code: def testIterPrefetch(self, prefetch):
      condition = threading.Condition()
      counter = variables.Variable(0)
  
      def count(x):
          counter.assign_add(1)
          return x
  
      num_batches = 8
      batch_size = 4
      total_elems = num_batches * batch_size
      prefetch_buffer_size = 2 if prefetch else 0
  
      inputs = np.arange(total_elems)
      dataset = dataset_ops.DatasetV2.from_tensor_slices(inputs)
      dataset = dataset.map(count)
  
      inputs_layout = Layout.batch_sharded(
          self.mesh, batch_dim=MESH_DIM_BATCH, rank=1
      )
  
      d_dataset = input_util.DTensorDataset(
          dataset=dataset,
          global_batch_size=batch_size,
          mesh=self.mesh,
          layouts=inputs_layout,
          batch_dim=MESH_DIM_BATCH,
          prefetch=prefetch_buffer_size if prefetch else None,
      )
  
      # Check nothing was prefetched before iterators were created.
      self.assertEqual(counter.numpy(), 0)
  
      # Check nothing was prefetched before the first iteration.
      d_iterator = iter(d_dataset)
      self.assertEqual(counter.numpy(), 0)
  
      # The number of elements that are expected to be fetched in each iteration.
      multiple = batch_size * (self.mesh.size // MESH_SIZE_BATCH)
  
      # Check the number of elements fetched upon for each batch.
      for i in range(num_batches):
          elem = next(d_iterator)
  
          with condition:
              count = min(
                  (i + prefetch_buffer_size) * multiple,
                  num_batches * multiple,
              )
              result = condition.wait_for(
                  lambda: counter.numpy() >= count, timeout=5
              )
          self.assertTrue(result)
  
          start_idx, end_idx = i * batch_size, (i + 1) * batch_size
          self.assertDTensorEqual(
              inputs[start_idx:end_idx], inputs_layout, elem
          )
  
imports: import contextlib
  import threading
  from absl.testing import parameterized
  import numpy
  from tensorflow.dtensor.python import api
  from tensorflow.dtensor.python import input_util
  from tensorflow.dtensor.python import layout
  from tensorflow.dtensor.python import mesh_util
  from tensorflow.dtensor.python.tests import test_util
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.eager.polymorphic_function import polymorphic_function
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors_impl
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import tensor_spec
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import stateless_random_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
label_desc: Use image node_id 14 for calling the DTensorDatasetTest obj's underlying member method code with example usage: obj.testIterPrefetch(prefetch) and returns: x