docstr: Preprocessing training and validation data.
  This method is a placeholder for inheriting models to override with more complex functionality if needed.
docstr_tok: ["Preprocessing","training","and","validation","data",".","This","method","is","a","placeholder","for","inheriting","models","to","override","with","more","complex","functionality","if","needed","."]
code: def preprocess_fit(self, X, y, X_val=None, y_val=None, **kwargs):
      """
      Preprocessing training and validation data.
      This method is a placeholder for inheriting models to override with more complex functionality if needed.
      """
      X = self.preprocess(X=X, **kwargs)
      if X_val is not None:
          X_val = self.preprocess(X=X_val, **kwargs)
      return X, y, X_val, y_val
  
imports: import logging
  import os
  from typing import Dict, Optional
  import pandas
  from autogluon.common.features.types import R_CATEGORY, R_FLOAT, R_INT, R_OBJECT, S_IMAGE_PATH, S_TEXT, S_TEXT_AS_CATEGORY, S_TEXT_NGRAM, S_TEXT_SPECIAL
  from autogluon.common.utils.resource_utils import ResourceManager
  from autogluon.common.utils.try_import import try_import_autogluon_multimodal
  from autogluon.core.constants import BINARY, MULTICLASS, REGRESSION
  from autogluon.core.models import AbstractModel
label_desc: Use image node_id 6 for calling the MultiModalPredictorModel obj's underlying member method code with example usage: obj.preprocess_fit(X, y, X_val, y_val) and returns: X,  y,  X_val,  y_val