update vc code

cosyvoice/cli/cosyvoice.py

@@ -25,7 +25,6 @@ class CosyVoice:
 
     def __init__(self, model_dir, load_jit=True, load_onnx=False):
         instruct = True if '-Instruct' in model_dir else False
-        vc = True if '-VC' in model_dir else False
         self.model_dir = model_dir
         if not os.path.exists(model_dir):
             model_dir = snapshot_download(model_dir)
@@ -37,7 +36,6 @@ class CosyVoice:
                                           '{}/speech_tokenizer_v1.onnx'.format(model_dir),
                                           '{}/spk2info.pt'.format(model_dir),
                                           instruct,
-                                          vc,
                                           configs['allowed_special'])
         self.model = CosyVoiceModel(configs['llm'], configs['flow'], configs['hift'])
         self.model.load('{}/llm.pt'.format(model_dir),

cosyvoice/cli/frontend.py

@@ -42,7 +42,6 @@ class CosyVoiceFrontEnd:
                  speech_tokenizer_model: str,
                  spk2info: str = '',
                  instruct: bool = False,
-                 vc: bool = False,
                  allowed_special: str = 'all'):
         self.tokenizer = get_tokenizer()
         self.feat_extractor = feat_extractor
@@ -59,7 +58,6 @@ class CosyVoiceFrontEnd:
         else:
             self.spk2info = {}
         self.instruct = instruct
-        self.vc = vc
         self.allowed_special = allowed_special
         self.inflect_parser = inflect.engine()
         self.use_ttsfrd = use_ttsfrd

cosyvoice/cli/model.py

@@ -54,10 +54,9 @@ class CosyVoiceModel:
         self.hift_cache_dict = {}
 
     def load(self, llm_model, flow_model, hift_model):
-        if self.llm is not None:
-            self.llm.load_state_dict(torch.load(llm_model, map_location=self.device))
-            self.llm.to(self.device).eval()
-            self.llm.half()
+        self.llm.load_state_dict(torch.load(llm_model, map_location=self.device))
+        self.llm.to(self.device).eval()
+        self.llm.half()
         self.flow.load_state_dict(torch.load(flow_model, map_location=self.device))
         self.flow.to(self.device).eval()
         self.hift.load_state_dict(torch.load(hift_model, map_location=self.device))