reactor main argument

.gitignore

@@ -40,9 +40,6 @@ client/lib/worklet/dist
 
 docker/cudnn/
 
-server/hubert_base.pt
+server/weights/
-server/hubert-soft-0d54a1f4.pt
-server/nsf_hifigan/
-
 
 start_trainer.sh

server/Exceptions.py

@@ -5,3 +5,8 @@ class NoModeLoadedException(Exception):
 
     def __str__(self):
         return repr(f"No model for {self.framework} loaded. Please confirm the model uploaded.")
+
+
+class ONNXInputArgumentException(Exception):
+    def __str__(self):
+        return repr(f"ONNX received invalid argument.")

server/MMVCServerSIO.py

@@ -42,11 +42,18 @@ def setupArgParser():
     parser.add_argument("--cluster", type=str, help="path to cluster model")
     parser.add_argument("--internal", type=strtobool, default=False, help="各種パスをmac appの中身に変換")
 
-    parser.add_argument("--hubert", type=str, help="path to hubert model")
+    # parser.add_argument("--hubert", type=str, help="path to hubert model")
-    parser.add_argument("--useHubertOnnx", type=strtobool, default=False, help="use hubert onnx")
+    # parser.add_argument("--useHubertOnnx", type=strtobool, default=False, help="use hubert onnx")
-    parser.add_argument("--hubertSoftPt", type=str, help="path to hubert-soft model(pytorch)")
+    # parser.add_argument("--hubertSoftPt", type=str, help="path to hubert-soft model(pytorch)")
-    parser.add_argument("--enhancerPt", type=str, help="path to enhancer model(pytorch)")
+    # parser.add_argument("--enhancerPt", type=str, help="path to enhancer model(pytorch)")
-    parser.add_argument("--enhancerOnnx", type=str, help="path to enhancer model(onnx)")
+    # parser.add_argument("--enhancerOnnx", type=str, help="path to enhancer model(onnx)")
+
+    parser.add_argument("--content_vec_500", type=str, help="path to content_vec_500 model(pytorch)")
+    parser.add_argument("--content_vec_500_onnx", type=str, help="path to content_vec_500 model(onnx)")
+    parser.add_argument("--content_vec_500_onnx_on", type=strtobool, default=False, help="use or not onnx for  content_vec_500")
+    parser.add_argument("--hubert_base", type=str, help="path to hubert_base model(pytorch)")
+    parser.add_argument("--hubert_soft", type=str, help="path to hubert_soft model(pytorch)")
+    parser.add_argument("--nsf_hifigan", type=str, help="path to nsf_hifigan model(pytorch)")
 
     return parser
 
@@ -129,11 +136,12 @@ if args.colab == True:
 
 if __name__ == 'MMVCServerSIO':
     voiceChangerManager = VoiceChangerManager.get_instance({
-        "hubert": args.hubert,
+        "content_vec_500": args.content_vec_500,
-        "useHubertOnnx": args.useHubertOnnx,
+        "content_vec_500_onnx": args.content_vec_500_onnx,
-        "hubertSoftPt": args.hubertSoftPt,
+        "content_vec_500_onnx_on": args.content_vec_500_onnx_on,
-        "enhancerPt": args.enhancerPt,
+        "hubert_base": args.hubert_base,
-        "enhancerOnnx": args.enhancerOnnx
+        "hubert_soft": args.hubert_soft,
+        "nsf_hifigan": args.nsf_hifigan,
     })
     if CONFIG and (MODEL or ONNX_MODEL):
         if MODEL_TYPE == "MMVCv15" or MODEL_TYPE == "MMVCv13":

server/voice_changer/DDSP_SVC/DDSP_SVC.py

@@ -84,7 +84,7 @@ class DDSP_SVC:
         print("-------------------hopsize", self.hop_size)
 
         # hubert
-        self.vec_path = self.params["hubertSoftPt"]
+        self.vec_path = self.params["hubert_soft"]
         self.encoder = vo.Units_Encoder(
             self.args.data.encoder,
             self.vec_path,
@@ -115,7 +115,7 @@ class DDSP_SVC:
             float(1100))
 
         self.volume_extractor = vo.Volume_Extractor(self.hop_size)
-        self.enhancer_path = self.params["enhancerPt"]
+        self.enhancer_path = self.params["nsf_hifigan"]
         self.enhancer = Enhancer(self.args.enhancer.type, self.enhancer_path, device=self.useDevice())
         return self.get_info()
 

server/voice_changer/MMVCv15/MMVCv15.py

@@ -20,7 +20,7 @@ import pyworld as pw
 from models import SynthesizerTrn
 from voice_changer.MMVCv15.client_modules import convert_continuos_f0, spectrogram_torch, get_hparams_from_file, load_checkpoint
 
