code: def test_fit_csv_logger(tmp_path):
      dm = ClassifDataModule()
      model = ClassificationModel()
      logger = CSVLogger(save_dir=tmp_path)
      trainer = Trainer(
          default_root_dir=tmp_path,
          max_steps=10,
          logger=logger,
          log_every_n_steps=1,
      )
      trainer.fit(model, datamodule=dm)
      metrics_file = os.path.join(
          logger.log_dir, ExperimentWriter.NAME_METRICS_FILE
      )
      assert os.path.isfile(metrics_file)
  
imports: import os
  from unittest.mock import MagicMock
  import fsspec
  import pytest
  import torch
  from lightning.pytorch import Trainer
  from lightning.pytorch.core.saving import load_hparams_from_yaml
  from lightning.pytorch.loggers import CSVLogger
  from lightning.pytorch.loggers.csv_logs import ExperimentWriter
  from tests_pytorch.helpers.datamodules import ClassifDataModule
  from tests_pytorch.helpers.runif import RunIf
  from tests_pytorch.helpers.simple_models import ClassificationModel
label_desc: Use image node_id 7 for calling a global function with example usage: test_fit_csv_logger(tmp_path) without return types