code: def __init__(
      self,
      name,
      spec,
      counter_factory,
      sampler,
      consumers,
      operation_cls,
      keyed_state_backend,
      operator_state_backend,
  ):
      self._keyed_state_backend = keyed_state_backend
      self._reusable_windowed_value = windowed_value.create(
          None, -1, None, None
      )
      super(StatefulFunctionOperation, self).__init__(
          name,
          spec,
          counter_factory,
          sampler,
          consumers,
          operation_cls,
          operator_state_backend,
      )
  
imports: import abc
  from abc import abstractmethod
  from typing import Iterable, Any, Dict, List
  from apache_beam.runners.worker.bundle_processor import TimerInfo, DataOutputOperation
  from apache_beam.runners.worker.operations import Operation
  from apache_beam.utils import windowed_value
  from apache_beam.utils.windowed_value import WindowedValue
  from pyflink.common.constants import DEFAULT_OUTPUT_TAG
  from pyflink.fn_execution.flink_fn_execution_pb2 import UserDefinedDataStreamFunction
  from pyflink.fn_execution.table.operations import BundleOperation
  from pyflink.fn_execution.profiler import Profiler
label_desc: Use image node_id 1 to create a new StatefulFunctionOperation object from inherited base classes: FunctionOperation with example: obj = StatefulFunctionOperation(name, spec, counter_factory, sampler, consumers, operation_cls, keyed_state_backend, operator_state_backend)