code: def load_unit_test_tsf():
      """Load tsf UnitTest dataset.
  
      Returns
      -------
      loaded_data: pd.DataFrame
          The converted dataframe containing the time series.
      frequency: str
          The frequency of the dataset.
      forecast_horizon: int
          The expected forecast horizon of the dataset.
      contain_missing_values: bool
          Whether the dataset contains missing values or not.
      contain_equal_length: bool
          Whether the series have equal lengths or not.
      """
      path = os.path.join(
          MODULE, DIRNAME, "UnitTest", "UnitTest_Tsf_Loader.tsf"
      )
      (
          loaded_data,
          frequency,
          forecast_horizon,
          contain_missing_values,
          contain_equal_length,
      ) = load_tsf_to_dataframe(path)
  
      return (
          loaded_data,
          frequency,
          forecast_horizon,
          contain_missing_values,
          contain_equal_length,
      )
  
imports: import os
  import zipfile
  from urllib.error import HTTPError, URLError
  from warnings import warn
  import numpy
  import pandas
  from sktime.datasets._data_io import _download_and_extract, _list_available_datasets, _load_dataset, _load_provided_dataset
  from sktime.datasets._readers_writers.tsf import load_tsf_to_dataframe
  from sktime.datasets.tsf_dataset_names import tsf_all, tsf_all_datasets
  from sktime.utils.validation._dependencies import _check_soft_dependencies
label_desc: Use image node_id 21 for calling a global function with example usage: load_unit_test_tsf() and returns: loaded_data,  frequency,  forecast_horizon,  contain_missing_values,  contain_equal_length