code: def test_gradcam_zeros():
      activations = np.zeros((2, 2, 3))  # three 2x2 maps
      weights = np.zeros((3,))  # weight for each map
      lmap = gradcam(weights, activations)
      # all zeroes
      assert np.count_nonzero(lmap) == 0
  
imports: import pytest
  import keras.backend
  from keras.models import Sequential, Model
  from keras.layers import Dense, Activation, Conv2D, GlobalAveragePooling2D, Input, Lambda
  from keras.backend import epsilon
  import numpy
  from eli5.keras.explain_prediction import explain_prediction, _validate_doc, _get_activation_layer
  from eli5.keras.gradcam import _get_target_prediction, _calc_gradient, gradcam
label_desc: Use image node_id 12 for calling a global function with example usage: test_gradcam_zeros() without return types