code: def test_logger_default_name(mlflow_mock, monkeypatch, tmp_path):
      """Test that the default logger name is lightning_logs."""
      # CSV
      logger = CSVLogger(save_dir=tmp_path)
      assert logger.name == "lightning_logs"
  
      # TensorBoard
      if _TENSORBOARD_AVAILABLE:
          import torch.utils.tensorboard as tb
      else:
          import tensorboardX as tb
  
      monkeypatch.setattr(tb, "SummaryWriter", Mock())
      logger = _instantiate_logger(TensorBoardLogger, save_dir=tmp_path)
      assert logger.name == "lightning_logs"
  
      # MLflow
      client = mlflow_mock.tracking.MlflowClient()
      client.get_experiment_by_name.return_value = None
      logger = _instantiate_logger(MLFlowLogger, save_dir=tmp_path)
  
      _ = logger.experiment
      logger._mlflow_client.create_experiment.assert_called_with(
          name="lightning_logs", artifact_location=ANY
      )
  
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 10 for calling a global function with example usage: test_logger_default_name(mlflow_mock, monkeypatch, tmp_path) without return types