Refactor: remove dependencies on libraries not required for style_bert_vits2 as a library

librosa: Originally not used under style_bert_vits2/.
pyannote.audio: Required only when using the "infer style vector from audio" function during inference, but it is currently almost unused.
scipy: Because it was used in only one utility function that was not needed outside of training.

pyproject.toml

@@ -26,18 +26,15 @@ dependencies = [
     'cn2an',
     'g2p_en',
     'jieba',
-    'librosa==0.9.2',
     'loguru',
     'num2words',
     'numba',
     'numpy',
-    'pyannote.audio>=3.1.0',
     'pydantic>=2.0',
     'pyopenjtalk-dict',
     'pypinyin',
     'pyworld-prebuilt',
     'safetensors',
-    'scipy',
     'torch>=2.1',
     'transformers',
 ]

style_bert_vits2/models/utils/__init__.py

@@ -9,7 +9,6 @@ from typing import TYPE_CHECKING, Any, Optional, Union
 import numpy as np
 import torch
 from numpy.typing import NDArray
-from scipy.io.wavfile import read
 
 from style_bert_vits2.logging import logger
 from style_bert_vits2.models.utils import checkpoints  # type: ignore
@@ -162,6 +161,13 @@ def load_wav_to_torch(full_path: Union[str, Path]) -> tuple[torch.FloatTensor, i
         tuple[torch.FloatTensor, int]: 音声データのテンソルとサンプリングレート
     """
 
+    # この関数は学習時以外使われないため、ライブラリとしての style_bert_vits2 が
+    # 重たい scipy に依存しないように遅延 import する
+    try:
+        from scipy.io.wavfile import read
+    except ImportError:
+        raise ImportError("scipy is required to load wav file")
+
     sampling_rate, data = read(full_path)
     return torch.FloatTensor(data.astype(np.float32)), sampling_rate
 

style_bert_vits2/tts_model.py

@@ -2,7 +2,6 @@ from pathlib import Path
 from typing import TYPE_CHECKING, Any, Optional, Union
 
 import numpy as np
-import pyannote.audio
 import torch
 from numpy.typing import NDArray
 from pydantic import BaseModel
@@ -76,7 +75,7 @@ class TTSModel:
                 f"Number of styles ({num_styles}) does not match the number of style2id ({len(self.style2id)})"
             )
 
-        self.__style_vector_inference: Optional[pyannote.audio.Inference] = None
+        self.__style_vector_inference: Optional[Any] = None
         self.__style_vectors: NDArray[Any] = np.load(self.style_vec_path)
         if self.__style_vectors.shape[0] != num_styles:
             raise ValueError(
@@ -125,8 +124,18 @@ class TTSModel:
             NDArray[Any]: スタイルベクトル
         """
 
-        # スタイルベクトルを取得するための推論モデルを初期化
         if self.__style_vector_inference is None:
+
+            # pyannote.audio は scikit-learn などの大量の重量級ライブラリに依存しているため、
+            # TTSModel.infer() に reference_audio_path を指定し音声からスタイルベクトルを推論する場合のみ遅延 import する
+            try:
+                import pyannote.audio
+            except ImportError:
+                raise ImportError(
+                    "pyannote.audio is required to infer style vector from audio"
+                )
+
+            # スタイルベクトルを取得するための推論モデルを初期化
             self.__style_vector_inference = pyannote.audio.Inference(
                 model=pyannote.audio.Model.from_pretrained(
                     "pyannote/wespeaker-voxceleb-resnet34-LM"