Fmt only (maybe)

app.py

@@ -4,6 +4,7 @@ from pathlib import Path
 import gradio as gr
 import torch
 
+from config import get_path_config
 from gradio_tabs.dataset import create_dataset_app
 from gradio_tabs.inference import create_inference_app
 from gradio_tabs.merge import create_merge_app
@@ -13,7 +14,6 @@ from style_bert_vits2.constants import GRADIO_THEME, VERSION
 from style_bert_vits2.nlp.japanese import pyopenjtalk_worker
 from style_bert_vits2.nlp.japanese.user_dict import update_dict
 from style_bert_vits2.tts_model import TTSModelHolder
-from config import get_path_config
 
 
 # このプロセスからはワーカーを起動して辞書を使いたいので、ここで初期化

bert_gen.py

@@ -10,10 +10,7 @@ from style_bert_vits2.constants import Languages
 from style_bert_vits2.logging import logger
 from style_bert_vits2.models import commons
 from style_bert_vits2.models.hyper_parameters import HyperParameters
-from style_bert_vits2.nlp import (
+from style_bert_vits2.nlp import cleaned_text_to_sequence, extract_bert_feature
-    cleaned_text_to_sequence,
-    extract_bert_feature,
-)
 from style_bert_vits2.nlp.japanese import pyopenjtalk_worker
 from style_bert_vits2.nlp.japanese.user_dict import update_dict
 from style_bert_vits2.utils.stdout_wrapper import SAFE_STDOUT
@@ -77,10 +74,10 @@ if __name__ == "__main__":
     config_path = args.config
     hps = HyperParameters.load_from_json(config_path)
     lines: list[str] = []
-    with open(hps.data.training_files, "r", encoding="utf-8") as f:
+    with open(hps.data.training_files, encoding="utf-8") as f:
         lines.extend(f.readlines())
 
-    with open(hps.data.validation_files, "r", encoding="utf-8") as f:
+    with open(hps.data.validation_files, encoding="utf-8") as f:
         lines.extend(f.readlines())
     add_blank = [hps.data.add_blank] * len(lines)
 

config.py

@@ -56,8 +56,13 @@ class Preprocess_text_config:
         clean: bool = True,
     ):
         self.transcription_path = Path(transcription_path)
-        self.cleaned_path = Path(cleaned_path)
         self.train_path = Path(train_path)
+        if cleaned_path == "" or cleaned_path is None:
+            self.cleaned_path = self.transcription_path.with_name(
+                self.transcription_path.name + ".cleaned"
+            )
+        else:
+            self.cleaned_path = Path(cleaned_path)
         self.val_path = Path(val_path)
         self.config_path = Path(config_path)
         self.val_per_lang = val_per_lang
@@ -70,7 +75,7 @@ class Preprocess_text_config:
 
         data["transcription_path"] = dataset_path / data["transcription_path"]
         if data["cleaned_path"] == "" or data["cleaned_path"] is None:
-            data["cleaned_path"] = None
+            data["cleaned_path"] = ""
         else:
             data["cleaned_path"] = dataset_path / data["cleaned_path"]
         data["train_path"] = dataset_path / data["train_path"]
@@ -232,7 +237,7 @@ class Config:
                 "Please do not modify default_config.yml. Instead, modify config.yml."
             )
             # sys.exit(0)
-        with open(config_path, "r", encoding="utf-8") as file:
+        with open(config_path, encoding="utf-8") as file:
             yaml_config: dict[str, Any] = yaml.safe_load(file.read())
             model_name: str = yaml_config["model_name"]
             self.model_name: str = model_name
@@ -241,6 +246,7 @@ class Config:
             else:
                 dataset_path = path_config.dataset_root / model_name
             self.dataset_path = dataset_path
+            self.dataset_root = path_config.dataset_root
             self.assets_root = path_config.assets_root
             self.out_dir = self.assets_root / model_name
             self.resample_config: Resample_config = Resample_config.from_dict(
@@ -284,7 +290,7 @@ def get_path_config() -> PathConfig:
         logger.info(
             "Please do not modify configs/default_paths.yml. Instead, modify configs/paths.yml."
         )
-    with open(path_config_path, "r", encoding="utf-8") as file:
+    with open(path_config_path, encoding="utf-8") as file:
         path_config_dict: dict[str, str] = yaml.safe_load(file.read())
     return PathConfig(**path_config_dict)
 

data_utils.py

@@ -7,7 +7,7 @@ import torch
 import torch.utils.data
 from tqdm import tqdm
 
-from config import config
+from config import get_config
 from mel_processing import mel_spectrogram_torch, spectrogram_torch
 from style_bert_vits2.logging import logger
 from style_bert_vits2.models import commons
@@ -16,6 +16,7 @@ from style_bert_vits2.models.utils import load_filepaths_and_text, load_wav_to_t
 from style_bert_vits2.nlp import cleaned_text_to_sequence
 
