fixed kwargs confusion

and resolved path issues

autotranscript/diarisation.py

@@ -2,9 +2,10 @@ from pyannote.audio import Pipeline
 from pyannote.audio.pipelines.speaker_diarization import SpeakerDiarization
 from torch import Tensor
 import os
+from pathlib import Path
 from typing import TypeVar, Union
 import json
-from .misc import PYANNOTE_DEFAULT_PATH
+from .misc import PYANNOTE_DEFAULT_CONFIG, PYANNOTE_DEFAULT_PATH
 Annotation = TypeVar('Annotation') 
 
 class Diariser:
@@ -118,10 +119,12 @@ class Diariser:
         return token
     
     @classmethod
-    def load_model(cls, model: str = PYANNOTE_DEFAULT_PATH, 
+    def load_model(cls, 
-                        token: str = "",
+                    model: str = PYANNOTE_DEFAULT_CONFIG, 
-                        local : bool = True,
+                    token: str = None,
-                        *args, **kwargs) -> Pipeline:
+                    cache_dir: Union[Path, str] = PYANNOTE_DEFAULT_PATH,
+                    hparams_file: Union[str, Path] = None
+                    ) -> Pipeline:
         """
         Load modules from pyannote
 
@@ -139,17 +142,15 @@ class Diariser:
         -------
         Pipeline Object
         """
-        
+        if not os.path.exists(model) and token is None:
-        if local:
+            token = cls._get_token()
-            diarization_model =  Pipeline.from_pretrained(model,*args, **kwargs)
+            
-        else:
+        _model =  Pipeline.from_pretrained(model,
-            print("Loading model from HuggingFace")
+                                           use_auth_token = token,
-            if token == "":
+                                           cache_dir = cache_dir,
-                token = cls._get_token()
+                                           hparams_file = hparams_file,)
-            diarization_model =  Pipeline.from_pretrained(model, use_auth_token = token,
+
-                                                           *args, **kwargs)
+        return cls(_model)
-        
-        return cls(diarization_model)
 
     @staticmethod
     def _get_diarisation_kwargs(**kwargs) -> dict: