code: def test_multi_target_regression_composing_correct(data_setup):
      # Load simple dataset for multi-target
      train, test, _, _ = data_setup
  
      problem = "regression"
      timeout = 0.1
      simple_composer_params = get_simple_composer_params()
  
      automl_model = Fedot(
          problem=problem, timeout=timeout, **simple_composer_params
      )
      automl_model.fit(train)
      predicted_array = automl_model.predict(test)
      assert predicted_array is not None
  
imports: import numpy
  import pytest
  from sklearn.datasets import make_regression
  from sklearn.metrics import mean_squared_error
  from fedot import Fedot
  from fedot.core.data.data import InputData
  from fedot.core.data.data_split import train_test_data_setup
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.tasks import Task, TaskTypesEnum
  from test.unit.common_tests import is_predict_ignores_target
  from test.unit.composer.test_metrics import data_setup
label_desc: Use image node_id 8 for calling a global function with example usage: test_multi_target_regression_composing_correct(data_setup) without return types