code: def _get_config(self):
      return {
          "name": "test_task",
          "num_epochs": 12,
          "loss": {"name": "test_loss"},
          "dataset": {
              "name": "test_data",
              "batchsize_per_replica": 8,
              "use_pairs": False,
              "num_samples": None,
              "use_shuffle": {"train": True, "test": False},
          },
          "meters": [{"name": "test_meter", "test_param": 0.1}],
          "model": {"name": "test_model", "architecture": [1, 2, 3, 4]},
          "optimizer": {
              "name": "test_optimizer",
              "test_param": {
                  "name": "test_scheduler",
                  "values": [0.1, 0.01, 0.001, 0.0001],
              },
          },
      }
  
imports: import copy
  import shutil
  import tempfile
  import unittest
  import unittest.mock
  from pathlib import Path
  import classy_vision.generic.util
  import torch
  import torch.nn
  from classy_vision.generic.util import CHECKPOINT_FILE, get_torch_version, load_checkpoint, save_checkpoint, split_batchnorm_params, Timer, update_classy_model, update_classy_state
  from classy_vision.models import build_model
  from classy_vision.tasks import build_task
  from classy_vision.trainer import LocalTrainer
  from test.generic.config_utils import get_fast_test_task_config, get_test_model_configs
  from test.generic.utils import compare_model_state, compare_states
label_desc: Use image node_id 2 for calling the TestUtilMethods obj's underlying member method code with example usage: obj._get_config() and returns: dict