class_docstr: An iterator over multiple devices.
class_docstr_tok: ["An","iterator","over","multiple","devices","."]
code: def get_next_as_optional(self):
      result = []
      for i, device in enumerate(self._devices):
          with ops.device(device):
              result.append(
                  self._device_iterators[i].get_next_as_optional()
              )
      return result
  
imports: from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.data.ops import iterator_ops
  from tensorflow.python.data.ops import options
  from tensorflow.python.data.ops import prefetch_op
  from tensorflow.python.data.util import structure
  from tensorflow.python.eager import context
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import composite_tensor
  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.framework import type_spec
  from tensorflow.python.framework import type_utils
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import control_flow_ops
  from tensorflow.python.ops import functional_ops
  from tensorflow.python.ops import gen_dataset_ops
  from tensorflow.python.ops import resource_variable_ops
label_desc: Use image node_id 3 for calling the MultiDeviceIterator obj's underlying member method code with example usage: obj.get_next_as_optional() and returns: result