| @@ -0,0 +1,149 @@ | |||||
| import gzip | |||||
| import html | |||||
| import os | |||||
| from functools import lru_cache | |||||
| import ftfy | |||||
| import regex as re | |||||
| @lru_cache() | |||||
| def default_bpe(): | |||||
| return os.path.join(os.path.dirname(os.path.abspath(__file__)), | |||||
| "bpe_simple_vocab_16e6.txt.gz") | |||||
| @lru_cache() | |||||
| def bytes_to_unicode(): | |||||
| """ | |||||
| Returns list of utf-8 byte and a corresponding list of unicode strings. | |||||
| The reversible bpe codes work on unicode strings. | |||||
| This means you need a large # of unicode characters in your vocab if you want to avoid UNKs. | |||||
| When you're at something like a 10B token dataset you end up needing around 5K for decent coverage. | |||||
| This is a signficant percentage of your normal, say, 32K bpe vocab. | |||||
| To avoid that, we want lookup tables between utf-8 bytes and unicode strings. | |||||
| And avoids mapping to whitespace/control characters the bpe code barfs on. | |||||
| """ | |||||
| bs = list(range(ord("!"), | |||||
| ord("~") + 1)) + list(range( | |||||
| ord("¡"), | |||||
| ord("¬") + 1)) + list(range(ord("®"), | |||||
| ord("ÿ") + 1)) | |||||
| cs = bs[:] | |||||
| n = 0 | |||||
| for b in range(2**8): | |||||
| if b not in bs: | |||||
| bs.append(b) | |||||
| cs.append(2**8 + n) | |||||
| n += 1 | |||||
| cs = [chr(n) for n in cs] | |||||
| return dict(zip(bs, cs)) | |||||
| def get_pairs(word): | |||||
| """Return set of symbol pairs in a word. | |||||
| Word is represented as tuple of symbols (symbols being variable-length strings). | |||||
| """ | |||||
| pairs = set() | |||||
| prev_char = word[0] | |||||
| for char in word[1:]: | |||||
| pairs.add((prev_char, char)) | |||||
| prev_char = char | |||||
| return pairs | |||||
| def basic_clean(text): | |||||
| text = ftfy.fix_text(text) | |||||
| text = html.unescape(html.unescape(text)) | |||||
| return text.strip() | |||||
| def whitespace_clean(text): | |||||
| text = re.sub(r'\s+', ' ', text) | |||||
| text = text.strip() | |||||
| return text | |||||
| class SimpleTokenizer(object): | |||||
| def __init__(self, bpe_path: str = default_bpe()): | |||||
| self.byte_encoder = bytes_to_unicode() | |||||
| self.byte_decoder = {v: k for k, v in self.byte_encoder.items()} | |||||
| merges = gzip.open(bpe_path).read().decode("utf-8").split('\n') | |||||
| merges = merges[1:49152 - 256 - 2 + 1] | |||||
| merges = [tuple(merge.split()) for merge in merges] | |||||
| vocab = list(bytes_to_unicode().values()) | |||||
| vocab = vocab + [v + '</w>' for v in vocab] | |||||
| for merge in merges: | |||||
| vocab.append(''.join(merge)) | |||||
| vocab.extend(['<|startoftext|>', '<|endoftext|>']) | |||||
| self.encoder = dict(zip(vocab, range(len(vocab)))) | |||||
| self.decoder = {v: k for k, v in self.encoder.items()} | |||||
| self.bpe_ranks = dict(zip(merges, range(len(merges)))) | |||||
| self.cache = { | |||||
| '<|startoftext|>': '<|startoftext|>', | |||||
| '<|endoftext|>': '<|endoftext|>' | |||||
| } | |||||
| self.pat = re.compile( | |||||
| r"""<\|startoftext\|>|<\|endoftext\|>|'s|'t|'re|'ve|'m|'ll|'d|[\p{L}]+|[\p{N}]|[^\s\p{L}\p{N}]+""", | |||||
| re.IGNORECASE) | |||||
| def bpe(self, token): | |||||
| if token in self.cache: | |||||
| return self.cache[token] | |||||
| word = tuple(token[:-1]) + (token[-1] + '</w>', ) | |||||
| pairs = get_pairs(word) | |||||
| if not pairs: | |||||
| return token + '</w>' | |||||
| while True: | |||||
| bigram = min( | |||||
| pairs, key=lambda pair: self.bpe_ranks.get(pair, float('inf'))) | |||||
| if bigram not in self.bpe_ranks: | |||||
| break | |||||
| first, second = bigram | |||||
| new_word = [] | |||||
| i = 0 | |||||
| while i < len(word): | |||||
| try: | |||||
| j = word.index(first, i) | |||||
| new_word.extend(word[i:j]) | |||||
| i = j | |||||
| except: | |||||
| new_word.extend(word[i:]) | |||||
| break | |||||
| if word[i] == first and i < len(word) - 1 and word[ | |||||
| i + 1] == second: | |||||
| new_word.append(first + second) | |||||
| i += 2 | |||||
| else: | |||||
| new_word.append(word[i]) | |||||
| i += 1 | |||||
| new_word = tuple(new_word) | |||||
| word = new_word | |||||
| if len(word) == 1: | |||||
| break | |||||
| else: | |||||
| pairs = get_pairs(word) | |||||
| word = ' '.join(word) | |||||
| self.cache[token] = word | |||||
| return word | |||||
| def encode(self, text): | |||||
| bpe_tokens = [] | |||||
| text = whitespace_clean(basic_clean(text)).lower() | |||||
| for token in re.findall(self.pat, text): | |||||
| token = ''.join(self.byte_encoder[b] | |||||
| for b in token.encode('utf-8')) | |||||
| bpe_tokens.extend(self.encoder[bpe_token] | |||||
| for bpe_token in self.bpe(token).split(' ')) | |||||
| return bpe_tokens | |||||
| def decode(self, tokens): | |||||
| text = ''.join([self.decoder[token] for token in tokens]) | |||||
| text = bytearray([self.byte_decoder[c] for c in text | |||||
| ]).decode('utf-8', | |||||
| errors="replace").replace('</w>', ' ') | |||||
| return text | |||||