code: def _test_logger_initialization(tmp_path, logger_class):
      logger_args = _get_logger_args(logger_class, tmp_path)
      logger = logger_class(**logger_args)
      callbacks = [LazyInitExperimentCheck()]
      if not isinstance(logger, CustomLoggerWithoutExperiment):
          callbacks.append(RankZeroLoggerCheck())
      model = BoringModel()
      trainer = Trainer(
          logger=logger,
          default_root_dir=tmp_path,
          strategy="ddp_spawn",
          accelerator="cpu",
          devices=2,
          max_steps=1,
          callbacks=callbacks,
      )
      trainer.fit(model)
  
imports: import inspect
  import os
  import pickle
  from unittest import mock
  from unittest.mock import ANY, Mock
  import pytest
  import torch
  from lightning.pytorch import Callback, Trainer
  from lightning.pytorch.demos.boring_classes import BoringModel
  from lightning.pytorch.loggers import CometLogger, CSVLogger, MLFlowLogger, NeptuneLogger, TensorBoardLogger, WandbLogger
  from lightning.pytorch.loggers.logger import DummyExperiment, Logger
  from lightning.pytorch.loggers.tensorboard import _TENSORBOARD_AVAILABLE
  from lightning.pytorch.tuner.tuning import Tuner
  from tests_pytorch.helpers.runif import RunIf
  from tests_pytorch.loggers.test_comet import _patch_comet_atexit
  from tests_pytorch.loggers.test_mlflow import mock_mlflow_run_creation
label_desc: Use image node_id 8 for calling a global function with example usage: _test_logger_initialization(tmp_path, logger_class) without return types