_file, "wb") as f:
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for token, rank in sorted(bpe_ranks.items(), key=lambda x: x[1]):
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f.write(base64.b64encode(token) + b" " + str(rank).encode() + b"\n")
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def bytes_to_pieces(the_bytes: bytes) -> "tuple[bytes]":
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return tuple(bytes([byte]) for byte in the_bytes)
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def get_pairs(pieces: "tuple[bytes]") -> "set[tuple[bytes, bytes]]":
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return set(zip(pieces[:-1], pieces[1:]))
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def get_stats(
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vocab: "dict[tuple[bytes, ...], int]",
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) -> "dict[tuple[bytes, bytes], int]":
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pairs = collections.defaultdict(int)
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for word, freq in vocab.items():
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for i in range(len(word) - 1):
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pairs[(word[i], word[i + 1])] += freq
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return pairs
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def merge_vocab(
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pair: "tuple[bytes, bytes]", vocab: "dict[tuple[bytes, ...], int]"
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) -> "dict[tuple[bytes, ...], int]":
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return {apply_bp(pieces, pair): freq for pieces, freq in vocab.items()}
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def apply_bp(
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pieces: "tuple[bytes, ...]", pair: "tuple[bytes, bytes]"
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) -> "tuple[bytes, ...]":
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new_pieces = []
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first, second = pair
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i = 0
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while i < len(pieces):
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try:
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j = pieces.index(first, i)
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new_pieces.extend(pieces[i:j])
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i = j
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except:
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new_pieces.extend(pieces[i:])
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break
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if pieces[i] == first and i < len(pieces) - 1 and pieces[i + 1] == second:
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new_pieces.append(first + second)
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i += 2
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else:
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new_pieces.append(pieces[i])
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i += 1
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return tuple(new_pieces)
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def bpe(word: bytes, merges: "dict[bytes,int]") -> "tuple[bytes, ...]":
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pieces = bytes_to_pieces(word)
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while len(pieces) > 1:
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pairs = get_pairs(pieces)
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pair = min(pairs, key=lambda pair: merges.get(pair[0] + pair[1], float("inf")))
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if pair[0] + pair[1] not in merges:
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break
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pieces = apply_bp(pieces, pair)
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# logger.debug(f"{[(p, p.decode('utf8', errors='replace')) for p in pieces]} {pair} {pieces}")
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return pieces
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def best_pair_sort_key(
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item: "tuple[dict[bytes, bytes], int]",
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) -> "tuple[int, int, int, str, bytes]":
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# prefer to use the highest frequency or shortest length or lexi sort, sligtly slower
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pair, freq = item
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pair_bytes = pair[0] + pair[1]
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pair_byte_length = len(pair_bytes)
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pair_str = pair_bytes.decode("utf-8", errors="replace")
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pair_str_length = len(pair_str)
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return -freq, pair_str_length, pair_byte_length, pair_str, pair_bytes
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def learn_bpe(
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freqs: "dict[str,int]", existing: "dict[bytes, int]"
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) -> "tuple[bytes, bytes]":
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vocab = {bpe(k.encode("utf-8"), existing): v for k, v in freqs.items()}
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vocab = {key: value for key, value in vocab.items() if len(key) > 1}
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new_merges = []
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with tqdm_logging_redirect() as bar:
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while vocab:
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pairs = get_stats(vocab)
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best, freq = min(pairs.items(), key=best_pair_sort_key)
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logger.debug(
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f'{best} ({(best[0]+best[1]).decode("utf-8", errors="replace")}) is selected as the next merge with freq {freq}'
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)
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new_merges.append(best)
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vocab = merge_vocab(best, vocab)
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vocab = {key: value for key, value in vocab.items() if len(key) > 1}
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bar.update()
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return new_merges
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def load_expand_vocab(path: Path) -> "dict[str, int]":
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freqs = {}
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with open(path, "r", encoding="utf8") as fin:
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for line in fin:
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if not line.strip():
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continue
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word, freq = line.strip().split("\t")
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word = unicodedata.normalize("NFC", word)
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parts = re.findall(PAT_STR, word)
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if len(parts) > 1:
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logger.warning(
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f"{word} would be pre-tokenized to {parts}, and thus cannot be added to vocabulary"
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)
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continue
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try:
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freq = int(freq)
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except ValueError as _:
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freq = 1
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if word in freqs:
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logger.warning(
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f"{word} is repeated, the frequency is increased by this much"
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)
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freqs[word] += freq
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else:
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freqs[word] = freq
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return freqs
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def make_new_merges_by_bpe(
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input_path: Path, output_path: Path, expand_path: Path, start_id: int
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) -> None:
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mergeable_ranks = load_tiktoken_bpe(input_path)
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if not start_id or start_id == -1:
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start_id = len(mergeable_ranks)
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elif start_id < len(mergeable_ranks):
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logger.warning(
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f"start_id {start_id} is too small, existing merges will be overridden, DONOT DO THIS. changed to {len(mergeable_ranks)}"
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)
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start_id = len(mergeable_ranks)
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else:
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start_id = start_id
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expand_vocab_freqs = load_expand_vocab(expand_path)
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for word in list(expand_vocab_freqs):
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token = word.encode("utf-8")
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if token in mergeable_ranks:
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logger.warning(f"word {word} is already a token {token}, skipping")
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del expand_vocab_freqs[word]
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logger.info(f"number of existing merges: {len(mergeable_ranks)}")
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logger.info(f"number of words for expanding: {len(expand_vocab_freqs)}")
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new_merges = learn_bpe(expand_vocab_freqs, mergeable_ranks)
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logger.info(f"number of newly learned merges: {len(new_merges)}")
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extra_merges = {p[0] + p[1]: i for i, p in enumerate(new_merges, start=start_id)}
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dump_tiktoken_bpe(extra_merges, output_path)
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def main():
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parser = argparse.ArgumentParser(
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formatter_class=argparse.ArgumentDefaultsHelpFormatter
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)
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parser.add_argument("input_path", type=str, help="Path for input tiktoken file")
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parser.add_argument(
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"output_path",
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type=str,
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help="Path for output tiktoken file, containing only the new merges",
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)
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parser.add_argument(
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"vocab_path",
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type=str,
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help="Path for words needed adding, each line is a word and its frequency separated by \\t",
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)
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# if the extended vocabulary is for fine-tuning, you better set those correctly (the default is for qwen.tiktoken)
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# if the extended vocabulary is for pretraining from the start, no need
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parser.add_argument(
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"--start_id",
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type=int,
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default=151851,
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help="The start id for new merges. For Qwen tokenizer, this should be 151851 (skipping the existing special tokens)",
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)
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args = parser.parse_args()
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make_new_merges_by_bpe(
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args.input_path, args.output_path, args.vocab_path, args.start_id
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)
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if __name__ == "__main__":
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main()
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@ -0,0 +1,6 @@
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5LiA5Y+q54yr 151851
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5Y+q54yr 151852
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5piv5LiA5Y+q54yr 151853
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5oiR5piv5LiA5Y+q54yr 151854
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5L2g5piv5LiA5Y+q54yr 151855
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5LuW5piv5LiA5Y+q54yr 151856
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@ -0,0 +1,6 @@
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我是一只猫 20
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你是一只猫 10
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他是一只猫 5
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一只 200
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一只猫 100
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夸张的 比喻手法 20
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