code: def turn_on_off_feature_column_info(
      data_processors: Dict,
      flag: bool,
  ):
      """
      Turn on or off returning feature column information in data processors.
      Since feature column information is not always required in training models,
      we optionally turn this flag on or off.
  
      Parameters
      ----------
      data_processors
          The data processors.
      flag
          True/False
      """
      for per_modality_processors in data_processors.values():
          for per_model_processor in per_modality_processors:
              # label processor doesn't have requires_column_info.
              if hasattr(per_model_processor, "requires_column_info"):
                  per_model_processor.requires_column_info = flag
  
imports: import copy
  import logging
  import os
  import warnings
  from typing import Dict, List, Optional, Tuple, Union
  import pandas
  from omegaconf import DictConfig, OmegaConf
  from torch import nn
  from autogluon.core.utils import default_holdout_frac, generate_train_test_split_combined
  from autogluon.core.utils.loaders import load_pd
  from ..constants import BINARY, CATEGORICAL, DEFAULT_SHOT, DOCUMENT, FEW_SHOT, IMAGE, IMAGE_PATH, LABEL, MMLAB_MODELS, MULTICLASS, NER, NER_ANNOTATION, NER_TEXT, NUMERICAL, OVD, REGRESSION, ROIS, SAM, SEMANTIC_SEGMENTATION_IMG, TEXT, TEXT_NER
  from ..data import CategoricalProcessor, DocumentProcessor, ImageProcessor, LabelProcessor, MixupModule, MMDetProcessor, MMOcrProcessor, MultiModalFeaturePreprocessor, NerLabelEncoder, NerProcessor, NumericalProcessor, OVDProcessor, SemanticSegImageProcessor, TextProcessor
  from ..data.infer_types import is_image_column
label_desc: Use image node_id 5 for calling a global function with example usage: turn_on_off_feature_column_info(data_processors, flag) without return types