code: def test_inference_no_head(self):
      directory = "nvidia/megatron-bert-uncased-345m"
      if "MYDIR" in os.environ:
          directory = os.path.join(os.environ["MYDIR"], directory)
      model = MegatronBertModel.from_pretrained(directory)
      model.to(torch_device)
      model.half()
      input_ids = _long_tensor(
          [[101, 7110, 1005, 1056, 2023, 11333, 17413, 1029, 102]]
      )
      with torch.no_grad():
          output = model(input_ids)[0]
      expected_shape = torch.Size((1, 9, 1024))
      self.assertEqual(output.shape, expected_shape)
  
      expected = [
          -0.6040,
          -0.2517,
          -0.1025,
          0.3420,
          -0.6758,
          -0.0017,
          -0.1089,
          -0.1990,
          0.5728,
      ]
      for ii in range(3):
          for jj in range(3):
              a = output[0, ii, jj]
              b = expected[3 * ii + jj]
              msg = "ii={} jj={} a={} b={}".format(ii, jj, a, b)
              self.assertTrue(
                  math.isclose(
                      a, b, rel_tol=TOLERANCE, abs_tol=TOLERANCE
                  ),
                  msg=msg,
              )
  
imports: import math
  import os
  import unittest
  from transformers import MegatronBertConfig, 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 ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
label_desc: Use image node_id 1 for calling the MegatronBertModelIntegrationTests obj's underlying member method code with example usage: obj.test_inference_no_head() without return types