code: def DISABLED_testFromGeneratorsRunningInParallel(self):
      self.skipTest("b/67868766")
      num_parallel_iterators = 3
  
      # Define shared state that multiple iterator instances will access to
      # demonstrate their concurrent activity.
      lock = threading.Lock()
      condition = threading.Condition(lock)
      next_ticket = [0]  # GUARDED_BY(lock)
  
      def generator():
          # NOTE(mrry): We yield one element before the barrier, because
          # the current implementation of `Dataset.interleave()` must
          # fetch one element from each incoming dataset to start the
          # prefetching.
          yield 0
  
          # Define a barrier that `num_parallel_iterators` iterators must enter
          # before any can proceed. Demonstrates that multiple iterators may be
          # active at the same time.
          condition.acquire()
          ticket = next_ticket[0]
          next_ticket[0] += 1
          if ticket == num_parallel_iterators - 1:
              # The last iterator to join the barrier notifies the others.
              condition.notify_all()
          else:
              # Wait until the last iterator enters the barrier.
              while next_ticket[0] < num_parallel_iterators:
                  condition.wait()
          condition.release()
  
          yield 1
  
      # As in `testFromMultipleConcurrentGenerators()`, we use a combination of
      # `Dataset.interleave()` and `Dataset.prefetch()` to cause multiple
      # iterators to be active concurrently.
      def interleave_fn(_):
          return dataset_ops.Dataset.from_generator(
              generator, output_types=dtypes.int64, output_shapes=[]
          ).prefetch(2)
  
      dataset = dataset_ops.Dataset.range(
          num_parallel_iterators
      ).interleave(
          interleave_fn,
          cycle_length=num_parallel_iterators,
          block_length=1,
      )
      get_next = self.getNext(dataset)
  
      for elem in [0, 1]:
          for _ in range(num_parallel_iterators):
              self.assertAllEqual(elem, self.evaluate(get_next()))
      with self.assertRaises(errors.OutOfRangeError):
          self.evaluate(get_next())
  
imports: import threading
  from absl.testing import parameterized
  import numpy
  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.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_spec
  from tensorflow.python.ops import script_ops
  from tensorflow.python.ops import sparse_ops
  from tensorflow.python.ops.ragged import ragged_factory_ops
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.platform import test
label_desc: Use image node_id 7 for calling the FromGeneratorTest obj's underlying member method code with example usage: obj.DISABLED_testFromGeneratorsRunningInParallel() and returns: dataset_ops