code: def _test_hash_combinations():
      cases = [
          (
              "Tensor",
              lambda: constant_op.constant(37.0),
              lambda: constant_op.constant(42.0),
              lambda: constant_op.constant([5]),
          ),
          (
              "TensorArray",
              lambda: tensor_array_ops.TensorArray(
                  dtype=dtypes.float32, element_shape=(3,), size=0
              ),
              lambda: tensor_array_ops.TensorArray(
                  dtype=dtypes.float32, element_shape=(3,), size=0
              ),
              lambda: tensor_array_ops.TensorArray(
                  dtype=dtypes.int32, element_shape=(), size=0
              ),
          ),
          (
              "SparseTensor",
              lambda: sparse_tensor.SparseTensor(
                  indices=[[3, 4]], values=[-1], dense_shape=[4, 5]
              ),
              lambda: sparse_tensor.SparseTensor(
                  indices=[[1, 2]], values=[42], dense_shape=[4, 5]
              ),
              lambda: sparse_tensor.SparseTensor(
                  indices=[[3]], values=[-1], dense_shape=[5]
              ),
          ),
          (
              "Nested",
              lambda: {
                  "a": constant_op.constant(37.0),
                  "b": constant_op.constant([1, 2, 3]),
              },
              lambda: {
                  "a": constant_op.constant(42.0),
                  "b": constant_op.constant([4, 5, 6]),
              },
              lambda: {
                  "a": constant_op.constant([1, 2, 3]),
                  "b": constant_op.constant(37.0),
              },
          ),
      ]
  
      def reduce_fn(x, y):
          name, value1_fn, value2_fn, value3_fn = y
          return x + combinations.combine(
              value1_fn=combinations.NamedObject(
                  "value1_fn.{}".format(name), value1_fn
              ),
              value2_fn=combinations.NamedObject(
                  "value2_fn.{}".format(name), value2_fn
              ),
              value3_fn=combinations.NamedObject(
                  "value3_fn.{}".format(name), value3_fn
              ),
          )
  
      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 5 for calling a global function with example usage: _test_hash_combinations() and returns: functools, unknown