code: def test_eval_strategy_logreg(data_setup):
      data_set = data_setup
      train, test = train_test_data_setup(data=data_set)
      test_skl_model = LogisticRegression(
          C=10.0,
          random_state=1,
          solver="liblinear",
          max_iter=10000,
          verbose=0,
      )
      test_skl_model.fit(train.features, train.target)
      expected_result = test_skl_model.predict(test.features)
  
      test_model_node = PipelineNode(operation_type="logit")
      test_model_node.fit(input_data=train)
      actual_result = test_model_node.predict(input_data=test)
  
      assert len(actual_result.predict) == len(expected_result)
  
imports: import numpy
  import pytest
  from golem.core.dag.linked_graph_node import LinkedGraphNode
  from sklearn.datasets import load_iris
  from sklearn.linear_model import LogisticRegression
  from sklearn.metrics import accuracy_score, classification_report
  from fedot.core.data.data import InputData
  from fedot.core.data.data_split import train_test_data_setup
  from fedot.core.operations.model import Model
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.tasks import Task, TaskTypesEnum
  from fedot.core.utils import DEFAULT_PARAMS_STUB, NESTED_PARAMS_LABEL
label_desc: Use image node_id 4 for calling a global function with example usage: test_eval_strategy_logreg(data_setup) without return types