code: def test_padding_valid_complex():
      valid_input = np.array(
          [
              1,
              2,
              4,
              3,
              8,
              6,
              7,
              5,
              9,
              10,
              12,
              11,
              13,
              16,
              15,
              14,
              20,
              18,
              17,
              19,
          ]
      ).astype(np.float32)
      valid_input = np.reshape(valid_input, (1, 4, 5, 1))
      updates, indices = tf.nn.max_pool_with_argmax(
          valid_input, ksize=[2, 3], strides=[2, 2], padding="VALID"
      )
      expected_output = np.array(
          [
              0,
              0,
              0,
              0,
              0,
              0,
              7,
              0,
              0,
              10,
              0,
              0,
              0,
              0,
              0,
              0,
              20,
              0,
              0,
              19,
          ]
      ).astype(np.float32)
      expected_output = np.reshape(expected_output, valid_input.shape)
  
      output = MaxUnpooling2D(pool_size=(2, 3), padding="VALID")(
          updates, indices
      ).numpy()
      np.testing.assert_array_equal(expected_output, output)
  
file_path: addons/tensorflow_addons/layers/tests/max_unpooling_2d_test.py
imports: import numpy
  import pytest
  import tensorflow
  from tensorflow_addons.layers.max_unpooling_2d import MaxUnpooling2D
label_desc: Use image node_id 10 for calling a global function with example usage: test_padding_valid_complex() without return types