 
+config = get_config()
 """Multi speaker version"""
 
 
@@ -120,9 +121,7 @@ class TextAudioSpeakerLoader(torch.utils.data.Dataset):
         audio, sampling_rate = load_wav_to_torch(filename)
         if sampling_rate != self.sampling_rate:
             raise ValueError(
-                "{} {} SR doesn't match target {} SR".format(
+                f"{filename} {sampling_rate} SR doesn't match target {self.sampling_rate} SR"
-                    filename, sampling_rate, self.sampling_rate
-                )
             )
         audio_norm = audio / self.max_wav_value
         audio_norm = audio_norm.unsqueeze(0)

default_style.py

@@ -33,7 +33,7 @@ def save_neutral_vector(wav_dir: Union[Path, str], output_path: Union[Path, str]
     np.save(output_path, only_mean)
     logger.info(f"Saved mean style vector to {output_path}")
 
-    with open(json_path, "r", encoding="utf-8") as f:
+    with open(json_path, encoding="utf-8") as f:
         json_dict = json.load(f)
     json_dict["data"]["num_styles"] = 1
     json_dict["data"]["style2id"] = {DEFAULT_STYLE: 0}
@@ -50,7 +50,7 @@ def save_styles_by_dirs(wav_dir: Union[Path, str], output_dir: Union[Path, str])
 
     subdirs = [d for d in wav_dir.iterdir() if d.is_dir()]
     subdirs.sort()
-    if len(subdirs) in (0, 1):
+    if not subdirs:
         logger.warning("No style directories found. Saving only neutral style.")
         save_neutral_vector(wav_dir, output_dir)
 
@@ -85,7 +85,7 @@ def save_styles_by_dirs(wav_dir: Union[Path, str], output_dir: Union[Path, str])
 
     # Save style2id config to json
     style2id = {name: i for i, name in enumerate(names)}
-    with open(json_path, "r", encoding="utf-8") as f:
+    with open(json_path, encoding="utf-8") as f:
         json_dict = json.load(f)
     json_dict["data"]["num_styles"] = len(names)
     json_dict["data"]["style2id"] = style2id

gen_yaml.py

@@ -22,7 +22,7 @@ args = parser.parse_args()
 def gen_yaml(model_name, dataset_path):
     if not os.path.exists("config.yml"):
         shutil.copy(src="default_config.yml", dst="config.yml")
-    with open("config.yml", "r", encoding="utf-8") as f:
+    with open("config.yml", encoding="utf-8") as f:
         yml_data = yaml.safe_load(f)
     yml_data["model_name"] = model_name
     yml_data["dataset_path"] = dataset_path

gradio_tabs/merge.py

@@ -47,9 +47,9 @@ def merge_style(
     style_vectors_b = np.load(
         assets_root / model_name_b / "style_vectors.npy"
     )  # (style_num_b, 256)
-    with open(assets_root / model_name_a / "config.json", "r", encoding="utf-8") as f:
+    with open(assets_root / model_name_a / "config.json", encoding="utf-8") as f:
         config_a = json.load(f)
-    with open(assets_root / model_name_b / "config.json", "r", encoding="utf-8") as f:
+    with open(assets_root / model_name_b / "config.json", encoding="utf-8") as f:
         config_b = json.load(f)
     style2id_a = config_a["data"]["style2id"]
     style2id_b = config_b["data"]["style2id"]
@@ -83,7 +83,7 @@ def merge_style(
     # recipe.jsonを読み込んで、style_triple_listを追記
     info_path = assets_root / output_name / "recipe.json"
     if info_path.exists():
-        with open(info_path, "r", encoding="utf-8") as f:
+        with open(info_path, encoding="utf-8") as f:
             info = json.load(f)
     else:
         info = {}
@@ -143,7 +143,7 @@ def merge_models(
 
     merged_model_weight = model_a_weight.copy()
 
