class_docstr: A connector that wraps around existing RLlib observation preprocessors.
  
  This includes:
  - OneHotPreprocessor for Discrete and Multi-Discrete spaces.
  - GenericPixelPreprocessor and AtariRamPreprocessor for Atari spaces.
  - TupleFlatteningPreprocessor and DictFlatteningPreprocessor for flattening
    arbitrary nested input observations.
  - RepeatedValuesPreprocessor for padding observations from RLlib Repeated
    observation space.
code: def transform(
      self, ac_data: AgentConnectorDataType
  ) -> AgentConnectorDataType:
      d = ac_data.data
      assert type(d) == dict, (
          "Single agent data must be of type Dict[str, TensorStructType] but is of "
          "type {}".format(type(d))
      )
  
      if SampleBatch.OBS in d:
          d[SampleBatch.OBS] = self._preprocessor.transform(
              d[SampleBatch.OBS]
          )
      if SampleBatch.NEXT_OBS in d:
          d[SampleBatch.NEXT_OBS] = self._preprocessor.transform(
              d[SampleBatch.NEXT_OBS]
          )
  
      return ac_data
  
file_path: ray/python/ray/rllib/connectors/agent/obs_preproc.py
imports: from typing import Any
  from ray.rllib.connectors.connector import AgentConnector, ConnectorContext
  from ray.rllib.connectors.registry import register_connector
  from ray.rllib.models.preprocessors import get_preprocessor, NoPreprocessor
  from ray.rllib.policy.sample_batch import SampleBatch
  from ray.rllib.utils.typing import AgentConnectorDataType
  from ray.util.annotations import PublicAPI
label_desc: Use image node_id 3 for calling the ObsPreprocessorConnector obj's underlying member method code with example usage: obj.transform(ac_data) and returns: ac_data