code: def test_AddTimeFeatures(start, target, is_train: bool):
      pred_length = 13
      t = transform.AddTimeFeatures(
          start_field=FieldName.START,
          target_field=FieldName.TARGET,
          output_field="myout",
          pred_length=pred_length,
          time_features=[
              time_feature.day_of_week,
              time_feature.day_of_month,
          ],
          dtype=np.float64,
      )
  
      assert_serializable(t)
  
      data = {"start": start, "target": target}
      res = t.map_transform(data, is_train=is_train)
      mat = res["myout"]
      expected_length = len(target) + (0 if is_train else pred_length)
      assert mat.shape == (2, expected_length)
      tmp_idx = pd.period_range(
          start=start, freq=start.freq, periods=expected_length
      )
      assert np.alltrue(mat[0] == time_feature.day_of_week(tmp_idx))
      assert np.alltrue(mat[1] == time_feature.day_of_month(tmp_idx))
  
imports: from typing import Tuple, List
  import numpy
  import pandas
  from pandas.tseries.frequencies import to_offset
  import pytest
  import gluonts
  from gluonts import time_feature, transform
  from gluonts.core import fqname_for
  from gluonts.core.serde import dump_json, load_json
  from gluonts.dataset.common import DataEntry, ListDataset
  from gluonts.dataset.field_names import FieldName
  from gluonts.dataset.stat import ScaleHistogram, calculate_dataset_statistics
  from gluonts.transform import CausalMeanValueImputation, DummyValueImputation, LastValueImputation, MeanValueImputation, RollingMeanValueImputation, Valmap
  from gluonts.transform.convert import ToIntervalSizeFormat, erf, erfinv
  from gluonts.transform.feature import CountTrailingZeros
label_desc: Use image node_id 3 for calling a global function with example usage: test_AddTimeFeatures(start, target, is_train) without return types