code: def testSimple(self):
      np.random.seed(7)
      for shape in (2,), (3,), (2, 3), (3, 2), (4, 3, 2):
          rank = len(shape)
          for axis in range(-rank, rank):
              for dtype in [
                  np.bool_,
                  np.float16,
                  np.float32,
                  np.float64,
                  np.uint8,
                  np.int32,
                  np.int64,
                  dtypes.float8_e5m2.as_numpy_dtype,
                  dtypes.float8_e4m3fn.as_numpy_dtype,
              ]:
                  data = self.randn(shape, dtype)
                  # Convert data to a single tensorflow tensor
                  x = constant_op.constant(data)
  
                  # Unstack into a list of tensors
                  ref = self.unstackReference(data, axis)
                  cs = array_ops_stack.unstack(x, axis=axis)
                  self.assertEqual(type(cs), list)
                  self.assertEqual(len(cs), shape[axis])
                  for k, c in enumerate(cs):
                      with self.subTest(
                          shape=shape, k=k, axis=axis, dtype=dtype
                      ):
                          self.assertAllEqual(ref[k], self.evaluate(c))
  
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 3 for calling the UnstackOpTest obj's underlying member method code with example usage: obj.testSimple() without return types