parameters: (self, name=None)
docstring: Get next element from underlying iterator.
  
      If there is no data left, a list of dummy tensors with possible batch
      dimensions set to 0 will be returned.
  
      Args:
        name: not used.
  
      Returns:
        A boolean tensor indicates whether there is any data in next element and
        the real data as the next element or a list of dummy tensors if no data
        left.
docstring_summary: Get next element from underlying iterator.
docstring_tokens: Get next element from underlying iterator .
function: def get_next_as_list(self, name=None):
      """Get next element from underlying iterator.
  
      If there is no data left, a list of dummy tensors with possible batch
      dimensions set to 0 will be returned.
  
      Args:
        name: not used.
  
      Returns:
        A boolean tensor indicates whether there is any data in next element and
        the real data as the next element or a list of dummy tensors if no data
        left.
      """
      del name
      with ops.device(self._worker):
        data_list = self._iterator.get_next_as_optional()
        result = []
        for i, data in enumerate(data_list):
          # Place the condition op in the same device as the data so the data
          # doesn't need to be sent back to the worker.
          with ops.device(self._devices[i]):
            # As MultiDeviceIterator will fetch data in order, so we only need to
            # check if the first replica has value to see whether there is data
            # left for this single worker.
            if i == 0:
              worker_has_value = data.has_value()
  
            # pylint: disable=unnecessary-lambda
            # pylint: disable=cell-var-from-loop
            real_data = control_flow_ops.cond(
                data.has_value(),
                lambda: data.get_value(),
                lambda: _dummy_tensor_fn(data.value_structure))
            result.append(real_data)
            # pylint: enable=cell-var-from-loop
            # pylint: enable=unnecessary-lambda
  
        return worker_has_value, result
function_tokens: def get_next_as_list ( self , name = None ) : del name with ops . device ( self . _worker ) : data_list = self . _iterator . get_next_as_optional ( ) result = [ ] for i , data in enumerate ( data_list ) : # Place the condition op in the same device as the data so the data # doesn't need to be sent back to the worker. with ops . device ( self . _devices [ i ] ) : # As MultiDeviceIterator will fetch data in order, so we only need to # check if the first replica has value to see whether there is data # left for this single worker. if i == 0 : worker_has_value = data . has_value ( ) # pylint: disable=unnecessary-lambda # pylint: disable=cell-var-from-loop real_data = control_flow_ops . cond ( data . has_value ( ) , lambda : data . get_value ( ) , lambda : _dummy_tensor_fn ( data . value_structure ) ) result . append ( real_data ) # pylint: enable=cell-var-from-loop # pylint: enable=unnecessary-lambda return worker_has_value , result