code: def test_all_models_handle_all_pandas_frequencies(freq):
      if (
          parse_version(pd.__version__) < parse_version("2.1")
          and freq == "SM"
      ):
          pytest.skip(
              "'SM' frequency inference not supported by pandas < 2.1"
          )
  
      prediction_length = 5
  
      train_data, test_data = generate_train_and_test_data(
          prediction_length=prediction_length,
          freq=freq,
          use_known_covariates=True,
          use_past_covariates=True,
          start_time="1990-01-01",
      )
      known_covariates_names = [
          col for col in train_data if col.startswith("known_")
      ]
  
      predictor = TimeSeriesPredictor(
          target=TARGET_COLUMN,
          prediction_length=prediction_length,
          known_covariates_names=known_covariates_names
          if len(known_covariates_names) > 0
          else None,
      )
      predictor.fit(train_data, hyperparameters=ALL_MODELS)
      predictor.evaluate(test_data)
      leaderboard = predictor.leaderboard(test_data)
  
      assert_leaderboard_contains_all_models(leaderboard)
  
      known_covariates = test_data.slice_by_timestep(
          -prediction_length, None
      )[known_covariates_names]
      predictions = predictor.predict(
          train_data, known_covariates=known_covariates
      )
  
      future_test_data = test_data.slice_by_timestep(
          -prediction_length, None
      )
  
      assert predictions.index.equals(future_test_data.index)
  
file_path: autogluon/timeseries/tests/smoketests/test_all_models.py
imports: from typing import Tuple
  import numpy
  import pandas
  import pytest
  from pkg_resources import parse_version
  from autogluon.timeseries import TimeSeriesPredictor
  from autogluon.timeseries.dataset.ts_dataframe import ITEMID, TIMESTAMP, TimeSeriesDataFrame
  from autogluon.timeseries.utils.datetime.seasonality import DEFAULT_SEASONALITIES
label_desc: Use image node_id 4 for calling a global function with example usage: test_all_models_handle_all_pandas_frequencies(freq) without return types