unit test modelscope for sd

funasr/bin/diar_inference_launch.py

@@ -127,7 +127,7 @@ def get_parser():
 def inference_launch(mode, **kwargs):
     if mode == "sond":
         from funasr.bin.sond_inference import inference_modelscope
-        return inference_modelscope(**kwargs)
+        return inference_modelscope(mode=mode, **kwargs)
     elif mode == "sond_demo":
         from funasr.bin.sond_inference import inference_modelscope
         param_dict = {
@@ -141,7 +141,7 @@ def inference_launch(mode, **kwargs):
                     kwargs["param_dict"][key] = param_dict[key]
         else:
             kwargs["param_dict"] = param_dict
-        return inference_modelscope(**kwargs)
+        return inference_modelscope(mode=mode, **kwargs)
     else:
         logging.info("Unknown decoding mode: {}".format(mode))
         return None

funasr/bin/sond_inference.py

@@ -231,6 +231,7 @@ def inference_modelscope(
         dur_threshold: int = 10,
         out_format: str = "vad",
         param_dict: Optional[dict] = None,
+        mode: str = "sond",
         **kwargs,
 ):
     assert check_argument_types()
@@ -254,7 +255,7 @@ def inference_modelscope(
     set_all_random_seed(seed)
 
     # 2a. Build speech2xvec [Optional]
-    if param_dict is not None and "extract_profile" in param_dict and param_dict["extract_profile"]:
+    if mode == "sond_demo" and param_dict is not None and "extract_profile" in param_dict and param_dict["extract_profile"]:
         assert "sv_train_config" in param_dict, "sv_train_config must be provided param_dict."
         assert "sv_model_file" in param_dict, "sv_model_file must be provided in param_dict."
         sv_train_config = param_dict["sv_train_config"]