code: def testContains(self):
      with test_util.use_gpu():
          shape = (3, 5, 7)
          target = (2, 3, 4)
          value = np.random.randint(1000000, size=shape)
          iterations = 10
          value_set = set(
              tuple(
                  value[i : i + 2, j : j + 3, k : k + 4].ravel()
              )  # pylint: disable=g-complex-comprehension
              for i in range(2)
              for j in range(3)
              for k in range(4)
          )
          test_seeds = [
              tuple(map(lambda x, i=i: x + 1 * i, t))
              for (i, t) in enumerate((1, 2) for _ in range(iterations))
          ]
  
          # Check that the result is valid by making sure that it is one of all
          # possible values for randomly cropping `value` with `target` shape.
          for seed in test_seeds:
              crop = random_crop_ops.stateless_random_crop(
                  value, size=target, seed=seed
              )
              y = self.evaluate(crop)
              self.assertAllEqual(y.shape, target)
              self.assertIn(tuple(y.ravel()), value_set)
  
file_path: tensorflow-upstream/tensorflow/python/kernel_tests/random/random_crop_test.py
imports: import numpy
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import random_crop_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 2 for calling the StatelessRandomCropTest obj's underlying member method code with example usage: obj.testContains() without return types