code: def test_lm_uneven_forward(self):
      config = BlenderbotConfig(
          vocab_size=self.vocab_size,
          d_model=14,
          encoder_layers=2,
          decoder_layers=2,
          encoder_attention_heads=2,
          decoder_attention_heads=2,
          encoder_ffn_dim=8,
          decoder_ffn_dim=8,
          max_position_embeddings=48,
      )
      lm_model = FlaxBlenderbotForConditionalGeneration(config)
      context = np.array(
          [[71, 82, 18, 33, 46, 91, 2], [68, 34, 26, 58, 30, 2, 1]],
          dtype=np.int64,
      )
      summary = np.array(
          [[82, 71, 82, 18, 2], [58, 68, 2, 1, 1]], dtype=np.int64
      )
      outputs = lm_model(input_ids=context, decoder_input_ids=summary)
      expected_shape = (*summary.shape, config.vocab_size)
      self.assertEqual(outputs["logits"].shape, expected_shape)
  
imports: import unittest
  import numpy
  import timeout_decorator
  from transformers import BlenderbotConfig, is_flax_available
  from transformers.testing_utils import jax_device, require_flax, slow
  from ...generation.test_generation_flax_utils import FlaxGenerationTesterMixin
  from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
label_desc: Use image node_id 3 for calling the BlenderbotHeadTests obj's underlying member method code with example usage: obj.test_lm_uneven_forward() without return types