1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
|
- """Byte pair encoding utilities"""
- import os
- import json
- import regex as re
- from functools import lru_cache
- @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
- class Encoder:
- def __init__(self, encoder, bpe_merges, errors='replace'):
- self.encoder = encoder
- self.decoder = {v:k for k,v in self.encoder.items()}
- self.errors = errors # how to handle errors in decoding
- self.byte_encoder = bytes_to_unicode()
- self.byte_decoder = {v:k for k, v in self.byte_encoder.items()}
- self.bpe_ranks = dict(zip(bpe_merges, range(len(bpe_merges))))
- self.cache = {}
- # Should haved added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
- self.pat = re.compile(r"""'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+""")
- def bpe(self, token):
- if token in self.cache:
- return self.cache[token]
- word = tuple(token)
- pairs = get_pairs(word)
- if not pairs:
- return token
- 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 = []
- 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=self.errors)
- return text
- def get_encoder(model_name, models_dir):
- with open(os.path.join(models_dir, model_name, 'encoder.json'), 'r') as f:
- encoder = json.load(f)
- with open(os.path.join(models_dir, model_name, 'vocab.bpe'), 'r', encoding="utf-8") as f:
- bpe_data = f.read()
- bpe_merges = [tuple(merge_str.split()) for merge_str in bpe_data.split('\n')[1:-1]]
- return Encoder(
- encoder=encoder,
- bpe_merges=bpe_merges,
- )
|