class_docstr: All the below results were obtained with the original checkpoints and code
  base from https://github.com/allenai/longformer.
  IMPORTANT: Note that the original checkpoints include a `postion_embeddings` "hack"
  and have to be cut to have the correct shape.
  See: https://github.com/huggingface/transformers/pull/9278#issue-544709661.
code: def test_inference_head(self):
      model = LEDForConditionalGeneration.from_pretrained(
          "allenai/led-base-16384"
      ).to(torch_device)
  
      # change to intended input
      input_ids = _long_tensor(
          [512 * [0, 31414, 232, 328, 740, 1140, 12695, 69]]
      )
      decoder_input_ids = _long_tensor(
          [128 * [0, 31414, 232, 328, 740, 1140, 12695, 69]]
      )
      inputs_dict = prepare_led_inputs_dict(
          model.config, input_ids, decoder_input_ids
      )
      with torch.no_grad():
          output = model(**inputs_dict, use_cache=False).logits
      expected_shape = torch.Size((1, 1024, model.config.vocab_size))
      self.assertEqual(output.shape, expected_shape)
      # change to expected output here
      expected_slice = torch.tensor(
          [
              [33.6507, 6.4572, 16.8089],
              [5.8739, -2.4238, 11.2902],
              [-3.2139, -4.3149, 4.2783],
          ],
          device=torch_device,
      )
      self.assertTrue(
          torch.allclose(
              output[:, :3, :3], expected_slice, atol=TOLERANCE
          )
      )
  
imports: import copy
  import tempfile
  import unittest
  from transformers import LEDConfig, is_torch_available
  from transformers.models.auto import get_values
  from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
  from transformers.utils import cached_property
  from ...generation.test_generation_utils import GenerationTesterMixin
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, ids_tensor
label_desc: Use image node_id 3 for calling the LEDModelIntegrationTests obj's underlying member method code with example usage: obj.test_inference_head() without return types