code: def testMultipleInitializationsGraph(self):
      dataset1 = dataset_ops.Dataset.range(1000)
      dataset2 = dataset_ops.Dataset.range(1000)
      dataset = dataset_ops.Dataset.zip((dataset1, dataset2))
      multi_device_iterator = (
          multi_device_iterator_ops.MultiDeviceIterator(
              dataset,
              [self._devices[1], self._devices[2]],
              prefetch_buffer_size=4,
          )
      )
      elem_on_1, elem_on_2 = multi_device_iterator.get_next()
  
      for _ in range(5):
          self.evaluate(multi_device_iterator.initializer)
          self.assertEqual(
              [(0, 0), (1, 1)], self.evaluate([elem_on_1, elem_on_2])
          )
  
imports: from absl.testing import parameterized
  import numpy
  from tensorflow.python.data.experimental.ops import testing
  from tensorflow.python.data.kernel_tests import test_base
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.data.ops import from_generator_op
  from tensorflow.python.data.ops import multi_device_iterator_ops
  from tensorflow.python.data.ops import options
  from tensorflow.python.eager import cancellation
  from tensorflow.python.eager import context
  from tensorflow.python.eager import def_function
  from tensorflow.python.eager import executor
  from tensorflow.python.framework import combinations
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_spec
  from tensorflow.python.ops import data_flow_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 9 for calling the MultiDeviceIteratorTest obj's underlying member method code with example usage: obj.testMultipleInitializationsGraph() without return types