code: def test_when_start_times_dont_match_freq_then_forecast_timestamps_are_correct(
      freq, prediction_length
  ):
      item_ids_to_length = {"B": 14, "A": 12, "1": 7}
      start_timestamps = {
          "B": pd.Timestamp("2020-01-05 12:05:01"),
          "A": pd.Timestamp("2017-04-20 07:14:55"),
          "1": pd.Timestamp("1901-12-31 20:14:07"),
      }
      dfs = []
      for item_id, length in item_ids_to_length.items():
          timestamps = pd.date_range(
              start=start_timestamps[item_id], periods=length, freq=freq
          )
          index = pd.MultiIndex.from_product(
              [(item_id,), timestamps], names=[ITEMID, TIMESTAMP]
          )
          dfs.append(
              pd.DataFrame(
                  {"CustomTarget": np.random.rand(length)}, index=index
              )
          )
      ts_dataframe = TimeSeriesDataFrame(pd.concat(dfs))
  
      prediction_index = get_forecast_horizon_index_ts_dataframe(
          ts_dataframe, prediction_length
      )
      preds = TimeSeriesDataFrame(
          pd.DataFrame(
              {"mean": np.random.rand(len(prediction_index))},
              index=prediction_index,
          )
      )
      offset = pd.tseries.frequencies.to_offset(freq)
      for item_id in ts_dataframe.item_ids:
          for i, timestamp in enumerate(preds.loc[item_id].index):
              assert (
                  timestamp
                  == ts_dataframe.loc[item_id].index[-1]
                  + (i + 1) * offset
              )
  
file_path: autogluon/timeseries/tests/unittests/test_utils.py
imports: from typing import Callable
  import numpy
  import pandas
  import pytest
  from autogluon.timeseries.dataset.ts_dataframe import ITEMID, TIMESTAMP, TimeSeriesDataFrame
  from autogluon.timeseries.utils.datetime import get_lags_for_frequency, get_time_features_for_frequency, norm_freq_str
  from autogluon.timeseries.utils.datetime.seasonality import DEFAULT_SEASONALITIES
  from autogluon.timeseries.utils.forecast import get_forecast_horizon_index_ts_dataframe
  from .common import ALL_PANDAS_FREQUENCIES
label_desc: Use image node_id 1 for calling a global function with example usage: test_when_start_times_dont_match_freq_then_forecast_timestamps_are_correct(freq, prediction_length) without return types