-from Exceptions import NoModeLoadedException
+from Exceptions import NoModeLoadedException, ONNXInputArgumentException
 
 providers = ['OpenVINOExecutionProvider', "CUDAExecutionProvider", "DmlExecutionProvider", "CPUExecutionProvider"]
 
@@ -241,11 +241,15 @@ class MMVCv15:
         return result
 
     def inference(self, data):
+        try:
             if self.settings.framework == "ONNX":
                 audio = self._onnx_inference(data)
             else:
                 audio = self._pyTorch_inference(data)
             return audio
+        except onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument as e:
+            print(e)
+            raise ONNXInputArgumentException()
 
     def __del__(self):
         del self.net_g

server/voice_changer/RVC/RVC.py

@@ -94,7 +94,7 @@ class RVC:
         print("[Voice Changer] RVC loading... slot:", self.slot)
 
         try:
-            hubert_path = self.params["hubert"]
+            hubert_path = self.params["hubert_base"]
             models, saved_cfg, task = checkpoint_utils.load_model_ensemble_and_task([hubert_path], suffix="",)
             model = models[0]
             model.eval()

server/voice_changer/SoVitsSvc40/SoVitsSvc40.py

@@ -83,22 +83,27 @@ class SoVitsSvc40:
         self.settings.onnxModelFile = props["files"]["onnxModelFilename"]
         clusterTorchModel = props["files"]["clusterTorchModelFilename"]
 
+        content_vec_path = self.params["content_vec_500"]
+        content_vec_hubert_onnx_path = self.params["content_vec_500_onnx"]
+        content_vec_hubert_onnx_on = self.params["content_vec_500_onnx_on"]
+        hubert_base_path = self.params["hubert_base"]
+
         # hubert model
         try:
-            hubert_path = self.params["hubert"]
-            useHubertOnnx = self.params["useHubertOnnx"]
-            self.useHubertOnnx = useHubertOnnx
 
-            if useHubertOnnx == True:
+            if os.path.exists(content_vec_path) == False:
+                content_vec_path = hubert_base_path
+
+            if content_vec_hubert_onnx_on == True:
                 ort_options = onnxruntime.SessionOptions()
                 ort_options.intra_op_num_threads = 8
                 self.hubert_onnx = onnxruntime.InferenceSession(
-                    HUBERT_ONNX_MODEL_PATH,
+                    content_vec_hubert_onnx_path,
                     providers=providers
                 )
             else:
                 models, saved_cfg, task = checkpoint_utils.load_model_ensemble_and_task(
-                    [hubert_path],
+                    [content_vec_path],
                     suffix="",
                 )
                 model = models[0]

server/voice_changer/SoVitsSvc40v2/SoVitsSvc40v2.py

@@ -78,16 +78,18 @@ class SoVitsSvc40v2:
         self.settings.onnxModelFile = props["files"]["onnxModelFilename"]
         clusterTorchModel = props["files"]["clusterTorchModelFilename"]
 
+        content_vec_path = self.params["content_vec_500"]
+        # content_vec_hubert_onnx_path = self.params["content_vec_500_onnx"]
+        # content_vec_hubert_onnx_on = self.params["content_vec_500_onnx_on"]
+        hubert_base_path = self.params["hubert_base"]
+
         # hubert model
         try:
-            # if sys.platform.startswith('darwin'):
+            if os.path.exists(content_vec_path) == False:
-            #     vec_path = os.path.join(sys._MEIPASS, "hubert/checkpoint_best_legacy_500.pt")
+                content_vec_path = hubert_base_path
-            # else:
-            #     vec_path = "hubert/checkpoint_best_legacy_500.pt"
-            vec_path = self.params["hubert"]
 
             models, saved_cfg, task = checkpoint_utils.load_model_ensemble_and_task(
-                [vec_path],
+                [content_vec_path],
                 suffix="",
             )
             model = models[0]

server/voice_changer/VoiceChanger.py

@@ -14,7 +14,7 @@ from voice_changer.IORecorder import IORecorder
 from voice_changer.utils.Timer import Timer
 from voice_changer.utils.VoiceChangerModel import VoiceChangerModel, AudioInOut
 import time
-from Exceptions import NoModeLoadedException
+from Exceptions import NoModeLoadedException, ONNXInputArgumentException
 
 providers = ['OpenVINOExecutionProvider', "CUDAExecutionProvider", "DmlExecutionProvider", "CPUExecutionProvider"]
 
@@ -289,6 +289,9 @@ class VoiceChanger():
         except NoModeLoadedException as e:
             print("[Voice Changer] [Exception]", e)
             return np.zeros(1).astype(np.int16), [0, 0, 0]
+        except ONNXInputArgumentException as e:
+            print("[Voice Changer] [Exception]", e)
+            return np.zeros(1).astype(np.int16), [0, 0, 0]
         except Exception as e:
             print("VC PROCESSING!!!! EXCEPTION!!!", e)
             print(traceback.format_exc())