Remove unused imports and fix style using make style

tests/generation/test_candidate_generator.py

@@ -1,24 +1,20 @@
 import gc
-import logging
 import threading
 import unittest
 import weakref
 from unittest.mock import MagicMock
 
-from zmq import device
-
 import numpy as np
 import torch
 
+from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig
 from transformers.generation.candidate_generator import (
     AssistantToTargetTranslator,
     AssistantVocabTranslatorCache,
     AssistedCandidateGeneratorDifferentTokenizers,
-    UniversalSpeculativeDecodingGenerator
+    UniversalSpeculativeDecodingGenerator,
 )
 
-from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig
-
 
 class TestAssistedCandidateGeneratorDifferentTokenizers(unittest.TestCase):
     def test_no_intersection(self):
@@ -313,15 +309,15 @@ def test_basic_generation(self):
     def test_mismatched_vocabularies(self):
         """Test handling of mismatched vocabularies between models"""
         # Create input with tokens present in main but not assistant vocab
-        # Find a token that is not in the assistant tokenizer but in 
+        # Find a token that is not in the assistant tokenizer but in
         # the main tokenizer.
         missing_token = next(
             token for token in self.main_tokenizer.get_vocab()
             if token not in self.assistant_tokenizer.get_vocab() and
                token not in self.main_tokenizer.all_special_tokens and
                "reserved_" not in token
         )
-        input_ids = torch.tensor([[self.main_tokenizer.convert_tokens_to_ids(missing_token)]]) 
+        input_ids = torch.tensor([[self.main_tokenizer.convert_tokens_to_ids(missing_token)]])
         self.generator.input_ids = input_ids
         candidates, scores = self.generator.get_candidates(input_ids)
         self.assertIsNotNone(candidates)