chore: make lint happy

ChatTTS/core.py

@@ -145,7 +145,7 @@ class Chat:
         use_flash_attn=False,
         use_vllm=False,
         experimental: bool = False,
-        enable_cache=False,
+        enable_cache=True,
     ) -> bool:
         download_path = self.download_models(source, force_redownload, custom_path)
         if download_path is None:
@@ -289,7 +289,7 @@ class Chat:
         use_flash_attn=False,
         use_vllm=False,
         experimental: bool = False,
-        enable_cache = False,
+        enable_cache = True,
     ):
         if device is None:
             device = select_device(experimental=experimental)

ChatTTS/model/gpt.py

@@ -28,7 +28,7 @@ class GPT(nn.Module):
         device=torch.device("cpu"),
         device_gpt=torch.device("cpu"),
         logger=logging.getLogger(__name__),
-        enable_cache=False,
+        enable_cache=True,
     ):
         super().__init__()
 

examples/web/funcs.py

@@ -62,7 +62,7 @@ def on_audio_seed_change(audio_seed_input):
     return rand_spk
 
 
-def load_chat(cust_path: Optional[str], coef: Optional[str], enable_cache = False) -> bool:
+def load_chat(cust_path: Optional[str], coef: Optional[str], enable_cache = True) -> bool:
     if cust_path == None:
         ret = chat.load(coef=coef, enable_cache=enable_cache)
     else:

examples/web/webui.py

@@ -261,12 +261,12 @@ def main():
     parser.add_argument("--root_path", type=str, help="root path")
     parser.add_argument("--custom_path", type=str, help="custom model path")
     parser.add_argument("--coef", type=str, help="custom dvae coefficient")
-    parser.add_argument("--enable_cache", action="store_true", help="enable model cache")
+    parser.add_argument("--disable_cache", action="store_true", help="enable model cache")
     args = parser.parse_args()
 
     logger.info("loading ChatTTS model...")
 
-    if load_chat(args.custom_path, args.coef, args.enable_cache):
+    if load_chat(args.custom_path, args.coef, not args.disable_cache):
         logger.info("Models loaded successfully.")
     else:
         logger.error("Models load failed.")