code: def test_ar_do_correct_lags():
      train_data, test_data = get_ts_data(n_steps=80)
      ar = AutoRegImplementation(
          OperationParameters(**{"lag_1": 70, "lag_2": 80})
      )
      params = ar.get_params()
      old_params = deepcopy(params)
      ar.fit(train_data)
      new_params = ar.get_params()
      for lag in old_params.keys():
          assert lag in new_params.changed_parameters.keys()
          assert old_params.get(lag) != new_params.get(lag)
  
imports: from copy import deepcopy
  from typing import Optional
  import numpy
  import pandas
  import pytest
  from scipy import stats
  from sklearn.metrics import mean_absolute_error, mean_squared_error
  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.models.ts_implementations.arima import ARIMAImplementation
  from fedot.core.operations.evaluation.operation_implementations.models.ts_implementations.statsmodels import AutoRegImplementation
  from fedot.core.operations.operation_parameters import OperationParameters
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.pipelines.ts_wrappers import in_sample_ts_forecast, out_of_sample_ts_forecast
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.tasks import Task, TaskTypesEnum, TsForecastingParams
  from fedot.core.utils import fedot_project_root
  from fedot.utilities.synth_dataset_generator import generate_synthetic_data
label_desc: Use image node_id 11 for calling a global function with example usage: test_ar_do_correct_lags() without return types