-    for key in model_a_weight.keys():
+    for key in model_a_weight:
         if any([key.startswith(prefix) for prefix in voice_keys]):
             weight = voice_weight
         elif any([key.startswith(prefix) for prefix in voice_pitch_keys]):
@@ -256,12 +256,12 @@ def update_two_model_names_dropdown(model_holder: TTSModelHolder):
 
 def load_styles_gr(model_name_a: str, model_name_b: str):
     config_path_a = assets_root / model_name_a / "config.json"
-    with open(config_path_a, "r", encoding="utf-8") as f:
+    with open(config_path_a, encoding="utf-8") as f:
         config_a = json.load(f)
     styles_a = list(config_a["data"]["style2id"].keys())
 
     config_path_b = assets_root / model_name_b / "config.json"
-    with open(config_path_b, "r", encoding="utf-8") as f:
+    with open(config_path_b, encoding="utf-8") as f:
         config_b = json.load(f)
     styles_b = list(config_b["data"]["style2id"].keys())
 

gradio_tabs/train.py

@@ -5,13 +5,14 @@ import subprocess
 import sys
 import time
 import webbrowser
+from dataclasses import dataclass
 from datetime import datetime
 from multiprocessing import cpu_count
 from pathlib import Path
 
 import gradio as gr
 import yaml
-from dataclasses import dataclass
+
 from config import get_path_config
 from style_bert_vits2.logging import logger
 from style_bert_vits2.utils.stdout_wrapper import SAFE_STDOUT
@@ -75,7 +76,7 @@ def initialize(
         "configs/config.json" if not use_jp_extra else "configs/config_jp_extra.json"
     )
 
-    with open(default_config_path, "r", encoding="utf-8") as f:
+    with open(default_config_path, encoding="utf-8") as f:
         config = json.load(f)
     config["model_name"] = model_name
     config["data"]["training_files"] = str(paths.train_path)
@@ -121,7 +122,7 @@ def initialize(
         json.dump(config, f, indent=2, ensure_ascii=False)
     if not Path("config.yml").exists():
         shutil.copy(src="default_config.yml", dst="config.yml")
-    with open("config.yml", "r", encoding="utf-8") as f:
+    with open("config.yml", encoding="utf-8") as f:
         yml_data = yaml.safe_load(f)
     yml_data["model_name"] = model_name
     yml_data["dataset_path"] = str(paths.dataset_path)
@@ -331,7 +332,7 @@ def train(
 ):
     paths = get_path(model_name)
     # 学習再開の場合を考えて念のためconfig.ymlの名前等を更新
-    with open("config.yml", "r", encoding="utf-8") as f:
+    with open("config.yml", encoding="utf-8") as f:
         yml_data = yaml.safe_load(f)
     yml_data["model_name"] = model_name
     yml_data["dataset_path"] = str(paths.dataset_path)

initialize.py

@@ -10,7 +10,7 @@ from style_bert_vits2.logging import logger
 
 
 def download_bert_models():
-    with open("bert/bert_models.json", "r", encoding="utf-8") as fp:
+    with open("bert/bert_models.json", encoding="utf-8") as fp:
         models = json.load(fp)
     for k, v in models.items():
         local_path = Path("bert").joinpath(k)
@@ -113,7 +113,7 @@ def main():
         return
 
     # Change default paths if necessary
-    with open(paths_yml, "r", encoding="utf-8") as f:
+    with open(paths_yml, encoding="utf-8") as f:
         yml_data = yaml.safe_load(f)
     if args.assets_root is not None:
         yml_data["assets_root"] = args.assets_root

preprocess_text.py

@@ -145,7 +145,7 @@ def preprocess(
             spk_utt_map[spk].append(line)
 
             # 新しい話者が出てきたら話者IDを割り当て、current_sidを1増やす
-            if spk not in spk_id_map.keys():
+            if spk not in spk_id_map:
                 spk_id_map[spk] = current_sid
                 current_sid += 1
         if count_same > 0 or count_not_found > 0:

pyproject.toml

@@ -5,7 +5,7 @@ build-backend = "hatchling.build"
 [project]
 name = "style-bert-vits2"
 dynamic = ["version"]
-description = 'Style-Bert-VITS2: Bert-VITS2 with more controllable voice styles.'
+description = "Style-Bert-VITS2: Bert-VITS2 with more controllable voice styles."
 readme = "README.md"
 requires-python = ">=3.9"
 license = "AGPL-3.0"
@@ -22,21 +22,21 @@ classifiers = [
     "Programming Language :: Python :: Implementation :: CPython",
 ]
 dependencies = [
-    'cmudict',
+    "cmudict",
-    'cn2an',
+    "cn2an",
-    'g2p_en',
+    "g2p_en",
-    'jieba',
+    "jieba",
-    'loguru',
+    "loguru",
-    'num2words',
+    "num2words",
-    'numba',
+    "numba",
-    'numpy',
+    "numpy",
-    'pydantic>=2.0',
+    "pydantic>=2.0",
-    'pyopenjtalk-dict',
+    "pyopenjtalk-dict",
-    'pypinyin',
+    "pypinyin",
-    'pyworld-prebuilt',
+    "pyworld-prebuilt",
-    'safetensors',
+    "safetensors",
-    'torch>=2.1',
+    "torch>=2.1",
-    'transformers',
+    "transformers",
 ]
 
