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hubert

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wataru 2023-03-30 00:22:37 +09:00
parent f0fbf58258
commit e10c832b46
1 changed files with 6 additions and 1 deletions
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7
server/voice_changer/SoVitsSvc40/SoVitsSvc40.py
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@ -83,7 +83,7 @@ class SoVitsSvc40:
ort_options.intra_op_num_threads = 8 ort_options.intra_op_num_threads = 8
self.hubert_onnx = onnxruntime.InferenceSession( self.hubert_onnx = onnxruntime.InferenceSession(
"model_hubert/hubert_simple.onnx", "model_hubert/hubert_simple.onnx",
providers=['TensorrtExecutionProvider', 'CUDAExecutionProvider', 'CPUExecutionProvider'] providers=providers
) )
else: else:
models, saved_cfg, task = checkpoint_utils.load_model_ensemble_and_task( models, saved_cfg, task = checkpoint_utils.load_model_ensemble_and_task(
@ -143,8 +143,12 @@ class SoVitsSvc40:
self.settings.gpu = 0 self.settings.gpu = 0
provider_options = [{'device_id': self.settings.gpu}] provider_options = [{'device_id': self.settings.gpu}]
self.onnx_session.set_providers(providers=[val], provider_options=provider_options) self.onnx_session.set_providers(providers=[val], provider_options=provider_options)
if hasattr(self, "hubert_onnx"):
self.hubert_onnx.set_providers(providers=[val], provider_options=provider_options)
else: else:
self.onnx_session.set_providers(providers=[val]) self.onnx_session.set_providers(providers=[val])
if hasattr(self, "hubert_onnx"):
self.hubert_onnx.set_providers(providers=[val])
elif key == "onnxExecutionProvider" and self.onnx_session == None: elif key == "onnxExecutionProvider" and self.onnx_session == None:
print("Onnx is not enabled. Please load model.") print("Onnx is not enabled. Please load model.")
return False return False
@ -217,6 +221,7 @@ class SoVitsSvc40:
"audio": wav16k_numpy.reshape(1, -1), "audio": wav16k_numpy.reshape(1, -1),
}) })
c = torch.from_numpy(np.array(c)).squeeze(0).transpose(1, 2) c = torch.from_numpy(np.array(c)).squeeze(0).transpose(1, 2)
# print("onnx hubert:", self.hubert_onnx.get_providers())
else: else:
self.hubert_model = self.hubert_model.to(dev) self.hubert_model = self.hubert_model.to(dev)
wav16k_tensor = wav16k_tensor.to(dev) wav16k_tensor = wav16k_tensor.to(dev)