code: def test_should_explain_output(
      convolutional_model_with_separate_activation_layer,
      random_data,
      mocker,
  ):
      mocker.patch(
          "tf_explain.core.vanilla_gradients.grid_display",
          side_effect=lambda x: x,
      )
      images, labels = random_data
      explainer = VanillaGradients()
      grid = explainer.explain(
          (images, labels),
          convolutional_model_with_separate_activation_layer,
          0,
      )
  
      # Outputs is in grayscale format
      assert grid.shape == images.shape[:-1]
  
imports: import pytest
  from tf_explain.core.vanilla_gradients import VanillaGradients, UNSUPPORTED_ARCHITECTURE_WARNING
label_desc: Use image node_id 1 for calling a global function with example usage: test_should_explain_output(convolutional_model_with_separate_activation_layer, random_data, mocker) without return types