code: def test_eval_test(self):
      eval_t(
          queue=self.queue,
          backend=self.backend,
          config=self.configuration,
          metrics=[accuracy],
          seed=test.conftest.DEFAULT_SEED,
          num_run=1,
          scoring_functions=None,
          output_y_hat_optimization=False,
          include=None,
          exclude=None,
          disable_file_output=False,
          instance=self.dataset_name,
          port=self.port,
          additional_components=dict(),
      )
      return_value = read_queue(self.queue)
      self.assertEqual(len(return_value), 1)
      self.assertAlmostEqual(
          return_value[0]["loss"], 0.07999999999999996
      )
      self.assertEqual(return_value[0]["status"], StatusType.SUCCESS)
      self.assertNotIn(
          "bac_metric", return_value[0]["additional_run_info"]
      )
  
imports: import copy
  import json
  import logging.handlers
  import multiprocessing
  import os
  import shutil
  import sys
  import tempfile
  import numpy
  from smac.tae import StatusType
  from autosklearn.automl_common.common.utils.backend import Backend
  from autosklearn.constants import BINARY_CLASSIFICATION, MULTICLASS_CLASSIFICATION, MULTILABEL_CLASSIFICATION, REGRESSION
  from autosklearn.evaluation.test_evaluator import TestEvaluator, eval_t
  from autosklearn.evaluation.util import read_queue
  from autosklearn.metrics import accuracy, balanced_accuracy, f1_macro, r2
  from autosklearn.util.pipeline import get_configuration_space
  import unittest
  import unittest.mock
  import test.conftest
  from evaluation_util import SCORER_LIST, BaseEvaluatorTest, get_dataset_getters, get_evaluation_backend, get_multiclass_classification_datamanager
label_desc: Use image node_id 3 for calling the FunctionsTest obj's underlying member method code with example usage: obj.test_eval_test() without return types