code: def test_native_print_results(monkeypatch, inputs, expected):
      import lightning.pytorch.loops.evaluation_loop as imports
  
      monkeypatch.setattr(imports, "_RICH_AVAILABLE", False)
  
      with redirect_stdout(StringIO()) as out:
          _EvaluationLoop._print_results(*inputs)
      expected = expected[
          1:
      ]  # remove the initial line break from the """ string
      assert (
          out.getvalue().replace(os.linesep, "\n") == expected.lstrip()
      )
  
imports: import collections
  import itertools
  import os
  from contextlib import redirect_stdout
  from io import StringIO
  from unittest import mock
  from unittest.mock import ANY, call
  import numpy
  import pytest
  import torch
  from lightning.fabric.utilities.imports import _PYTHON_GREATER_EQUAL_3_8_0
  from lightning.pytorch import Trainer, callbacks
  from lightning.pytorch.callbacks.progress.rich_progress import _RICH_AVAILABLE
  from lightning.pytorch.demos.boring_classes import BoringModel, RandomDataset
  from lightning.pytorch.loggers import TensorBoardLogger
  from lightning.pytorch.loops import _EvaluationLoop
  from lightning.pytorch.trainer.states import RunningStage
  from lightning.pytorch.utilities.exceptions import MisconfigurationException
  from torch import Tensor
  from tests_pytorch.helpers.runif import RunIf
label_desc: Use image node_id 15 for calling a global function with example usage: test_native_print_results(monkeypatch, inputs, expected) without return types