formatting

src/winer_worker.py

@@ -39,32 +39,31 @@ class WinerWorker(nlp_ws.NLPWorker):
             sent_starts: list,
             max_tokens: int = 510
         ):
-        """
-        Pack sentences without exceeding a maximum token count.
+        """Pack sentences without exceeding a maximum token count.
 
-        This method takes in plain text sentences, their tokenized 
+        This method takes in plain text sentences, their tokenized
         versions, and sentence start indices,
-        and it creates batches of sentences such that the total 
+        and it creates batches of sentences such that the total
         token count per batch does not exceed the
         specified max_tokens limit.
 
         Args:
             plain_inputs (list): List of plain text sentences.
-            tokenized_inputs (list): List of tokenized versions 
+            tokenized_inputs (list): List of tokenized versions
             of the sentences.
             sent_starts (list): List of sentence start indices.
-            max_tokens (int, optional): The maximum number of 
+            max_tokens (int, optional): The maximum number of
             tokens allowed per chunk. Defaults to 510.
 
         Returns:
-            tuple: 
-                - packed_plain_inputs (list): List of packed 
-                plain text sentences, where each element 
+            tuple:
+                - packed_plain_inputs (list): List of packed
+                plain text sentences, where each element
                 is a chunk of sentences.
-                - packed_tokenized_inputs (list): List of packed 
-                tokenized inputs corresponding to the plain 
+                - packed_tokenized_inputs (list): List of packed
+                tokenized inputs corresponding to the plain
                 text chunks.
-                - packed_sent_starts (list): List of sentence 
+                - packed_sent_starts (list): List of sentence
                 start indices for each chunk.
 
         """
@@ -164,4 +163,4 @@ class WinerWorker(nlp_ws.NLPWorker):
 
         # Clean the memory
         gc.collect()
-        torch.cuda.empty_cache()
\ No newline at end of file
+        torch.cuda.empty_cache()