code: def test_should_call_activations_visualization_callback(
      random_data, convolutional_model, output_dir, mocker
  ):
      mock_explainer = mocker.MagicMock(
          explain=mocker.MagicMock(return_value=np.zeros((28, 28)))
      )
      mocker.patch(
          "tf_explain.callbacks.activations_visualization.ExtractActivations",
          return_value=mock_explainer,
      )
  
      images, labels = random_data
  
      callbacks = [
          ActivationsVisualizationCallback(
              validation_data=random_data,
              layers_name=["activation_1"],
              output_dir=output_dir,
          )
      ]
  
      convolutional_model.fit(
          images, labels, batch_size=2, epochs=1, callbacks=callbacks
      )
  
      mock_explainer.explain.assert_called_once_with(
          random_data, convolutional_model, ["activation_1"]
      )
      assert len([_ for _ in output_dir.iterdir()]) == 1
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_should_call_activations_visualization_callback(random_data, convolutional_model, output_dir, mocker) without return types