code: def check_and_update_params(self):
      n_jobs = self.params.get("n_jobs")
      self.params.update(thread_count=n_jobs)
  
      use_best_model = self.params.get("use_best_model")
      early_stopping_rounds = self.params.get("early_stopping_rounds")
      use_eval_set = self.params.get("use_eval_set")
  
      if use_best_model or early_stopping_rounds and not use_eval_set:
          self.params.update(
              use_best_model=False, early_stopping_rounds=False
          )
  
imports: import os
  from typing import Optional
  import numpy
  import pandas
  from catboost import CatBoostClassifier, CatBoostRegressor, Pool
  from matplotlib import pyplot
  from fedot.core.data.data import InputData
  from fedot.core.data.data_split import train_test_data_setup
  from fedot.core.operations.evaluation.operation_implementations.implementation_interfaces import ModelImplementation
  from fedot.core.operations.operation_parameters import OperationParameters
  from fedot.core.utils import default_fedot_data_dir
label_desc: Use image node_id 4 for calling the FedotCatBoostImplementation obj's underlying member method code with example usage: obj.check_and_update_params() without return types