 [project.urls]
@@ -59,42 +59,26 @@ only-include = [
     "pyproject.toml",
     "README.md",
 ]
-exclude = [
+exclude = [".git", ".gitignore", ".gitattributes"]
-    ".git",
-    ".gitignore",
-    ".gitattributes",
-]
 
 [tool.hatch.build.targets.wheel]
 packages = ["style_bert_vits2"]
 
 [tool.hatch.envs.test]
-dependencies = [
+dependencies = ["coverage[toml]>=6.5", "pytest"]
-    "coverage[toml]>=6.5",
-    "pytest",
-]
 [tool.hatch.envs.test.scripts]
 # Usage: `hatch run test:test`
 test = "pytest {args:tests}"
 # Usage: `hatch run test:coverage`
 test-cov = "coverage run -m pytest {args:tests}"
 # Usage: `hatch run test:cov-report`
-cov-report = [
+cov-report = ["- coverage combine", "coverage report"]
-    "- coverage combine",
-    "coverage report",
-]
 # Usage: `hatch run test:cov`
-cov = [
+cov = ["test-cov", "cov-report"]
-    "test-cov",
-    "cov-report",
-]
 
 [tool.hatch.envs.style]
 detached = true
-dependencies = [
+dependencies = ["black", "isort"]
-    "black",
-    "isort",
-]
 [tool.hatch.envs.style.scripts]
 check = [
     "black --check --diff .",
@@ -113,17 +97,17 @@ python = ["3.9", "3.10", "3.11"]
 source_pkgs = ["style_bert_vits2", "tests"]
 branch = true
 parallel = true
-omit = [
+omit = ["style_bert_vits2/constants.py"]
-    "style_bert_vits2/constants.py",
-]
 
 [tool.coverage.paths]
 style_bert_vits2 = ["style_bert_vits2", "*/style-bert-vits2/style_bert_vits2"]
 tests = ["tests", "*/style-bert-vits2/tests"]
 
 [tool.coverage.report]
-exclude_lines = [
+exclude_lines = ["no cov", "if __name__ == .__main__.:", "if TYPE_CHECKING:"]
-    "no cov",
+
-    "if __name__ == .__main__.:",
+[tool.ruff]
-    "if TYPE_CHECKING:",
+extend-select = ["I"]
-]
+
+[tool.ruff.lint.isort]
+lines-after-imports = 2

server_editor.py

@@ -127,7 +127,7 @@ def download_and_extract(url, extract_to: Path):
 
 def new_release_available(latest_release):
     if LAST_DOWNLOAD_FILE.exists():
-        with open(LAST_DOWNLOAD_FILE, "r") as file:
+        with open(LAST_DOWNLOAD_FILE) as file:
             last_download_str = file.read().strip()
             # 'Z'を除去して日時オブジェクトに変換
             last_download_str = last_download_str.replace("Z", "+00:00")

slice.py

@@ -7,7 +7,6 @@ from typing import Any, Optional
 
 import soundfile as sf
 import torch
-import yaml
 from tqdm import tqdm
 
 from config import get_path_config

style_bert_vits2/models/hyper_parameters.py

@@ -125,5 +125,5 @@ class HyperParameters(BaseModel):
             HyperParameters: ハイパーパラメータ
         """
 
-        with open(json_path, "r", encoding="utf-8") as f:
+        with open(json_path, encoding="utf-8") as f:
             return HyperParameters.model_validate_json(f.read())

style_bert_vits2/models/models.py

@@ -786,7 +786,7 @@ class ReferenceEncoder(nn.Module):
             for i in range(K)
         ]
         self.convs = nn.ModuleList(convs)
-        # self.wns = nn.ModuleList([weight_norm(num_features=ref_enc_filters[i]) for i in range(K)]) # noqa: E501
+        # self.wns = nn.ModuleList([weight_norm(num_features=ref_enc_filters[i]) for i in range(K)])
 
         out_channels = self.calculate_channels(spec_channels, 3, 2, 1, K)
         self.gru = nn.GRU(

style_bert_vits2/models/models_jp_extra.py

@@ -844,7 +844,7 @@ class ReferenceEncoder(nn.Module):
             for i in range(K)
         ]
         self.convs = nn.ModuleList(convs)
-        # self.wns = nn.ModuleList([weight_norm(num_features=ref_enc_filters[i]) for i in range(K)]) # noqa: E501
+        # self.wns = nn.ModuleList([weight_norm(num_features=ref_enc_filters[i]) for i in range(K)])
 
         out_channels = self.calculate_channels(spec_channels, 3, 2, 1, K)
         self.gru = nn.GRU(

style_bert_vits2/models/utils/__init__.py

@@ -186,7 +186,7 @@ def load_filepaths_and_text(
         list[list[str]]: ファイルパスとテキストのリスト
     """
 
