hatch fmt

convert_bert_onnx.py

@@ -31,8 +31,8 @@ if __name__ == "__main__":
     # モデルの入出力先ファイルパスを取得
     language = Languages(args.language)
     pretrained_model_name_or_path = DEFAULT_BERT_MODEL_PATHS[language]
-    onnx_temp_model_path = Path(pretrained_model_name_or_path) / f"model_temp.onnx"
+    onnx_temp_model_path = Path(pretrained_model_name_or_path) / "model_temp.onnx"
-    onnx_optimized_model_path = Path(pretrained_model_name_or_path) / f"model.onnx"
+    onnx_optimized_model_path = Path(pretrained_model_name_or_path) / "model.onnx"
     tokenizer_json_path = Path(pretrained_model_name_or_path) / "tokenizer.json"
     print(Rule(characters="=", style=Style(color="blue")))
     print(f"[bold cyan]Language:[/bold cyan] {language.name}")
@@ -68,7 +68,7 @@ if __name__ == "__main__":
 
     # モデルを ONNX に変換
     print(Rule(characters="=", style=Style(color="blue")))
-    print(f"[bold cyan]Exporting ONNX model...[/bold cyan]")
+    print("[bold cyan]Exporting ONNX model...[/bold cyan]")
     print(Rule(characters="=", style=Style(color="blue")))
     export_start_time = time.time()
     torch.onnx.export(
@@ -98,7 +98,7 @@ if __name__ == "__main__":
 
     # ONNX モデルを最適化
     print(Rule(characters="=", style=Style(color="blue")))
-    print(f"[bold cyan]Optimizing ONNX model...[/bold cyan]")
+    print("[bold cyan]Optimizing ONNX model...[/bold cyan]")
     print(Rule(characters="=", style=Style(color="blue")))
     optimize_start_time = time.time()
     onnx_model = onnx.load(onnx_temp_model_path)

convert_onnx.py

@@ -1,5 +1,5 @@
-# Usage: .venv/bin/python convert_onnx.py --model model_assets/koharune-ami/koharune-ami.safetensors
+# Usage: python convert_onnx.py --model model_assets/koharune-ami/koharune-ami.safetensors
-# Usage: .venv/bin/python convert_onnx.py --model model_assets/ (All models in the directory will be converted)
+# Usage: python convert_onnx.py --model model_assets/ (All models in the directory will be converted)
 # ref: https://github.com/tuna2134/sbv2-api/blob/main/convert/convert_model.py
 
 import time
@@ -162,7 +162,7 @@ if __name__ == "__main__":
             # モデルを ONNX に変換
             print(Rule(characters="=", style=Style(color="blue")))
             print(
-                f"[bold cyan]Exporting ONNX model... (Architecture: JP-Extra)[/bold cyan]"
+                "[bold cyan]Exporting ONNX model... (Architecture: JP-Extra)[/bold cyan]"
             )
             print(Rule(characters="=", style=Style(color="blue")))
             export_start_time = time.time()
@@ -253,7 +253,7 @@ if __name__ == "__main__":
             # モデルを ONNX に変換
             print(Rule(characters="=", style=Style(color="blue")))
             print(
-                f"[bold cyan]Exporting ONNX model... (Architecture: Non-JP-Extra)[/bold cyan]"
+                "[bold cyan]Exporting ONNX model... (Architecture: Non-JP-Extra)[/bold cyan]"
             )
             print(Rule(characters="=", style=Style(color="blue")))
             export_start_time = time.time()
@@ -310,7 +310,7 @@ if __name__ == "__main__":
 
         # ONNX モデルを最適化
         print(Rule(characters="=", style=Style(color="blue")))
-        print(f"[bold cyan]Optimizing ONNX model...[/bold cyan]")
+        print("[bold cyan]Optimizing ONNX model...[/bold cyan]")
         print(Rule(characters="=", style=Style(color="blue")))
         optimize_start_time = time.time()
         onnx_model = onnx.load(onnx_temp_model_path)

gradio_tabs/merge.py

@@ -897,7 +897,7 @@ initial_md = """
 - 話者数が違うモデル同士はおそらくマージできません。
 """
 
