code: def _test_predict_and_extract_features(
      self, hub_interface: ClassyHubInterface
  ):
      dataset = hub_interface.create_image_dataset(
          image_files=[self.image_path], phase_type="test"
      )
      data_iterator = hub_interface.get_data_iterator(dataset)
      input = next(data_iterator)
      # set the model to eval mode
      hub_interface.eval()
      output = hub_interface.predict(input)
      self.assertIsNotNone(output)
      # see the prediction for the input
      hub_interface.predict(input).argmax().item()
      # check extract features
      output = hub_interface.extract_features(input)
      self.assertIsNotNone(output)
  
imports: import shutil
  import tempfile
  import unittest
  import torch
  from classy_vision.dataset.transforms import ClassyTransform
  from classy_vision.hub import ClassyHubInterface
  from classy_vision.models import build_model, ClassyModel
  from classy_vision.tasks import build_task, ClassyTask
  from test.generic.config_utils import get_test_task_config
  from torchvision import models, transforms
label_desc: Use image node_id 3 for calling the TestClassyHubInterface obj's underlying member method code with example usage: obj._test_predict_and_extract_features(hub_interface) without return types