-    with open(filename, "r", encoding="utf-8") as f:
+    with open(filename, encoding="utf-8") as f:
         filepaths_and_text = [line.strip().split(split) for line in f]
     return filepaths_and_text
 
@@ -245,9 +245,7 @@ def check_git_hash(model_dir_path: Union[str, Path]) -> None:
     source_dir = os.path.dirname(os.path.realpath(__file__))
     if not os.path.exists(os.path.join(source_dir, ".git")):
         logger.warning(
-            "{} is not a git repository, therefore hash value comparison will be ignored.".format(
+            f"{source_dir} is not a git repository, therefore hash value comparison will be ignored."
-                source_dir
-            )
         )
         return
 
@@ -255,13 +253,11 @@ def check_git_hash(model_dir_path: Union[str, Path]) -> None:
 
     path = os.path.join(model_dir_path, "githash")
     if os.path.exists(path):
-        with open(path, "r", encoding="utf-8") as f:
+        with open(path, encoding="utf-8") as f:
             saved_hash = f.read()
         if saved_hash != cur_hash:
             logger.warning(
-                "git hash values are different. {}(saved) != {}(current)".format(
+                f"git hash values are different. {saved_hash[:8]}(saved) != {cur_hash[:8]}(current)"
-                    saved_hash[:8], cur_hash[:8]
-                )
             )
     else:
         with open(path, "w", encoding="utf-8") as f:

style_bert_vits2/models/utils/safetensors.py

@@ -77,7 +77,7 @@ def save_safetensors(
     keys = []
     for k in state_dict:
         if "enc_q" in k and for_infer:
-            continue  # noqa: E701
+            continue
         keys.append(k)
 
     new_dict = (

style_bert_vits2/nlp/chinese/g2p.py

@@ -8,7 +8,7 @@ from style_bert_vits2.nlp.chinese.tone_sandhi import ToneSandhi
 from style_bert_vits2.nlp.symbols import PUNCTUATIONS
 
 
-with open(Path(__file__).parent / "opencpop-strict.txt", "r", encoding="utf-8") as f:
+with open(Path(__file__).parent / "opencpop-strict.txt", encoding="utf-8") as f:
     __PINYIN_TO_SYMBOL_MAP = {
         line.split("\t")[0]: line.strip().split("\t")[1] for line in f.readlines()
     }
@@ -73,7 +73,7 @@ def __g2p(segments: list[str]) -> tuple[list[str], list[int], list[int]]:
                         "iou": "iu",
                         "uen": "un",
                     }
-                    if v_without_tone in v_rep_map.keys():
+                    if v_without_tone in v_rep_map:
                         pinyin = c + v_rep_map[v_without_tone]
                 else:
                     # 单音节
@@ -83,7 +83,7 @@ def __g2p(segments: list[str]) -> tuple[list[str], list[int], list[int]]:
                         "in": "yin",
                         "u": "wu",
                     }
-                    if pinyin in pinyin_rep_map.keys():
+                    if pinyin in pinyin_rep_map:
                         pinyin = pinyin_rep_map[pinyin]
                     else:
                         single_rep_map = {
@@ -92,10 +92,10 @@ def __g2p(segments: list[str]) -> tuple[list[str], list[int], list[int]]:
                             "i": "y",
                             "u": "w",
                         }
-                        if pinyin[0] in single_rep_map.keys():
+                        if pinyin[0] in single_rep_map:
                             pinyin = single_rep_map[pinyin[0]] + pinyin[1:]
 
