code: def test_model_fails_for_uneven_eos_tokens(self):
      config = BartConfig(eos_token_id=2)
      model = TFBartForSequenceClassification(config)
      inputs = {
          "input_ids": tf.constant(
              [[1, 2, 2, 2], [1, 3, 2, 2], [2, 2, 3, 3]]
          ),
          "attention_mask": tf.constant(
              [[1, 1, 1, 1], [1, 1, 1, 1], [1, 1, 1, 1]]
          ),
      }
      with self.assertRaises(tf.errors.InvalidArgumentError):
          model(inputs)
  
imports: from __future__ import annotations
  import copy
  import tempfile
  import unittest
  import numpy
  from transformers import BartConfig, BartTokenizer, is_tf_available
  from transformers.testing_utils import require_tf, slow
  from transformers.utils import cached_property
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
  from ...test_pipeline_mixin import PipelineTesterMixin
  from ...utils.test_modeling_tf_core import TFCoreModelTesterMixin
label_desc: Use image node_id 1 for calling the TFBartForSequenceClassificationTest obj's underlying member method code with example usage: obj.test_model_fails_for_uneven_eos_tokens() without return types