code: def test_get_nearest_neighbors(self):
      test_filename = "test_inference.index"
      for indexer_input in [self.train_vectors, self.dataset]:
          for load_from_file in [False, True]:
              inference_model = InferenceModel(
                  trunk=self.model, data_device=TEST_DEVICE
              )
              if load_from_file:
                  inference_model.load_knn_func(test_filename)
              else:
                  inference_model.train_knn(indexer_input)
                  inference_model.save_knn_func(test_filename)
  
              self.helper_assertions(inference_model)
  
      os.remove(test_filename)
  
imports: import os
  import unittest
  import uuid
  import faiss
  import torch
  import torchvision
  from torchvision import datasets, transforms
  from pytorch_metric_learning.utils.inference import InferenceModel
  from ..None import TEST_DEVICE
label_desc: Use image node_id 4 for calling the TestInference obj's underlying member method code with example usage: obj.test_get_nearest_neighbors() without return types