-                assert pinyin in __PINYIN_TO_SYMBOL_MAP.keys(), (
+                assert pinyin in __PINYIN_TO_SYMBOL_MAP, (
                     pinyin,
                     seg,
                     raw_pinyin,

style_bert_vits2/nlp/chinese/normalizer.py

@@ -51,7 +51,7 @@ def normalize_text(text: str) -> str:
 def replace_punctuation(text: str) -> str:
 
     text = text.replace("嗯", "恩").replace("呣", "母")
-    pattern = re.compile("|".join(re.escape(p) for p in __REPLACE_MAP.keys()))
+    pattern = re.compile("|".join(re.escape(p) for p in __REPLACE_MAP))
 
     replaced_text = pattern.sub(lambda x: __REPLACE_MAP[x.group()], text)
 

style_bert_vits2/nlp/chinese/tone_sandhi.py

@@ -471,26 +471,27 @@ class ToneSandhi:
             ):
                 finals[j] = finals[j][:-1] + "5"
         ge_idx = word.find("个")
-        if len(word) >= 1 and word[-1] in "吧呢啊呐噻嘛吖嗨呐哦哒额滴哩哟喽啰耶喔诶":
+        if (
-            finals[-1] = finals[-1][:-1] + "5"
+            len(word) >= 1
-        elif len(word) >= 1 and word[-1] in "的地得":
+            and word[-1] in "吧呢啊呐噻嘛吖嗨呐哦哒额滴哩哟喽啰耶喔诶"
-            finals[-1] = finals[-1][:-1] + "5"
+            or len(word) >= 1
-        # e.g. 走了, 看着, 去过
+            and word[-1] in "的地得"
-        # elif len(word) == 1 and word in "了着过" and pos in {"ul", "uz", "ug"}:
+            or (
-        #     finals[-1] = finals[-1][:-1] + "5"
+                (
-        elif (
+                    len(word) > 1
-            len(word) > 1
+                    and word[-1] in "们子"
-            and word[-1] in "们子"
+                    and pos in {"r", "n"}
-            and pos in {"r", "n"}
+                    and word not in self.must_not_neural_tone_words
-            and word not in self.must_not_neural_tone_words
+                )
+                or len(word) > 1
+                and word[-1] in "上下里"
+                and pos in {"s", "l", "f"}
+            )
+            or len(word) > 1
+            and word[-1] in "来去"
+            and word[-2] in "上下进出回过起开"
         ):
             finals[-1] = finals[-1][:-1] + "5"
-        # e.g. 桌上, 地下, 家里
-        elif len(word) > 1 and word[-1] in "上下里" and pos in {"s", "l", "f"}:
-            finals[-1] = finals[-1][:-1] + "5"
-        # e.g. 上来, 下去
-        elif len(word) > 1 and word[-1] in "来去" and word[-2] in "上下进出回过起开":
-            finals[-1] = finals[-1][:-1] + "5"
         # 个做量词
         elif (
             ge_idx >= 1
@@ -500,12 +501,11 @@ class ToneSandhi:
             )
         ) or word == "个":
             finals[ge_idx] = finals[ge_idx][:-1] + "5"
-        else:
+        elif (
-            if (
+            word in self.must_neural_tone_words
-                word in self.must_neural_tone_words
+            or word[-2:] in self.must_neural_tone_words
-                or word[-2:] in self.must_neural_tone_words
+        ):
-            ):
+            finals[-1] = finals[-1][:-1] + "5"
-                finals[-1] = finals[-1][:-1] + "5"
 
         word_list = self._split_word(word)
         finals_list = [finals[: len(word_list[0])], finals[len(word_list[0]) :]]
@@ -549,10 +549,8 @@ class ToneSandhi:
                     if finals[i + 1][-1] == "4":
                         finals[i] = finals[i][:-1] + "2"
                     # "一" before non-tone4 should be yi4, e.g. 一天
-                    else:
+                    elif word[i + 1] not in self.punc:
-                        # "一" 后面如果是标点，还读一声
+                        finals[i] = finals[i][:-1] + "4"
-                        if word[i + 1] not in self.punc:
-                            finals[i] = finals[i][:-1] + "4"
         return finals
 
     def _split_word(self, word: str) -> list[str]:

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, "r", encoding="utf-8") as f:
+    with open(CMU_DICT_PATH, encoding="utf-8") as f:
         line = f.readline()
         line_index = 1
         while line:

style_bert_vits2/nlp/english/g2p.py

@@ -1,23 +1,91 @@
 import re
+
 from g2p_en import G2p
+
 from style_bert_vits2.constants import Languages
 from style_bert_vits2.nlp import bert_models
 from style_bert_vits2.nlp.english.cmudict import get_dict
 from style_bert_vits2.nlp.symbols import PUNCTUATIONS, SYMBOLS
 
