code: def test_target_dim_indicator():
      target = np.array([0, 2, 3, 10]).tolist()
  
      multi_dim_target = np.array([target, target, target, target])
      dataset = gluonts.dataset.common.ListDataset(
          data_iter=[
              {"start": "2012-01-01", "target": multi_dim_target}
          ],
          freq="1D",
          one_dim_target=False,
      )
  
      t = transform.TargetDimIndicator(
          target_field=FieldName.TARGET, field_name="target_dimensions"
      )
  
      for data_entry in t(dataset, is_train=True):
          assert (
              data_entry["target_dimensions"] == np.array([0, 1, 2, 3])
          ).all()
  
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 15 for calling a global function with example usage: test_target_dim_indicator() without return types