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63 lines
2.2 KiB
Python

import numpy as np
from typing import *
from transformers import AutoTokenizer
from transformers.models.gpt2 import GPT2TokenizerFast
def encode_whitespaces(text: str, start_extra_id: int, max_len: int):
""" Encode whitespaces to extra tokens.
>>> encode_whitespaces('a\\n b\\n c', 10, 10)
'a\\n<|extratoken_10|>b\\n<|extratoken_11|>c'
"""
for i in np.arange(max_len, 1, -1):
text = text.replace(" " * i, f"<|extratoken_{start_extra_id + i - 2}|>")
return text
def decode_whitespaces(text: str, start_extra_id: int, max_len: int):
""" Decode the whitespace-encoded strings produced by encode_whitespace.
>>> text = 'a\\n b\\n c'
>>> s, l = 10, 10
>>> text == decode_whitespaces(encode_whitespaces(text, s, l), s, l)
True
"""
for l in range(2, max_len + 1):
token_id = start_extra_id - 2 + l
token = f'<|extratoken_{token_id}|>'
text = text.replace(token, ' ' * l)
return text
class CodeGeeXTokenizer(object):
def __init__(
self,
tokenizer: GPT2TokenizerFast = None,
tokenizer_path: str = "EleutherAI/gpt-j-6B",
start_extra_id: int = 10,
max_len : int = 10,
mode='codegeex-13b',
dict_file: str = None,
):
self.tokenizer = tokenizer if tokenizer is not None else AutoTokenizer.from_pretrained(tokenizer_path)
if mode not in ['codegeex-13b']:
raise ValueError(f"Invalid mode {mode}, choose from ['codegeex-13b']")
self.start_extra_id = start_extra_id
self.max_len = max_len
self.mode = mode
self.eos_token_id = self.tokenizer.eos_token_id
def encode_code(self, code: str):
if self.mode == 'codegeex-13b':
code = encode_whitespaces(code, self.start_extra_id, self.max_len)
input_ids = self.tokenizer(code, is_split_into_words=False, verbose=False).input_ids
return input_ids
def decode_code(self, input_ids):
if self.mode == 'codegeex-13b':
text = self.tokenizer.decode(input_ids, skip_special_tokens=False, verbose=False)
output_code = decode_whitespaces(text, self.start_extra_id, self.max_len)
return output_code