code: def expected_values() -> Dict[str, Dict[str, float]]:
      with open(
          fedot_project_root()
          / "test/data/expected_metric_values.json",
          "r",
      ) as f:
          return json.load(f)
  
imports: import json
  import sys
  from itertools import product
  from typing import Callable, Dict, Tuple, Union
  import numpy
  import pandas
  import pytest
  from sklearn.datasets import load_breast_cancer, load_diabetes, load_linnerud, load_wine
  from fedot.core.composer.metrics import QualityMetric, ROCAUC
  from fedot.core.data.data import InputData, OutputData
  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.metrics_repository import ClassificationMetricsEnum, ComplexityMetricsEnum, MetricsRepository, RegressionMetricsEnum, TimeSeriesForecastingMetricsEnum
  from fedot.core.repository.tasks import Task, TaskTypesEnum, TsForecastingParams
  from fedot.core.utils import fedot_project_root, set_random_seed
label_desc: Use image node_id 5 for calling a global function with example usage: expected_values() and returns: json