code: def test_inference_embedder(self):
      retriever_projected_size = 128
  
      model = RealmEmbedder.from_pretrained(
          "google/realm-cc-news-pretrained-embedder"
      )
      input_ids = torch.tensor([[0, 1, 2, 3, 4, 5]])
      output = model(input_ids)[0]
  
      expected_shape = torch.Size((1, retriever_projected_size))
      self.assertEqual(output.shape, expected_shape)
  
      expected_slice = torch.tensor([[-0.0714, -0.0837, -0.1314]])
      self.assertTrue(
          torch.allclose(output[:, :3], expected_slice, atol=1e-4)
      )
  
imports: import copy
  import unittest
  import numpy
  from transformers import RealmConfig, is_torch_available
  from transformers.testing_utils import require_torch, slow, torch_device
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
label_desc: Use image node_id 1 for calling the RealmModelIntegrationTest obj's underlying member method code with example usage: obj.test_inference_embedder() without return types