class_docstr: Inputs created from dataset function.
class_docstr_tok: ["Inputs","created","from","dataset","function","."]
code: def _get_iterator(self):
      iterators = _create_iterators_per_worker(
          self._datasets, self._input_workers, self._options
      )
      cardinality = input_lib._cardinality(
          self._datasets[0]
      )  # pylint: disable=protected-access
      iterator = DistributedIteratorV1(
          self._input_workers,
          iterators,
          self._strategy,
          cardinality,
          self._enable_get_next_as_optional,
      )
      iterator._element_spec = (
          self._element_spec
      )  # pylint: disable=protected-access
  
      # When async eager is enabled, sometimes the iterator may not finish
      # initialization before passing to a multi device function, add a sync point
      # here to make sure all underlying iterators are initialized.
      if context.executing_eagerly():
          context.async_wait()
  
      return iterator
  
imports: from tensorflow.python.data.experimental.ops import cardinality
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.data.ops import multi_device_iterator_ops
  from tensorflow.python.data.ops import optional_ops
  from tensorflow.python.distribute import input_lib
  from tensorflow.python.eager import context
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import control_flow_ops
  from tensorflow.python.types import data
  from tensorflow.python.util.deprecation import deprecated
label_desc: Use image node_id 3 for calling the DistributedDatasetsFromFunctionV1 obj's underlying member method code with example usage: obj._get_iterator() and returns: iterator