code: def testUnbatchDatasetWithSparseTensor(self):
      st = sparse_tensor.SparseTensorValue(
          indices=[[i, i] for i in range(10)],
          values=list(range(10)),
          dense_shape=[10, 10],
      )
      data = dataset_ops.Dataset.from_tensors(st)
      data = data.unbatch()
      data = data.batch(5)
      data = data.unbatch()
      expected_output = [
          sparse_tensor.SparseTensorValue([[i]], [i], [10])
          for i in range(10)
      ]
      self.assertDatasetProduces(data, expected_output=expected_output)
  
imports: from absl.testing import parameterized
  import numpy
  from tensorflow.python.data.kernel_tests import checkpoint_test_base
  from tensorflow.python.data.kernel_tests import test_base
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.data.ops import options
  from tensorflow.python.framework import combinations
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import string_ops
  from tensorflow.python.ops.ragged import ragged_factory_ops
  from tensorflow.python.platform import test
  from tensorflow.python.util import compat
label_desc: Use image node_id 5 for calling the UnbatchTest obj's underlying member method code with example usage: obj.testUnbatchDatasetWithSparseTensor() without return types