name2go fix for fast_inference (RVC-Boss#1133)

Author: XXXXRT666

GPT_SoVITS/prepare_datasets/2-get-hubert-wav32k.py

@@ -82,15 +82,15 @@ def name2go(wav_name,wav_path):
         tensor_wav16 = tensor_wav16.to(device)
     ssl=model.model(tensor_wav16.unsqueeze(0))["last_hidden_state"].transpose(1,2).cpu()#torch.Size([1, 768, 215])
     if np.isnan(ssl.detach().numpy()).sum()!= 0:
-        nan_fails.append(wav_name)
+        nan_fails.append((wav_name,wav_path))
         print("nan filtered:%s"%wav_name)
         return
     wavfile.write(
         "%s/%s"%(wav32dir,wav_name),
         32000,
         tmp_audio32.astype("int16"),
     )
-    my_save(ssl,hubert_path )
+    my_save(ssl,hubert_path)
 
 with open(inp_text,"r",encoding="utf8")as f:
     lines=f.read().strip("\n").split("\n")
@@ -113,8 +113,8 @@ def name2go(wav_name,wav_path):
 if(len(nan_fails)>0 and is_half==True):
     is_half=False
     model=model.float()
-    for wav_name in nan_fails:
+    for wav in nan_fails:
         try:
-            name2go(wav_name)
+            name2go(wav[0],wav[1])
         except:
             print(wav_name,traceback.format_exc())