code: def make_dataset(N, train_length):
      # generates 2 ** N - 1 timeseries with constant increasing values
      n = 2**N - 1
      targets = np.ones((n, train_length))
      for i in range(0, n):
          targets[i, :] = targets[i, :] * i
  
      ds = gluonts.dataset.common.ListDataset(
          data_iter=[
              {"start": "2012-01-01", "target": targets[i, :]}
              for i in range(n)
          ],
          freq="1D",
      )
  
      return ds
  
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 24 for calling a global function with example usage: make_dataset(N, train_length) and returns: ds