Refactor: unify invoke format of open() function

style_bert_vits2/nlp/bert_models.py

@@ -39,7 +39,7 @@ def load_model(
     language: Languages,
     pretrained_model_name_or_path: Optional[str] = None,
     cache_dir: Optional[str] = None,
-    revision: str = 'main',
+    revision: str = "main",
 ) -> Union[PreTrainedModel, DebertaV2Model]:
     """
     指定された言語の BERT モデルをロードし、ロード済みの BERT モデルを返す。
@@ -96,7 +96,7 @@ def load_tokenizer(
     language: Languages,
     pretrained_model_name_or_path: Optional[str] = None,
     cache_dir: Optional[str] = None,
-    revision: str = 'main',
+    revision: str = "main",
 ) -> Union[PreTrainedTokenizer, PreTrainedTokenizerFast, DebertaV2Tokenizer]:
     """
     指定された言語の BERT モデルをロードし、ロード済みの BERT トークナイザーを返す。

style_bert_vits2/nlp/chinese/g2p.py

@@ -8,10 +8,11 @@ from style_bert_vits2.nlp.chinese.tone_sandhi import ToneSandhi
 from style_bert_vits2.nlp.symbols import PUNCTUATIONS
 
 
-__PINYIN_TO_SYMBOL_MAP = {
-    line.split("\t")[0]: line.strip().split("\t")[1]
-    for line in open(Path(__file__).parent / "opencpop-strict.txt").readlines()
-}
+with open(Path(__file__).parent / "opencpop-strict.txt", "r", encoding="utf-8") as f:
+    __PINYIN_TO_SYMBOL_MAP = {
+        line.split("\t")[0]: line.strip().split("\t")[1]
+        for line in f.readlines()
+    }
 
 
 def g2p(text: str) -> tuple[list[str], list[int], list[int]]:

style_bert_vits2/nlp/english/cmudict.py

@@ -20,7 +20,7 @@ def get_dict() -> dict[str, list[list[str]]]:
 def read_dict() -> dict[str, list[list[str]]]:
     g2p_dict = {}
     start_line = 49
-    with open(CMU_DICT_PATH) as f:
+    with open(CMU_DICT_PATH, "r", encoding="utf-8") as f:
         line = f.readline()
         line_index = 1
         while line: