code: def run_feature_identification(
      self, input_table_spec: TableSpec
  ) -> Dict[str, NormalizationData]:
      # Run state feature identification
      state_preprocessing_options = PreprocessingOptions()
      state_features = [
          ffi.feature_id
          for ffi in self.model_manager.state_feature_config.float_feature_infos
      ]
      logger.info(
          f"Overriding state allowedlist_features: {state_features}"
      )
      assert len(state_features) > 0, "No state feature is specified"
      state_preprocessing_options = replace(
          state_preprocessing_options,
          allowedlist_features=state_features,
      )
  
      state_normalization_parameters = (
          identify_normalization_parameters(
              input_table_spec,
              InputColumn.STATE_FEATURES,
              state_preprocessing_options,
          )
      )
  
      return {
          NormalizationKey.STATE: NormalizationData(
              dense_normalization_parameters=state_normalization_parameters
          )
      }
  
file_path: ReAgent/reagent/model_managers/world_model_base.py
imports: import logging
  from dataclasses import replace
  from typing import Dict, Optional, Tuple
  from reagent.core.dataclasses import dataclass
  from reagent.core.parameters import NormalizationData, NormalizationKey
  from reagent.data.data_fetcher import DataFetcher
  from reagent.data.manual_data_module import ManualDataModule
  from reagent.preprocessing.batch_preprocessor import BatchPreprocessor
  from reagent.preprocessing.types import InputColumn
  from reagent.workflow.identify_types_flow import identify_normalization_parameters
  from reagent.workflow.types import Dataset, PreprocessingOptions, RewardOptions, TableSpec
label_desc: Use image node_id 2 for calling the WorldModelDataModule obj's underlying member method code with example usage: obj.run_feature_identification(input_table_spec) and returns: dict