Repository: huggingface/transformers
Pull request: Fixed convert_batch_to_list_format staticmethod function call

# What does this PR do?
Fixes these [failing tests](https://github.com/huggingface/transformers/actions/runs/19758977591/job/56616632584#step:14:5132)

<img width="1306" height="207" alt="image" src="https://github.com/user-attachments/assets/c90a23e0-5b1a-4207-869a-1207b10de8a7" />

## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#create-a-pull-request),
      Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes? Here are the
      [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and
      [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?


## Who can review?
@ArthurZucker @zucchini-nlp @itazap 

Changed files:
filename: tests/test_tokenization_common.py
patch: @@ -2302,7 +2302,9 @@ def test_batch_encode_plus_batch_sequence_length(self):
 
         encoded_sequences = [tokenizer(sequence) for sequence in sequences]
         encoded_sequences_batch = tokenizer(sequences, padding=False)
-        self.assertListEqual(encoded_sequences, self.convert_batch_to_list_format(encoded_sequences_batch))
+        self.assertListEqual(
+            encoded_sequences, TokenizerTesterMixin.convert_batch_to_list_format(encoded_sequences_batch)
+        )
 
         maximum_length = len(max([encoded_sequence["input_ids"] for encoded_sequence in encoded_sequences], key=len))
 
@@ -2316,7 +2318,7 @@ def test_batch_encode_plus_batch_sequence_length(self):
         encoded_sequences_batch_padded = tokenizer(sequences, padding=True)
         self.assertListEqual(
             encoded_sequences_padded,
-            self.convert_batch_to_list_format(encoded_sequences_batch_padded),
+            TokenizerTesterMixin.convert_batch_to_list_format(encoded_sequences_batch_padded),
         )
 
         # check 'longest' is unsensitive to a max length
@@ -2357,7 +2359,9 @@ def test_batch_encode_plus_padding(self):
             tokenizer(sequence, max_length=max_length, padding="max_length") for sequence in sequences
         ]
         encoded_sequences_batch = tokenizer(sequences, max_length=max_length, padding="max_length")
-        self.assertListEqual(encoded_sequences, self.convert_batch_to_list_format(encoded_sequences_batch))
+        self.assertListEqual(
+            encoded_sequences, TokenizerTesterMixin.convert_batch_to_list_format(encoded_sequences_batch)
+        )
 
         # Left padding tests
         tokenizer = self.get_tokenizer(do_lower_case=False)
@@ -2377,7 +2381,9 @@ def test_batch_encode_plus_padding(self):
             tokenizer(sequence, max_length=max_length, padding="max_length") for sequence in sequences
         ]
         encoded_sequences_batch = tokenizer(sequences, max_length=max_length, padding="max_length")
-        self.assertListEqual(encoded_sequences, self.convert_batch_to_list_format(encoded_sequences_batch))
+        self.assertListEqual(
+            encoded_sequences, TokenizerTesterMixin.convert_batch_to_list_format(encoded_sequences_batch)
+        )
 
     def test_pretokenized_inputs(self):
         # Test when inputs are pretokenized