code: def _test_unbatch_combinations():
      cases = [
          (
              tensor.TensorSpec([32], dtypes.float32),
              tensor.TensorSpec([], dtypes.float32),
          ),
          (
              tensor.TensorSpec([None], dtypes.float32),
              tensor.TensorSpec([], dtypes.float32),
          ),
          (
              sparse_tensor.SparseTensorSpec(
                  [32, None], dtypes.float32
              ),
              sparse_tensor.SparseTensorSpec([None], dtypes.float32),
          ),
          (
              sparse_tensor.SparseTensorSpec([None, 4], dtypes.float32),
              sparse_tensor.SparseTensorSpec([4], dtypes.float32),
          ),
          (
              ragged_tensor.RaggedTensorSpec(
                  [32, None, None], dtypes.float32, 2
              ),
              ragged_tensor.RaggedTensorSpec(
                  [None, None], dtypes.float32, 1
              ),
          ),
          (
              ragged_tensor.RaggedTensorSpec(
                  [None, None, None], dtypes.float32, 2
              ),
              ragged_tensor.RaggedTensorSpec(
                  [None, None], dtypes.float32, 1
              ),
          ),
          (
              {
                  "a": tensor.TensorSpec([128], dtypes.float32),
                  "b": (
                      sparse_tensor.SparseTensorSpec(
                          [128, 2, 2], dtypes.int32
                      ),
                      tensor.TensorSpec([None], dtypes.string),
                  ),
              },
              {
                  "a": tensor.TensorSpec([], dtypes.float32),
                  "b": (
                      sparse_tensor.SparseTensorSpec(
                          [2, 2], dtypes.int32
                      ),
                      tensor.TensorSpec([], dtypes.string),
                  ),
              },
          ),
      ]
  
      def reduce_fn(x, y):
          element_structure, expected_unbatched_structure = y
          return x + combinations.combine(
              element_structure=element_structure,
              expected_unbatched_structure=expected_unbatched_structure,
          )
  
      return functools.reduce(reduce_fn, cases, [])
  
imports: import collections
  import dataclasses
  import functools
  from absl.testing import parameterized
  import numpy
  import wrapt
  from tensorflow.python.data.kernel_tests import test_base
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.data.util import nest
  from tensorflow.python.data.util import structure
  from tensorflow.python.framework import combinations
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.framework import tensor
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import tensor_array_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.ops.ragged import ragged_factory_ops
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.ops.ragged import ragged_tensor_value
  from tensorflow.python.platform import test
  from tensorflow.python.util.compat import collections_abc
label_desc: Use image node_id 9 for calling a global function with example usage: _test_unbatch_combinations() and returns: functools, unknown