code: def testTuple(self):
      def init_fn(_):
          return np.array([], dtype=np.int64), np.int64(0)
  
      def reduce_fn(state, value):
          s1, s2 = state
          v1, v2 = value
          return array_ops.concat([s1, [v1]], 0), s2 + v2
  
      def finalize_fn(s1, s2):
          return s1, s2
  
      reducer = grouping.Reducer(init_fn, reduce_fn, finalize_fn)
      dataset = dataset_ops.Dataset.zip(
          (dataset_ops.Dataset.range(10), dataset_ops.Dataset.range(10))
      ).apply(
          grouping.group_by_reducer(lambda x, y: np.int64(0), reducer)
      )
      get_next = self.getNext(dataset)
      x, y = self.evaluate(get_next())
      self.assertAllEqual(x, np.asarray([x for x in range(10)]))
      self.assertEqual(y, 45)
  
imports: from absl.testing import parameterized
  import numpy
  from tensorflow.python.data.experimental.ops import grouping
  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.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.framework import tensor_shape
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 9 for calling the GroupByReducerTest obj's underlying member method code with example usage: obj.testTuple() and returns: np,  np, array_ops,  unknown, s1,  s2