+
 # Initialize global variables once
 ARPA = {
-    "AH0", "S", "AH1", "EY2", "AE2", "EH0", "OW2", "UH0", "NG", "B", "G", "AY0",
+    "AH0",
-    "M", "AA0", "F", "AO0", "ER2", "UH1", "IY1", "AH2", "DH", "IY0", "EY1",
+    "S",
-    "IH0", "K", "N", "W", "IY2", "T", "AA1", "ER1", "EH2", "OY0", "UH2", "UW1",
+    "AH1",
-    "Z", "AW2", "AW1", "V", "UW2", "AA2", "ER", "AW0", "UW0", "R", "OW1", "EH1",
+    "EY2",
-    "ZH", "AE0", "IH2", "IH", "Y", "JH", "P", "AY1", "EY0", "OY2", "TH", "HH",
+    "AE2",
-    "D", "ER0", "CH", "AO1", "AE1", "AO2", "OY1", "AY2", "IH1", "OW0", "L",
+    "EH0",
-    "SH"
+    "OW2",
+    "UH0",
+    "NG",
+    "B",
+    "G",
+    "AY0",
+    "M",
+    "AA0",
+    "F",
+    "AO0",
+    "ER2",
+    "UH1",
+    "IY1",
+    "AH2",
+    "DH",
+    "IY0",
+    "EY1",
+    "IH0",
+    "K",
+    "N",
+    "W",
+    "IY2",
+    "T",
+    "AA1",
+    "ER1",
+    "EH2",
+    "OY0",
+    "UH2",
+    "UW1",
+    "Z",
+    "AW2",
+    "AW1",
+    "V",
+    "UW2",
+    "AA2",
+    "ER",
+    "AW0",
+    "UW0",
+    "R",
+    "OW1",
+    "EH1",
+    "ZH",
+    "AE0",
+    "IH2",
+    "IH",
+    "Y",
+    "JH",
+    "P",
+    "AY1",
+    "EY0",
+    "OY2",
+    "TH",
+    "HH",
+    "D",
+    "ER0",
+    "CH",
+    "AO1",
+    "AE1",
+    "AO2",
+    "OY1",
+    "AY2",
+    "IH1",
+    "OW0",
+    "L",
+    "SH",
 }
 _g2p = G2p()
 eng_dict = get_dict()
 
+
 def g2p(text: str) -> tuple[list[str], list[int], list[int]]:
     phones = []
     tones = []
@@ -72,9 +140,19 @@ def g2p(text: str) -> tuple[list[str], list[int], list[int]]:
 
 def __post_replace_ph(ph: str) -> str:
     REPLACE_MAP = {
-        "：": ",", "；": ",", "，": ",", "。": ".", "！": "!", "？": "?",
+        "：": ",",
-        "\n": ".", "·": ",", "、": ",", "…": "...", "···": "...",
+        "；": ",",
-        "・・・": "...", "v": "V"
+        "，": ",",
+        "。": ".",
+        "！": "!",
+        "？": "?",
+        "\n": ".",
+        "·": ",",
+        "、": ",",
+        "…": "...",
+        "···": "...",
+        "・・・": "...",
+        "v": "V",
     }
     if ph in REPLACE_MAP:
         ph = REPLACE_MAP[ph]
@@ -120,21 +198,22 @@ def __text_to_words(text: str) -> list[list[str]]:
     for idx, t in enumerate(tokens):
         if t.startswith("▁"):
             words.append([t[1:]])
-        else:
+        elif t in PUNCTUATIONS:
-            if t in PUNCTUATIONS:
+            if idx == len(tokens) - 1:
-                if idx == len(tokens) - 1:
+                words.append([f"{t}"])
-                    words.append([f"{t}"])
+            elif (
-                else:
+                not tokens[idx + 1].startswith("▁")
-                    if not tokens[idx + 1].startswith("▁") and tokens[idx + 1] not in PUNCTUATIONS:
+                and tokens[idx + 1] not in PUNCTUATIONS
-                        if idx == 0:
+            ):
-                            words.append([])
-                        words[-1].append(f"{t}")
-                    else:
-                        words.append([f"{t}"])
-            else:
                 if idx == 0:
                     words.append([])
                 words[-1].append(f"{t}")
+            else:
+                words.append([f"{t}"])
+        else:
+            if idx == 0:
+                words.append([])
+            words[-1].append(f"{t}")
     return words
 
