learningself / ChatTTS /utils /infer_utils.py
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初始化项目
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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)