code: def test_list_of_text(self):
      model = TextModel()
      dataset = TextDataset()
      inference_model = InferenceModel(
          trunk=model, data_device=TEST_DEVICE
      )
      inference_model.train_knn(dataset)
      inference_model.add_to_knn(
          [["test1", "test2"], ["test3", "test4"]]
      )
      inference_model.get_nearest_neighbors(["dog", "cat"], k=10)
  
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 6 for calling the TestInference obj's underlying member method code with example usage: obj.test_list_of_text() without return types