1 files changed, 12 insertions, 11 deletions

diff --git a/models/clip/tokenizer.py b/models/clip/tokenizer.py
index 789b525..a866641 100644
--- a/models/clip/tokenizer.py
+++ b/models/clip/tokenizer.py
@@ -91,18 +91,21 @@ class MultiCLIPTokenizer(CLIPTokenizer):
             self.vector_shuffle = shuffle_none
 
     def add_multi_tokens(
-        self,
-        new_tokens: Union[str, list[str]],
-        num_vectors: Union[int, list[int]] = 1
+        self, new_tokens: Union[str, list[str]], num_vectors: Union[int, list[int]] = 1
     ) -> Union[list[int], list[list[int]]]:
         if isinstance(new_tokens, list):
             if isinstance(num_vectors, int):
                 num_vectors = [num_vectors] * len(new_tokens)
 
             if len(num_vectors) != len(new_tokens):
-                raise ValueError("Expected new_tokens and num_vectors to have the same len")
+                raise ValueError(
+                    "Expected new_tokens and num_vectors to have the same len"
+                )
 
-            return [self.add_multi_tokens(new_token, vecs) for new_token, vecs in zip(new_tokens, num_vectors)]
+            return [
+                self.add_multi_tokens(new_token, vecs)
+                for new_token, vecs in zip(new_tokens, num_vectors)
+            ]
 
         if isinstance(num_vectors, list):
             raise ValueError("Expected num_vectors to be int for single token")
@@ -129,13 +132,11 @@ class MultiCLIPTokenizer(CLIPTokenizer):
             return [id]
 
     def expand_ids(self, ids: list[int]):
-        return [
-            new_id
-            for id in ids
-            for new_id in self.expand_id(id)
-        ]
+        return [new_id for id in ids for new_id in self.expand_id(id)]
 
-    def expand_batched_ids(self, input_ids: Union[list[int], list[list[int]], tuple[list[int]]]):
+    def expand_batched_ids(
+        self, input_ids: Union[list[int], list[list[int]], tuple[list[int]]]
+    ):
         if isinstance(input_ids, (list, tuple)) and isinstance(input_ids[0], list):
             return [self.expand_ids(batch) for batch in input_ids]
         else: