code: def test_ctsplitter_train_short_intervals(point_process_dataset):
      splitter = transform.ContinuousTimeInstanceSplitter(
          0.01,
          0.01,
          instance_sampler=MockContinuousTimeSampler(
              ret_values=[1.01, 1.5, 1.99]
          ),
          freq=to_offset("H"),
      )
  
      iter_de = splitter(point_process_dataset, is_train=True)
  
      for d in iter_de:
          assert d["future_valid_length"] == d["past_valid_length"] == 0
          assert np.prod(np.shape(d["past_target"])) == 0
          assert np.prod(np.shape(d["future_target"])) == 0
  
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 22 for calling a global function with example usage: test_ctsplitter_train_short_intervals(point_process_dataset) without return types