code: def get_all_int_categorical_strategy(
      self, current_models, total_time_limit
  ):
      return self.get_categorical_strategy(
          current_models,
          PreprocessingTuner.CATEGORICALS_ALL_INT,
          total_time_limit,
      )
  
imports: import copy
  import json
  import logging
  import os
  import numpy
  import pandas
  from sklearn.preprocessing import OneHotEncoder
  from supervised.algorithms.catboost import catboost_eval_metric
  from supervised.algorithms.lightgbm import lightgbm_eval_metric
  from supervised.algorithms.registry import BINARY_CLASSIFICATION, MULTICLASS_CLASSIFICATION, REGRESSION, AlgorithmsRegistry
  from supervised.algorithms.xgboost import xgboost_eval_metric
  from supervised.preprocessing.label_encoder import LabelEncoder
  from supervised.preprocessing.preprocessing_categorical import PreprocessingCategorical
  from supervised.tuner.hill_climbing import HillClimbing
  from supervised.tuner.preprocessing_tuner import PreprocessingTuner
  from supervised.tuner.random_parameters import RandomParameters
  from supervised.utils.config import LOG_LEVEL
  from supervised.utils.utils import dump_data, load_data
label_desc: Use image node_id 21 for calling the MljarTuner obj's underlying member method code with example usage: obj.get_all_int_categorical_strategy(current_models, total_time_limit) and returns: self