docstr: Calculates and updates a few key information to the config object. Logic happens in _update_config. This is
  just a wrapper to make it accessible from outside and not break current apis.
  
  Args:
      config (DictConfig): The config object
  
  Returns:
      InferredConfig: The updated config object
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code: def update_config(self, config) -> InferredConfig:
      """Calculates and updates a few key information to the config object. Logic happens in _update_config. This is
      just a wrapper to make it accessible from outside and not break current apis.
  
      Args:
          config (DictConfig): The config object
  
      Returns:
          InferredConfig: The updated config object
      """
      if self.cache_mode is self.CACHE_MODES.INFERENCE:
          warnings.warn(
              "Cannot update config in inference mode. Returning the cached config"
          )
          return self._inferred_config
      else:
          return self._update_config(config)
  
imports: import re
  import warnings
  from enum import Enum
  from pathlib import Path
  from typing import Dict, Iterable, List, Optional, Tuple, Union
  import joblib
  import numpy
  import pandas
  import pytorch_lightning
  import torch
  from omegaconf import DictConfig
  from pandas import DataFrame, DatetimeTZDtype, to_datetime
  from pandas.tseries import offsets
  from pandas.tseries.frequencies import to_offset
  from sklearn.base import TransformerMixin, copy
  from sklearn.preprocessing import FunctionTransformer, LabelEncoder, PowerTransformer, QuantileTransformer, StandardScaler
  from torch.utils.data import DataLoader, Dataset
  from pytorch_tabular.config import InferredConfig
  from pytorch_tabular.utils import get_logger
  from .categorical_encoders import OrdinalEncoder
label_desc: Use image node_id 15 for calling the TabularDatamodule obj's underlying member method code with example usage: obj.update_config(config) and returns: self, self