233 lines
7.5 KiB
Python
233 lines
7.5 KiB
Python
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########################################################################################################
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# The RWKV Language Model - https://github.com/BlinkDL/RWKV-LM
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# Source: https://github.com/BlinkDL/ChatRWKV/blob/main/tokenizer/rwkv_tokenizer.py
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########################################################################################################
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import os, sys, time, random
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print('''
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#######################################################################################################################
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This tokenizer is not used in any RWKV models yet. I plan to use it for the future multilang RWKV models.
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Benefits:
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* Good support of most languages, from European to CJK to Arabic and Hindi and more.
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* Clean vocab. Good for code too. Vocab size = 65525 (use 0 for <|endoftext|>).
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* Good at numbers: the numerical tokens are '0'~'9', '10'~'99', ' 0'~' 9', ' 10'~' 99'.
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* Very easy tokenization:
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** The input text must be in UTF-8.
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** Greedy encoding: always pick the longest (in bytes) token (with the highest id) that matches your UTF-8 bytes.
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* The tokenization result is surprisingly good, because the vocab respects word boundaries and UTF-8 boundaries.
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For 10x faster speed:
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mypyc rwkv_tokenizer.py
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python3 -c "import rwkv_tokenizer"
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#######################################################################################################################
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''')
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########################################################################################################
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# Tokenizer #1 (reference, naive, slow)
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########################################################################################################
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class RWKV_TOKENIZER():
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table = None # : list[list[list[bytes]]] = None
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good = None # : list[set[int]]
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wlen = None # : list[int]
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def __init__(self, file_name):
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self.vocab_size = 65525
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self.idx2token = {}
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sorted = [] # must be already sorted
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lines = open(file_name, "r", encoding="utf-8").readlines()
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for l in lines:
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idx = int(l[:l.index(' ')])
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x = eval(l[l.index(' '):l.rindex(' ')])
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x = x.encode("utf-8") if isinstance(x, str) else x
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assert isinstance(x, bytes)
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assert len(x) == int(l[l.rindex(' '):])
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sorted += [x]
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self.idx2token[idx] = x
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self.token2idx = {}
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for k, v in self.idx2token.items():
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self.token2idx[v] = int(k)
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# precompute some tables for fast matching
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self.table = [[[] for j in range(256)] for i in range(256)]
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self.good = [set() for i in range(256)]
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self.wlen = [0 for i in range(256)]
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for i in reversed(range(len(sorted))): # reverse order - match longer tokens first
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s = sorted[i]
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if len(s) >= 2:
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s0 = int(s[0])
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s1 = int(s[1])
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self.table[s0][s1] += [s]
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self.wlen[s0] = max(self.wlen[s0], len(s))
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self.good[s0].add(s1)
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def encodeBytes(self, src: bytes):
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src_len: int = len(src)
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tokens = []
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i: int = 0
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while i < src_len:
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s: bytes = src[i : i + 1]
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if i < src_len - 1:
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s1: int = int(src[i + 1])
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s0: int = int(src[i])
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if s1 in self.good[s0]:
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sss: bytes = src[i : i + self.wlen[s0]]
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try:
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s = next(filter(sss.startswith, self.table[s0][s1]))
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except:
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pass
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tokens.append(self.token2idx[s])
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i += len(s)
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return tokens
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def decodeBytes(self, tokens):
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return b''.join(map(lambda i: self.idx2token[i], tokens))
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def encode(self, src: str):
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return self.encodeBytes(src.encode("utf-8"))
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def decode(self, tokens):
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return self.decodeBytes(tokens).decode('utf-8')
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def token_to_id(self, token):
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return self.token2idx[token]
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def get_vocab_size(self):
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return self.vocab_size
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def get_vocab(self):
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return self.idx2token
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def printTokens(self, tokens):
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for i in tokens:
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s = self.idx2token[i]
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try:
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s = s.decode('utf-8')
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except:
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pass
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print(f'{repr(s)}{i}', end=' ')
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# print(repr(s), i)
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print()
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########################################################################################################
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# Tokenizer #2 (trie, faster) https://github.com/TkskKurumi/ChatRWKV-TRIE-Tokenizer
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########################################################################################################
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class TRIE:
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__slots__ = tuple("ch,to,values,front".split(","))
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to:list
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values:set
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def __init__(self, front=None, ch=None):
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self.ch = ch
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self.to = [None for ch in range(256)]
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self.values = set()
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self.front = front
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def __repr__(self):
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fr = self
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ret = []
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while(fr!=None):
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if(fr.ch!=None):
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ret.append(fr.ch)
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fr = fr.front
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return "<TRIE %s %s>"%(ret[::-1], self.values)
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def add(self, key:bytes, idx:int=0, val=None):
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if(idx == len(key)):
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if(val is None):
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val = key
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self.values.add(val)
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return self
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ch = key[idx]
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if(self.to[ch] is None):
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self.to[ch] = TRIE(front=self, ch=ch)
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return self.to[ch].add(key, idx=idx+1, val=val)
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def find_longest(self, key:bytes, idx:int=0):
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u:TRIE = self
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ch:int = key[idx]
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while(u.to[ch] is not None):
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u = u.to[ch]
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idx += 1
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if(u.values):
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ret = idx, u, u.values
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if(idx==len(key)):
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break
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ch = key[idx]
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return ret
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class TRIE_TOKENIZER():
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def __init__(self, file_name):
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self.vocab_size = 65525
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self.idx2token = {}
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sorted = [] # must be already sorted
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with open(file_name, "r", encoding="utf-8") as f:
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lines = f.readlines()
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for l in lines:
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idx = int(l[:l.index(' ')])
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x = eval(l[l.index(' '):l.rindex(' ')])
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x = x.encode("utf-8") if isinstance(x, str) else x
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assert isinstance(x, bytes)
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assert len(x) == int(l[l.rindex(' '):])
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sorted += [x]
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self.idx2token[idx] = x
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self.token2idx = {}
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for k,v in self.idx2token.items():
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self.token2idx[v] = int(k)
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self.root = TRIE()
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for t, i in self.token2idx.items():
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_ = self.root.add(t, val=(t, i))
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def encodeBytes(self, src:bytes):
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idx:int = 0
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tokens = []
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while (idx < len(src)):
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_idx:int = idx
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idx, _, values = self.root.find_longest(src, idx)
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assert(idx != _idx)
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_, token = next(iter(values))
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tokens.append(token)
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return tokens
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def decodeBytes(self, tokens):
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return b''.join(map(lambda i: self.idx2token[i], tokens))
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def encode(self, src):
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return self.encodeBytes(src.encode("utf-8"))
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def decode(self, tokens):
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return self.decodeBytes(tokens).decode('utf-8')
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def get_vocab_size(self):
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return self.vocab_size
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def get_vocab(self):
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return self.idx2token
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def printTokens(self, tokens):
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for i in tokens:
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s = self.idx2token[i]
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try:
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s = s.decode('utf-8')
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except:
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pass
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print(f'{repr(s)}{i}', end=' ')
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print()
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