code: def test_pipeline_tuner_correct(
      data_fixture, pipelines, loss_functions, request, tuner
  ):
      """Test all tuners for pipeline"""
      data = request.getfixturevalue(data_fixture)
      cvs = [None, 2]
  
      for pipeline in pipelines:
          for loss_function in loss_functions:
              for cv in cvs:
                  pipeline_tuner, tuned_pipeline = run_pipeline_tuner(
                      tuner=tuner,
                      train_data=data,
                      pipeline=pipeline,
                      loss_function=loss_function,
                      cv=cv,
                  )
                  assert pipeline_tuner.obtained_metric is not None
                  assert tuned_pipeline is not None
                  assert not tuned_pipeline.is_fitted
  
imports: import os
  from time import time
  import pytest
  from fedot.core.repository.dataset_types import DataTypesEnum
  from golem.core.tuning.hyperopt_tuner import get_node_parameters_for_hyperopt
  from golem.core.tuning.iopt_tuner import IOptTuner
  from golem.core.tuning.optuna_tuner import OptunaTuner
  from golem.core.tuning.sequential import SequentialTuner
  from golem.core.tuning.simultaneous import SimultaneousTuner
  from golem.utilities.data_structures import ensure_wrapped_in_sequence
  from hyperopt import hp
  from hyperopt.pyll.stochastic import sample
  from examples.simple.time_series_forecasting.ts_pipelines import ts_complex_ridge_smoothing_pipeline, ts_glm_pipeline
  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.statsmodels import GLMImplementation
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.pipelines.tuning.search_space import PipelineSearchSpace
  from fedot.core.pipelines.tuning.tuner_builder import TunerBuilder
  from fedot.core.repository.metrics_repository import RegressionMetricsEnum, ClassificationMetricsEnum
  from fedot.core.repository.tasks import Task, TaskTypesEnum
  from fedot.core.utils import fedot_project_root, NESTED_PARAMS_LABEL
  from test.unit.multimodal.data_generators import get_single_task_multimodal_tabular_data, get_multimodal_pipeline
  from test.unit.tasks.test_forecasting import get_ts_data
label_desc: Use image node_id 24 for calling a global function with example usage: test_pipeline_tuner_correct(data_fixture, pipelines, loss_functions, request, tuner) without return types