code: # Copyright 2020 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 SqueezeDimd
  
  
  TEST_CASE_1 = [
      {"keys": ["img", "seg"], "dim": None},
      {"img": np.random.rand(1, 2, 1, 3), "seg": np.random.randint(0, 2, size=[1, 2, 1, 3])},
      (2, 3),
  ]
  
  TEST_CASE_2 = [
      {"keys": ["img", "seg"], "dim": 2},
      {"img": np.random.rand(1, 2, 1, 8, 16), "seg": np.random.randint(0, 2, size=[1, 2, 1, 8, 16])},
      (1, 2, 8, 16),
  ]
  
  TEST_CASE_3 = [
      {"keys": ["img", "seg"], "dim": -1},
      {"img": np.random.rand(1, 1, 16, 8, 1), "seg": np.random.randint(0, 2, size=[1, 1, 16, 8, 1])},
      (1, 1, 16, 8),
  ]
  
  TEST_CASE_4 = [
      {"keys": ["img", "seg"]},
      {"img": np.random.rand(1, 2, 1, 3), "seg": np.random.randint(0, 2, size=[1, 2, 1, 3])},
      (2, 3),
  ]
  
  TEST_CASE_5 = [
      {"keys": ["img", "seg"], "dim": -2},
      {"img": np.random.rand(1, 1, 16, 8, 1), "seg": np.random.randint(0, 2, size=[1, 1, 16, 8, 1])},
  ]
  
  TEST_CASE_6 = [
      {"keys": ["img", "seg"], "dim": 0.5},
      {"img": np.random.rand(1, 1, 16, 8, 1), "seg": np.random.randint(0, 2, size=[1, 1, 16, 8, 1])},
  ]
  
  
  class TestSqueezeDim(unittest.TestCase):
      @parameterized.expand([TEST_CASE_1, TEST_CASE_2, TEST_CASE_3, TEST_CASE_4])
      def test_shape(self, input_param, test_data, expected_shape):
          result = SqueezeDimd(**input_param)(test_data)
          self.assertTupleEqual(result["img"].shape, expected_shape)
          self.assertTupleEqual(result["seg"].shape, expected_shape)
  
      @parameterized.expand([TEST_CASE_5, TEST_CASE_6])
      def test_invalid_inputs(self, input_param, test_data):
          with self.assertRaises(AssertionError):
              result = SqueezeDimd(**input_param)(test_data)
  
  
  if __name__ == "__main__":
      unittest.main()
  
apis: numpy.random.randint numpy.random.rand