code: def test_with_pooling():
      valid_input = np.array(
          [1, 2, 4, 3, 8, 6, 7, 5, 9, 10, 12, 11, 13, 16, 15, 14]
      ).astype(np.float32)
      valid_input = np.reshape(valid_input, (1, 4, 4, 1))
      updates, indices = tf.nn.max_pool_with_argmax(
          valid_input, ksize=[2, 2], strides=[2, 2], padding="SAME"
      )
      expected_output = np.array(
          [0, 0, 0, 0, 8, 0, 7, 0, 0, 0, 0, 0, 0, 16, 15, 0]
      ).astype(np.float32)
      expected_output = np.reshape(expected_output, valid_input.shape)
  
      output = MaxUnpooling2DV2(valid_input.shape)(
          updates, indices
      ).numpy()
      np.testing.assert_array_equal(expected_output, output)
  
file_path: addons/tensorflow_addons/layers/tests/max_unpooling_2d_v2_test.py
imports: import numpy
  import pytest
  import tensorflow
  from tensorflow_addons.layers.max_unpooling_2d_v2 import MaxUnpooling2DV2
label_desc: Use image node_id 5 for calling a global function with example usage: test_with_pooling() without return types