code: def feature_dict_to_list(config: ModelConfigDict) -> ModelConfigDict:
      # This works because Python dicts are order-preserving, so we do not need to
      # do anything special to map from a key in the dict to an index in a list
      input_features_list = []
      for feature in config[INPUT_FEATURES].values():
          input_features_list.append(feature)
  
      output_features_list = []
      for feature in config[OUTPUT_FEATURES].values():
          output_features_list.append(feature)
  
      config = copy.copy(config)
      config[INPUT_FEATURES] = input_features_list
      config[OUTPUT_FEATURES] = output_features_list
      return config
  
imports: import copy
  import dataclasses
  import json
  import logging
  import os
  import warnings
  from typing import Any, Dict
  from ludwig.api_annotations import DeveloperAPI
  from ludwig.constants import AUTO, COMBINED, EXECUTOR, GOAL, GRID_SEARCH, HYPEROPT, INPUT_FEATURES, LOSS, MAX_CONCURRENT_TRIALS, METRIC, MINIMIZE, NAME, NUM_SAMPLES, OUTPUT_FEATURES, PARAMETERS, PREPROCESSING, RAY, SPACE, SPLIT, TYPE, VALIDATION
  from ludwig.globals import HYPEROPT_STATISTICS_FILE_NAME
  from ludwig.hyperopt.results import HyperoptResults, TrialResults
  from ludwig.types import HyperoptConfigDict, ModelConfigDict
  from ludwig.utils.data_utils import save_json
  from ludwig.utils.misc_utils import get_class_attributes, get_from_registry, merge_dict, set_default_value, set_default_values
  from ludwig.utils.print_utils import print_boxed
label_desc: Use image node_id 8 for calling a global function with example usage: feature_dict_to_list(config) and returns: config