 
@@ -149,4 +228,3 @@ if __name__ == "__main__":
     #         for ph in group:
     #             all_phones.add(ph)
     # print(all_phones)
-

style_bert_vits2/nlp/english/normalizer.py

@@ -58,7 +58,7 @@ def replace_punctuation(text: str) -> str:
         "「": "'",
         "」": "'",
     }
-    pattern = re.compile("|".join(re.escape(p) for p in REPLACE_MAP.keys()))
+    pattern = re.compile("|".join(re.escape(p) for p in REPLACE_MAP))
     replaced_text = pattern.sub(lambda x: REPLACE_MAP[x.group()], text)
     # replaced_text = re.sub(
     #     r"[^\u3040-\u309F\u30A0-\u30FF\u4E00-\u9FFF\u3400-\u4DBF\u3005"

style_bert_vits2/nlp/japanese/g2p.py

@@ -719,5 +719,3 @@ class YomiError(Exception):
     基本的に「学習の前処理のテキスト処理時」には発生させ、そうでない場合は、
     ignore_yomi_error=True にしておいて、この例外を発生させないようにする。
     """
-
-    pass

style_bert_vits2/nlp/japanese/normalizer.py

@@ -60,7 +60,7 @@ __REPLACE_MAP = {
     "」": "'",
 }
 # 記号類の正規化パターン
-__REPLACE_PATTERN = re.compile("|".join(re.escape(p) for p in __REPLACE_MAP.keys()))
+__REPLACE_PATTERN = re.compile("|".join(re.escape(p) for p in __REPLACE_MAP))
 # 句読点等の正規化パターン
 __PUNCTUATION_CLEANUP_PATTERN = re.compile(
     # ↓ ひらがな、カタカナ、漢字

style_bert_vits2/nlp/japanese/pyopenjtalk_worker/__init__.py

@@ -88,7 +88,7 @@ def initialize_worker(port: int = WORKER_PORT) -> None:
     client = None
     try:
         client = WorkerClient(port)
-    except (socket.timeout, socket.error):
+    except (OSError, socket.timeout):
         logger.debug("try starting pyopenjtalk worker server")
         import os
         import subprocess
@@ -120,7 +120,7 @@ def initialize_worker(port: int = WORKER_PORT) -> None:
             try:
                 client = WorkerClient(port)
                 break
-            except socket.error:
+            except OSError:
                 time.sleep(0.5)
                 count += 1
                 # 20: max number of retries

style_bert_vits2/nlp/japanese/user_dict/word_model.py

@@ -114,7 +114,7 @@ class PartOfSpeechDetail(BaseModel):
     part_of_speech_detail_2: str = Field(title="品詞細分類2")
     part_of_speech_detail_3: str = Field(title="品詞細分類3")
     # context_idは辞書の左・右文脈IDのこと
-    # https://github.com/VOICEVOX/open_jtalk/blob/427cfd761b78efb6094bea3c5bb8c968f0d711ab/src/mecab-naist-jdic/_left-id.def # noqa
+    # https://github.com/VOICEVOX/open_jtalk/blob/427cfd761b78efb6094bea3c5bb8c968f0d711ab/src/mecab-naist-jdic/_left-id.def
     context_id: int = Field(title="文脈ID")
     cost_candidates: List[int] = Field(title="コストのパーセンタイル")
     accent_associative_rules: List[str] = Field(title="アクセント結合規則の一覧")

style_bert_vits2/tts_model.py

@@ -1,5 +1,5 @@
 from pathlib import Path
-from typing import TYPE_CHECKING, Any, Optional, Union
+from typing import Any, Optional, Union
 
 import numpy as np
 import torch

style_bert_vits2/utils/subprocess.py

@@ -27,6 +27,7 @@ def run_script_with_log(
         stderr=subprocess.PIPE,
         text=True,
         encoding="utf-8",
+        check=False,
     )
     if result.returncode != 0:
         logger.error(f"Error: {' '.join(cmd)}\n{result.stderr}")

style_gen.py

@@ -26,7 +26,6 @@ class NaNValueError(ValueError):
     """カスタム例外クラス。NaN値が見つかった場合に使用されます。"""
 
 
-
 # 推論時にインポートするために短いが関数を書く
 def get_style_vector(wav_path: str) -> NDArray[Any]:
     return inference(wav_path)  # type: ignore

train_ms_jp_extra.py

@@ -17,11 +17,7 @@ from tqdm import tqdm
 # logging.getLogger("numba").setLevel(logging.WARNING)
 import default_style
 from config import get_config
-from data_utils import (
+from data_utils import TextAudioSpeakerCollate, TextAudioSpeakerLoader
-    DistributedBucketSampler,
-    TextAudioSpeakerCollate,
-    TextAudioSpeakerLoader,
-)
 from losses import WavLMLoss, discriminator_loss, feature_loss, generator_loss, kl_loss
 from mel_processing import mel_spectrogram_torch, spec_to_mel_torch
 from style_bert_vits2.logging import logger

transcribe.py

@@ -1,10 +1,8 @@
 import argparse
-import os
 import sys
 from pathlib import Path
 from typing import Any, Optional
 
-import yaml
 from torch.utils.data import Dataset
 from tqdm import tqdm