Fix: CUDAExecutionProvider was not being used to infer Style-Bert-VITS2 ONNX models even though CUDA was available

gradio_tabs/inference.py

@@ -18,11 +18,12 @@ from style_bert_vits2.constants import (
     Languages,
 )
 from style_bert_vits2.logging import logger
-from style_bert_vits2.models.infer import InvalidToneError
+from style_bert_vits2.nlp import InvalidToneError
 from style_bert_vits2.nlp.japanese import pyopenjtalk_worker as pyopenjtalk
 from style_bert_vits2.nlp.japanese.g2p_utils import g2kata_tone, kata_tone2phone_tone
 from style_bert_vits2.nlp.japanese.normalizer import normalize_text
 from style_bert_vits2.tts_model import TTSModelHolder
+from style_bert_vits2.utils import torch_device_to_onnx_providers
 
 
 # pyopenjtalk_worker を起動
@@ -533,6 +534,8 @@ if __name__ == "__main__":
     path_config = get_path_config()
     assets_root = path_config.assets_root
     device = "cuda" if torch.cuda.is_available() else "cpu"
-    model_holder = TTSModelHolder(assets_root, device)
+    model_holder = TTSModelHolder(
+        assets_root, device, torch_device_to_onnx_providers(device)
+    )
     app = create_inference_app(model_holder)
     app.launch(inbrowser=True)

gradio_tabs/merge.py

@@ -12,6 +12,7 @@ from config import get_path_config
 from style_bert_vits2.constants import DEFAULT_STYLE, GRADIO_THEME
 from style_bert_vits2.logging import logger
 from style_bert_vits2.tts_model import TTSModel, TTSModelHolder
+from style_bert_vits2.utils import torch_device_to_onnx_providers
 
 
 voice_keys = ["dec"]
@@ -1524,8 +1525,9 @@ def create_merge_app(model_holder: TTSModelHolder) -> gr.Blocks:
 
 
 if __name__ == "__main__":
+    device = "cuda" if torch.cuda.is_available() else "cpu"
     model_holder = TTSModelHolder(
-        assets_root, device="cuda" if torch.cuda.is_available() else "cpu"
+        assets_root, device, torch_device_to_onnx_providers(device)
     )
     app = create_merge_app(model_holder)
     app.launch(inbrowser=True)