code: def test_ctsplitter_train_samples_correct_times(
      point_process_dataset,
  ):
      splitter = transform.ContinuousTimeInstanceSplitter(
          past_interval_length=1.25,
          future_interval_length=1.25,
          instance_sampler=transform.ContinuousTimeUniformSampler(
              num_instances=20,
              min_past=1.25,
              min_future=1.25,
          ),
          freq=to_offset("H"),
      )
  
      iter_de = splitter(point_process_dataset, is_train=True)
  
      assert all(
          [
              (
                  pd.Timestamp("2011-01-01 01:15:00")
                  <= d["forecast_start"]
                  <= pd.Timestamp("2011-01-01 01:45:00")
              )
              for d in iter_de
          ]
      )
  
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 21 for calling a global function with example usage: test_ctsplitter_train_samples_correct_times(point_process_dataset) without return types