code: def test_count_trailing_zeros(
      target, expected, convert_to_np, is_train
  ):
      if convert_to_np:
          target = np.array(target)
  
      data_set = ListDataset(
          [{"target": target, "start": "2010-01-01"}], freq="1m"
      )
      transform = CountTrailingZeros(new_field="time_remaining")
  
      transformed = next(transform(data_set, is_train=is_train))
  
      if len(target) == 0:
          assert "time_remaining" not in transformed
          return
  
      assert "time_remaining" in transformed
      assert transformed["time_remaining"] == expected
  
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 28 for calling a global function with example usage: test_count_trailing_zeros(target, expected, convert_to_np, is_train) without return types