code: def test_detect_gpu(self):
      import copy
  
      params = copy.deepcopy(self.DEFAULT_PARAMS)
      params["trainer"]["callbacks"] = ["training_device_logger"]
  
      global _seen_training_devices
      _seen_training_devices.clear()
      train_model(
          params,
          serialization_dir=os.path.join(
              self.TEST_DIR, "test_detect_gpu"
          ),
      )
      assert len(_seen_training_devices) == 1
      seen_training_device = next(iter(_seen_training_devices))
      if torch.cuda.device_count() == 0:
          assert seen_training_device.type == "cpu"
      else:
          assert seen_training_device.type == "cuda"
  
imports: import argparse
  import copy
  import json
  import logging
  import math
  import os
  import re
  import shutil
  from collections import OrderedDict, Counter
  from typing import Optional, List, Dict, Any
  import pytest
  import torch
  from allennlp.version import VERSION
  from allennlp.commands.train import Train, train_model, train_model_from_args, TrainModel
  from allennlp.common import Params
  from allennlp.common.checks import ConfigurationError
  from allennlp.common.testing import AllenNlpTestCase, cpu_or_gpu
  from allennlp.data import Vocabulary
  from allennlp.data.data_loaders import TensorDict
  from allennlp.models import load_archive, Model
  from allennlp.models.archival import CONFIG_NAME
  from allennlp.training import TrainerCallback, GradientDescentTrainer
  from allennlp.training.learning_rate_schedulers import ExponentialLearningRateScheduler, LearningRateScheduler
label_desc: Use image node_id 2 for calling the TestTrain obj's underlying member method code with example usage: obj.test_detect_gpu() without return types