code: def test_tabular_log_to_file():
      data_root = "https://autogluon.s3.amazonaws.com/datasets/Inc/"
      train_data = TabularDataset(data_root + "train.csv")
      train_data = train_data.sample(500)
  
      predictor = TabularPredictor(label="class", log_to_file=True).fit(
          train_data=train_data, hyperparameters={"DUMMY": {}}
      )
      log = TabularPredictor.load_log(predictor_path=predictor.path)
      assert "TabularPredictor saved." in log[-1]
  
      log_file = os.path.join(".", "temp.log")
      predictor = TabularPredictor(
          label="class", log_to_file=True, log_file_path=log_file
      ).fit(train_data=train_data, hyperparameters={"DUMMY": {}})
      log = TabularPredictor.load_log(log_file_path=log_file)
      assert "TabularPredictor saved." in log[-1]
      if not on_windows:
          os.remove(log_file)
  
      with pytest.raises(AssertionError):
          TabularPredictor.load_log()
  
imports: import os
  import shutil
  import sys
  import tempfile
  import warnings
  from random import seed
  import numpy
  import pandas
  import pytest
  from networkx.exception import NetworkXError
  from autogluon.common import space
  from autogluon.common.utils.simulation_utils import convert_simulation_artifacts_to_tabular_predictions_dict
  from autogluon.core.constants import BINARY, MULTICLASS, PROBLEM_TYPES_CLASSIFICATION, QUANTILE, REGRESSION
  from autogluon.core.utils import download, unzip
  from autogluon.tabular import TabularDataset, TabularPredictor
  from autogluon.tabular.configs.hyperparameter_configs import get_hyperparameter_config
label_desc: Use image node_id 26 for calling a global function with example usage: test_tabular_log_to_file() without return types