code: def test_sequence_classification_forward(self):
      config, input_ids, batch_size = self._get_config_and_data()
      model = FlaxBartForSequenceClassification(config)
      outputs = model(input_ids=input_ids, decoder_input_ids=input_ids)
      expected_shape = (batch_size, config.num_labels)
      self.assertEqual(outputs["logits"].shape, expected_shape)
  
imports: import unittest
  import numpy
  import timeout_decorator
  from transformers import BartConfig, BartTokenizer, is_flax_available
  from transformers.testing_utils import require_flax, slow
  from ...generation.test_generation_flax_utils import FlaxGenerationTesterMixin
  from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
label_desc: Use image node_id 2 for calling the BartHeadTests obj's underlying member method code with example usage: obj.test_sequence_classification_forward() without return types