code: def model_metrics_info(class_name, y_true, y_pred):
      print("\n", f"#test_eval_strategy_{class_name}")
      print(classification_report(y_true, y_pred))
      print("Test model accuracy: ", accuracy_score(y_true, y_pred))
  
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 2 for calling a global function with example usage: model_metrics_info(class_name, y_true, y_pred) without return types