code: def test_reload():
      """Test that a Metalearner can be reloaded."""
      learner = SineLearner()
      optimizer = dc.models.optimizers.Adam(learning_rate=5e-3)
      maml = dc.metalearning.MAML(
          learner, meta_batch_size=4, optimizer=optimizer
      )
      maml.fit(900)
  
      learner.select_task()
      batch = learner.get_batch()
      loss, outputs = maml.predict_on_batch(batch)
  
      reloaded = dc.metalearning.MAML(
          SineLearner(), model_dir=maml.model_dir
      )
      reloaded.restore()
      reloaded_loss, reloaded_outputs = maml.predict_on_batch(batch)
  
      assert loss == reloaded_loss
  
      assert len(outputs) == len(reloaded_outputs)
      for output, reloaded_output in zip(outputs, reloaded_outputs):
          assert np.all(output == reloaded_output)
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_reload() without return types