class_docstr: Basic test to train module
code: def testTrainSave(self):
      model_type = "mockfasterrcnn"
  
      # Save checkpoints to a temp directory.
      tmp_job_dir = tempfile.mkdtemp()
      override_params = [
          "train.num_epochs={}".format(self.total_epochs),
          "train.job_dir={}".format(tmp_job_dir),
          "train.run_name=test_runname",
      ]
  
      config = self.get_config(
          model_type, override_params=override_params
      )
  
      run(
          config,
          get_dataset_fn=self.get_dataset,
          get_model_fn=self.get_model,
      )
  
      # Create new graph which will load previously saved checkpoint
      tf.reset_default_graph()
      new_session = tf.Session()
      new_saver = tf.train.import_meta_graph(
          tmp_job_dir + "/test_runname/model.ckpt-3.meta"
      )
      new_saver.restore(
          new_session, tmp_job_dir + "/test_runname/model.ckpt-3"
      )
  
      # Get tensor from graph and run it in session
      w_tensor = tf.get_default_graph().get_tensor_by_name(
          "mockfasterrcnn/w:0"
      )
      w_numpy = new_session.run(w_tensor)
  
      # Assert we correctly loaded the weight
      self.assertArrayNear(w_numpy, [2.5, 3.0], err=0.01)
  
imports: import sonnet
  import tempfile
  import tensorflow
  from easydict import EasyDict
  from luminoth.train import run
  from luminoth.models import get_model
  from luminoth.utils.config import get_model_config, load_config_files, get_base_config
label_desc: Use image node_id 6 for calling the TrainTest obj's underlying member method code with example usage: obj.testTrainSave() without return types