code: def test_reload():
      """Test that a Metalearner can be reloaded."""
      learner = SineLearner()
      optimizer = dc.models.optimizers.Adam(learning_rate=5e-3)
      maml = 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)
      loss = loss.detach().numpy()
  
      reloaded = MAML(SineLearner(), model_dir=maml.model_dir)
      reloaded.restore()
      reloaded_loss, reloaded_outputs = maml.predict_on_batch(batch)
      reloaded_loss = reloaded_loss.detach().numpy()
  
      assert loss == reloaded_loss
  
      assert len(outputs) == len(reloaded_outputs)
  
      outputs = outputs[0].detach().numpy()
      reloaded_outputs = reloaded_outputs[0].detach().numpy()
      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