vocab/gpt_35_turbo/__init__.py

"""
，请
"""

import tiktoken
from tiktoken import Encoding
from utils.log_util import logger

tokenizer = tiktoken.encoding_for_model('gpt-3.5-turbo')
tokenizer.vocab_size = tokenizer.n_vocab

tokenizer.comments = "tiktoken is a fast BPE tokeniser for use with OpenAI's models. There are 16 tokens KeyError"
tokenizer.reversible = True  # It's reversible and lossless, so you can convert tokens back into the original text


def decode(self, tokens, errors="replace", skip_special_tokens=False):
    """
    默认的decode，可能会报错，详见 decode_test.py
    skip_special_tokens 是为了兼容 hf_tokenizer
    """
    try:
        decode_str = self._core_bpe.decode_bytes(tokens).decode("utf-8", errors=errors)
    except:
        decode_str = "null"
    return decode_str


def convert_ids_to_tokens(self, tokens, skip_special_tokens=False):
    """
    为什么没有这个方法？
    """
    try:
        return self.decode_tokens_bytes(tokens)
    except Exception as e:
        # 什么要返回None？见zh_util.py
        # 16个空闲id, 100256 100261-100275
        logger.error(e)
        return [None for _ in tokens]


def get_vocab(self, token_type="str"):
    """Returns vocab as a dict
    :param token_type: ["str", "byte"]
    :return:
    """
    vocab = {}
    key_error_list = []
    unicode_decode_error_list = []
    for i in range(self.vocab_size):
        try:
            token_byte = self.convert_ids_to_tokens([i])[0]
            if token_byte is None:
                continue
            # token_str = token_byte.decode("utf-8")
            vocab[token_byte] = i

        except UnicodeDecodeError:  # 773 UnicodeDecodeError
            unicode_decode_error_list.append((i, str(token_byte)))
            vocab[token_byte] = i

    # vocab.update(self.added_tokens_encoder)
    logger.info(f"gpt_35_turbo {len(key_error_list)} KeyError: {key_error_list}")
    logger.info(f"gpt_35_turbo {len(unicode_decode_error_list)} UnicodeDecodeError: {unicode_decode_error_list[:5]}")
    return vocab


def encode(self, *args, **kwargs):
    """
    add_special_token 是为了兼容 hf_tokenizer
    """
    kwargs.pop("add_special_tokens", None)
    return self._encode(*args, **kwargs)


# tiktoken patch
Encoding._encode = Encoding.encode
Encoding.encode = encode
Encoding.decode = decode
Encoding.convert_ids_to_tokens = convert_ids_to_tokens
Encoding.get_vocab = get_vocab