cleaning

nnet/preprocessor.py

@@ -222,7 +222,7 @@ class MelSpecFrontEnd(torch.nn.Module):
 
 
 
-class RawPreprocessor(torch.nn.Module):
+class (torch.nn.Module):
     """
 
     """

nnet/sincnet.py

@@ -416,7 +416,7 @@ class SincNet(torch.nn.Module):
         #return output.transpose(1, 2)
         return output
 
-    def dimension(self):
+    def dimension():
         doc = "Output features dimension."
 
         def fget(self):

nnet/xvector.py

@@ -1227,7 +1227,6 @@ def extract_embeddings(idmap_name,
                        data_root_name,
                        device,
                        model_yaml=None,
-                       speaker_number=None,
                        file_extension="wav",
                        transform_pipeline=None,
                        frame_shift=0.01,
@@ -1255,8 +1254,7 @@ def extract_embeddings(idmap_name,
     # Load the model
     if isinstance(model_filename, str):
         checkpoint = torch.load(model_filename, map_location=device)
-        if speaker_number is None:
-            speaker_number = checkpoint["speaker_number"]
+        speaker_number = checkpoint["speaker_number"]
         if model_yaml is None:
             model_archi = checkpoint["model_archi"]
         else:
@@ -1438,7 +1436,10 @@ def extract_sliding_embedding(idmap_name,
     :return:
     """
     # From the original IdMap, create the new one to extract x-vectors
-    input_idmap = IdMap(idmap_name)
+    if not isinstance(idmap_name, IdMap):
+        input_idmap = IdMap(idmap_name)
+    else:
+        input_idmap = idmap_name
 
     # Create temporary lists
     nb_chunks = 0