code: def test_when_predict_called_then_predicted_timestamps_align_with_time(
      model_class, freq, temp_model_path
  ):
      prediction_length = 4
      train_length = 20
      item_id = "A"
      timestamps = pd.date_range(
          start=pd.Timestamp("2020-01-05 12:05:01"),
          freq=freq,
          periods=train_length,
      )
      index = pd.MultiIndex.from_product(
          [(item_id,), timestamps], names=[ITEMID, TIMESTAMP]
      )
      train_data = TimeSeriesDataFrame(
          pd.DataFrame(
              {"target": np.random.rand(train_length)}, index=index
          )
      )
  
      model = model_class(
          path=temp_model_path,
          freq=train_data.freq,
          prediction_length=prediction_length,
          hyperparameters=DUMMY_HYPERPARAMETERS,
      )
  
      model.fit(train_data=train_data)
      predictions = model.predict(train_data)
  
      offset = pd.tseries.frequencies.to_offset(freq)
      preds_first_item = predictions.loc[item_id]
      for i in range(prediction_length):
          assert preds_first_item.index[i] == timestamps[
              -1
          ] + offset * (i + 1)
  
imports: import itertools
  import shutil
  import sys
  import tempfile
  from unittest import mock
  import numpy
  import pandas
  import pytest
  from flaky import flaky
  from autogluon.common import space
  from autogluon.core.hpo.constants import RAY_BACKEND
  from autogluon.timeseries import TimeSeriesDataFrame
  from autogluon.timeseries.dataset.ts_dataframe import ITEMID, TIMESTAMP
  from autogluon.timeseries.metrics import AVAILABLE_METRICS
  from autogluon.timeseries.models import DeepARModel, ETSModel
  from autogluon.timeseries.models.abstract import AbstractTimeSeriesModel
  from autogluon.timeseries.models.multi_window import MultiWindowBacktestingModel
  from ..common import DUMMY_TS_DATAFRAME, CustomMetric, dict_equal_primitive, get_data_frame_with_item_index
  from .test_gluonts import TESTABLE_MODELS
  from .test_local import TESTABLE_MODELS
  from .test_mlforecast import TESTABLE_MODELS
  from .test_multi_window_model import get_multi_window_deepar
label_desc: Use image node_id 13 for calling a global function with example usage: test_when_predict_called_then_predicted_timestamps_align_with_time(model_class, freq, temp_model_path) without return types