-style_merge_md = f"""
+style_merge_md = """
 ## 3. スタイルベクトルのマージ
 
 1. マージ後のモデルにいくつスタイルを追加したいかを「作りたいスタイル数」で指定

preprocess_text.py

@@ -2,7 +2,7 @@ import argparse
 import json
 from collections import defaultdict
 from pathlib import Path
-from random import sample, shuffle
+from random import sample
 from typing import Optional
 
 from tqdm import tqdm

style_bert_vits2/models/infer_onnx.py

@@ -1,4 +1,5 @@
-from typing import Any, Optional, Sequence, Union
+from collections.abc import Sequence
+from typing import Any, Optional, Union
 
 import numpy as np
 import onnxruntime

style_bert_vits2/models/utils/__init__.py

@@ -11,8 +11,10 @@ import torch
 from numpy.typing import NDArray
 
 from style_bert_vits2.logging import logger
-from style_bert_vits2.models.utils import checkpoints  # type: ignore
+from style_bert_vits2.models.utils import (
-from style_bert_vits2.models.utils import safetensors  # type: ignore
+    checkpoints,  # type: ignore
+    safetensors,  # type: ignore
+)
 
 
 if TYPE_CHECKING:

style_bert_vits2/nlp/__init__.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
-from typing import TYPE_CHECKING, Any, Optional, Sequence, Union
+from collections.abc import Sequence
+from typing import TYPE_CHECKING, Any, Optional, Union
 
 from numpy.typing import NDArray
 

style_bert_vits2/nlp/bert_models.py

@@ -251,7 +251,6 @@ def unload_tokenizer(language: Languages) -> None:
         language (Languages): アンロードする BERT トークナイザーの言語
     """
 
-    import torch
 
     if language in __loaded_tokenizers:
         del __loaded_tokenizers[language]

style_bert_vits2/nlp/chinese/bert_feature.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
-from typing import TYPE_CHECKING, Any, Optional, Sequence, Union
+from collections.abc import Sequence
+from typing import TYPE_CHECKING, Any, Optional, Union
 
 import numpy as np
 from numpy.typing import NDArray

style_bert_vits2/nlp/english/bert_feature.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
-from typing import TYPE_CHECKING, Any, Optional, Sequence, Union
+from collections.abc import Sequence
+from typing import TYPE_CHECKING, Any, Optional, Union
 
 import numpy as np
 from numpy.typing import NDArray

style_bert_vits2/nlp/japanese/bert_feature.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
-from typing import TYPE_CHECKING, Any, Optional, Sequence, Union
+from collections.abc import Sequence
+from typing import TYPE_CHECKING, Any, Optional, Union
 
 import numpy as np
 from numpy.typing import NDArray

style_bert_vits2/nlp/onnx_bert_models.py

@@ -11,8 +11,9 @@ Style-Bert-VITS2 の ONNX 推論に必要な各言語ごとの ONNX 版 BERT モ
 
 import gc
 import time
+from collections.abc import Sequence
 from pathlib import Path
-from typing import Any, Optional, Sequence, Union
+from typing import Any, Optional, Union
 
 import onnxruntime
 from huggingface_hub import hf_hub_download

style_bert_vits2/tts_model.py

@@ -2,8 +2,9 @@ from __future__ import annotations
 
 import gc
 import time
+from collections.abc import Sequence
 from pathlib import Path
-from typing import TYPE_CHECKING, Any, Optional, Sequence, Union
+from typing import TYPE_CHECKING, Any, Optional, Union
 
 import numpy as np
 import onnxruntime

style_bert_vits2/utils/__init__.py

@@ -1,4 +1,5 @@
-from typing import Any, Sequence, Union
+from collections.abc import Sequence
+from typing import Any, Union
 
 
 def torch_device_to_onnx_providers(

tests/test_main.py

@@ -1,4 +1,5 @@
-from typing import Any, Literal, Sequence
+from collections.abc import Sequence
+from typing import Any, Literal
 
 import pytest
 from scipy.io import wavfile