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import re
import torch
import torch.nn.functional as F
class CustomRepetitionPenaltyLogitsProcessorRepeat():
def __init__(self, penalty: float, max_input_ids, past_window):
if not isinstance(penalty, float) or not (penalty > 0):
raise ValueError(f"`penalty` has to be a strictly positive float, but is {penalty}")
self.penalty = penalty
self.max_input_ids = max_input_ids
self.past_window = past_window
def __call__(self, input_ids: torch.LongTensor, scores: torch.FloatTensor) -> torch.FloatTensor:
input_ids = input_ids[:, -self.past_window:]
freq = F.one_hot(input_ids, scores.size(1)).sum(1)
freq[self.max_input_ids:] = 0
alpha = self.penalty**freq
scores = torch.where(scores < 0, scores*alpha, scores/alpha)
return scores
class CustomRepetitionPenaltyLogitsProcessor():
def __init__(self, penalty: float, max_input_ids, past_window):
if not isinstance(penalty, float) or not (penalty > 0):
raise ValueError(f"`penalty` has to be a strictly positive float, but is {penalty}")
self.penalty = penalty
self.max_input_ids = max_input_ids
self.past_window = past_window
def __call__(self, input_ids: torch.LongTensor, scores: torch.FloatTensor) -> torch.FloatTensor:
input_ids = input_ids[:, -self.past_window:]
score = torch.gather(scores, 1, input_ids)
_score = score.detach().clone()
score = torch.where(score < 0, score * self.penalty, score / self.penalty)
score[input_ids>=self.max_input_ids] = _score[input_ids>=self.max_input_ids]
scores.scatter_(1, input_ids, score)
return scores
def count_invalid_characters(s):
s = re.sub(r'\[uv_break\]|\[laugh\]|\[lbreak\]', '', s)
pattern = re.compile(r'[^\u4e00-\u9fffA-Za-z，。、,\. ]')
non_alphabetic_chinese_chars = pattern.findall(s)
return set(non_alphabetic_chinese_chars)
def detect_language(sentence):
chinese_char_pattern = re.compile(r'[\u4e00-\u9fff]')
english_word_pattern = re.compile(r'\b[A-Za-z]+\b')
chinese_chars = chinese_char_pattern.findall(sentence)
english_words = english_word_pattern.findall(sentence)
if len(chinese_chars) > len(english_words):
return "zh"
else:
return "en"
character_map = {
'：': '，',
'；': '，',
'！': '。',
'（': '，',
'）': '，',
'【': '，',
'】': '，',
'『': '，',
'』': '，',
'「': '，',
'」': '，',
'《': '，',
'》': '，',
'－': '，',
'‘': '',
'“': '',
'’': '',
'”': '',
':': ',',
';': ',',
'!': '.',
'(': ',',
')': ',',
'[': ',',
']': ',',
'>': ',',
'<': ',',
'-': ',',
}
halfwidth_2_fullwidth_map = {
'!': '！',
'"': '“',
"'": '‘',
'#': '＃',
'$': '＄',
'%': '％',
'&': '＆',
'(': '（',
')': '）',
',': '，',
'-': '－',
'*': '＊',
'+': '＋',
'.': '。',
'/': '／',
':': '：',
';': '；',
'<': '＜',
'=': '＝',
'>': '＞',
'?': '？',
'@': '＠',
# '[': '［',
'\\': '＼',
# ']': '］',
'^': '＾',
# '_': '＿',
'`': '｀',
'{': '｛',
'|': '｜',
'}': '｝',
'~': '～'
}
def apply_half2full_map(text):
translation_table = str.maketrans(halfwidth_2_fullwidth_map)
return text.translate(translation_table)
def apply_character_map(text):
translation_table = str.maketrans(character_map)
return text.translate(translation_table) |