text: # Copyright 2020 - 2021 MONAI Consortium
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #     http://www.apache.org/licenses/LICENSE-2.0
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  
  import unittest
  
  import numpy as np
  from parameterized import parameterized
  
  from monai.transforms import AsChannelLastd
  
  TEST_CASE_1 = [{"keys": ["image", "label", "extra"], "channel_dim": 0}, (2, 3, 4, 1)]
  
  TEST_CASE_2 = [{"keys": ["image", "label", "extra"], "channel_dim": 1}, (1, 3, 4, 2)]
  
  TEST_CASE_3 = [{"keys": ["image", "label", "extra"], "channel_dim": 3}, (1, 2, 3, 4)]
  
  
  class TestAsChannelLastd(unittest.TestCase):
      @parameterized.expand([TEST_CASE_1, TEST_CASE_2, TEST_CASE_3])
      def test_shape(self, input_param, expected_shape):
          test_data = {
              "image": np.random.randint(0, 2, size=[1, 2, 3, 4]),
              "label": np.random.randint(0, 2, size=[1, 2, 3, 4]),
              "extra": np.random.randint(0, 2, size=[1, 2, 3, 4]),
          }
          result = AsChannelLastd(**input_param)(test_data)
          self.assertTupleEqual(result["image"].shape, expected_shape)
          self.assertTupleEqual(result["label"].shape, expected_shape)
          self.assertTupleEqual(result["extra"].shape, expected_shape)
  
  
  if __name__ == "__main__":
      unittest.main()
  