improve:onnx export

client/demo/src/components/demo/components2/101_CharacterArea.tsx

@@ -249,7 +249,7 @@ export const CharacterArea = (_props: CharacterAreaProps) => {
                 </div>
             </div>
         );
-    }, [selected, serverSetting.getOnnx, serverSetting.updateModelDefault]);
+    }, [selected, serverSetting.getOnnx, serverSetting.updateModelDefault, guiState.isConverting]);
 
     const characterArea = useMemo(() => {
         return (

server/voice_changer/DiffusionSVC/pipeline/Pipeline.py

@@ -211,7 +211,6 @@ class Pipeline(object):
                 pitch_buffer = None
 
             del pitch, pitchf, feats, sid
-            torch.cuda.empty_cache()
             audio1 = self.resamplerOut(audio1.float())
         # print("[Timer::5: ]", t.secs)
         return audio1, pitch_buffer, feats_buffer

server/voice_changer/RVC/RVC.py

@@ -225,7 +225,15 @@ class RVC(VoiceChangerModel):
             print("[Voice Changer] export2onnx, No pyTorch filepath.")
             return {"status": "ng", "path": ""}
 
+        if self.pipeline is not None:
+            del self.pipeline
+            self.pipeline = None
+
+        torch.cuda.empty_cache()
+        self.initialize()
+        
         output_file_simple = export2onnx(self.settings.gpu, modelSlot)
+        
         return {
             "status": "ok",
             "path": f"/tmp/{output_file_simple}",

server/voice_changer/RVC/inferencer/VorasInferencebeta.py

@@ -12,7 +12,7 @@ class VoRASInferencer(Inferencer):
         super().setProps(EnumInferenceTypes.pyTorchVoRASbeta, file, False, gpu)
 
         dev = DeviceManager.get_instance().getDevice(gpu)
-        self.isHalf = False # DeviceManager.get_instance().halfPrecisionAvailable(gpu)
+        self.isHalf = False  # DeviceManager.get_instance().halfPrecisionAvailable(gpu)
 
         cpt = torch.load(file, map_location="cpu")
         model = Synthesizer(**cpt["params"])

server/voice_changer/RVC/inferencer/models.py

@@ -138,7 +138,6 @@ class SynthesizerTrnMsNSFsid(nn.Module):
         return o, x_mask, (z, z_p, m_p, logs_p)
 
 
-
 class SynthesizerTrnMsNSFsidNono(nn.Module):
     def __init__(self, spec_channels, segment_size, inter_channels, hidden_channels, filter_channels, n_heads, n_layers, kernel_size, p_dropout, resblock, resblock_kernel_sizes, resblock_dilation_sizes, upsample_rates, upsample_initial_channel, upsample_kernel_sizes, spk_embed_dim, gin_channels, emb_channels, sr=None, **kwargs):
         super().__init__()

server/voice_changer/RVC/pipeline/Pipeline.py

@@ -243,7 +243,7 @@ class Pipeline(object):
             pitchf_buffer = None
 
         del p_len, pitch, pitchf, feats
-        torch.cuda.empty_cache()
+        # torch.cuda.empty_cache()
 
         # inferで出力されるサンプリングレートはモデルのサンプリングレートになる。
         # pipelineに（入力されるときはhubertように16k）
@@ -253,5 +253,11 @@ class Pipeline(object):
             audio1 = audio1[offset:end]
 
         del sid
-        torch.cuda.empty_cache()
+        # torch.cuda.empty_cache()
         return audio1, pitchf_buffer, feats_buffer
+
+    def __del__(self):
+        del self.embedder
+        del self.inferencer
+        del self.pitchExtractor
+        print('Pipeline has been deleted')