code: def test_nnunetv2runner(self) -> None:
      runner = nnUNetV2Runner(
          input_config=self.data_src_cfg,
          trainer_class_name="nnUNetTrainer_1epoch",
      )
      with skip_if_downloading_fails():
          runner.run(
              run_train=False,
              run_find_best_configuration=False,
              run_predict_ensemble_postprocessing=False,
          )
          runner.train(configs="3d_fullres")
          runner.find_best_configuration(configs="3d_fullres")
          runner.predict_ensemble_postprocessing()
  
file_path: MONAI/tests/test_integration_nnunetv2_runner.py
imports: from __future__ import annotations
  import os
  import tempfile
  import unittest
  import nibabel
  import numpy
  from monai.apps.nnunet import nnUNetV2Runner
  from monai.bundle.config_parser import ConfigParser
  from monai.data import create_test_image_3d
  from monai.utils import optional_import
  from tests.utils import SkipIfBeforePyTorchVersion, skip_if_downloading_fails, skip_if_no_cuda, skip_if_quick
label_desc: Use image node_id 2 for calling the TestnnUNetV2Runner obj's underlying member method code with example usage: obj.test_nnunetv2runner() without return types