code: def point_process_dataset():
      ia_times = np.array([0.2, 0.7, 0.2, 0.5, 0.3, 0.3, 0.2, 0.1])
      marks = np.array([0, 1, 2, 0, 1, 2, 2, 2])
  
      return ListDataset(
          [
              {
                  "target": np.c_[ia_times, marks].T,
                  "start": pd.Timestamp("2011-01-01 00:00:00"),
                  "end": pd.Timestamp("2011-01-01 03:00:00"),
              }
          ],
          freq="H",
          one_dim_target=False,
          use_timestamp=True,
      )
  
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 16 for calling a global function with example usage: point_process_dataset() and returns: ListDataset