code: def testComplexGpu(self):
      if not test_util.is_gpu_available():
          self.skipTest("No GPU available")
  
      np.random.seed(7)
      with test_util.force_gpu():
          for shape in (2,), (3,), (2, 3), (3, 2), (4, 3, 2):
              for dtype in [np.complex64, np.complex128]:
                  data = np.random.randn(*shape).astype(dtype)
                  # Convert data to a single tensorflow tensor
                  x = constant_op.constant(data)
                  # Unstack into a list of tensors
                  cs = array_ops_stack.unstack(x, num=shape[0])
                  self.assertEqual(type(cs), list)
                  self.assertEqual(len(cs), shape[0])
                  cs = [self.evaluate(c) for c in cs]
                  self.assertAllEqual(cs, data)
  
imports: import numpy
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.ops import gradient_checker_v2
  from tensorflow.python.platform import test
label_desc: Use image node_id 16 for calling the UnstackOpTest obj's underlying member method code with example usage: obj.testComplexGpu() without return types