code: def testUnbatchDatasetWithDenseSparseAndRaggedTensor(self):
      st = sparse_tensor.SparseTensorValue(
          indices=[[i, i] for i in range(10)],
          values=list(range(10)),
          dense_shape=[10, 10],
      )
      rt = ragged_factory_ops.constant_value(
          [
              [[0]],
              [[1]],
              [[2]],
              [[3]],
              [[4]],
              [[5]],
              [[6]],
              [[7]],
              [[8]],
              [[9]],
          ]
      )
      data = dataset_ops.Dataset.from_tensors((list(range(10)), st, rt))
      data = data.unbatch()
      data = data.batch(5)
      data = data.unbatch()
      expected_output = [
          (
              i,
              sparse_tensor.SparseTensorValue([[i]], [i], [10]),
              ragged_factory_ops.constant_value([[i]]),
          )
          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 6 for calling the UnbatchTest obj's underlying member method code with example usage: obj.testUnbatchDatasetWithDenseSparseAndRaggedTensor() without return types