class_docstr: Parent class of a dataset that can be generated from code.
class_docstr_tok: ["Parent","class","of","a","dataset","that","can","be","generated","from","code","."]
code: def generate(self) -> TrainDatasets:
      return TrainDatasets(
          metadata=self.metadata,
          train=ListDataset(self.train, self.freq),
          test=ListDataset(self.test, self.freq),
      )
  
imports: import math
  import random
  from abc import abstractmethod
  from typing import Callable, Dict, List, NamedTuple, Optional, Tuple, Union, cast
  import numpy
  import pandas
  from pandas.tseries.frequencies import to_offset
  from pandas.tseries.offsets import BaseOffset, Week
  from gluonts.dataset.artificial.recipe import BinaryHolidays, BinaryMarkovChain, Constant, ForEachCat, Lag, LinearTrend, RandomCat, RandomGaussian, Stack, generate, take_as_list
  from gluonts.dataset.common import BasicFeatureInfo, CategoricalFeatureInfo, DataEntry, Dataset, ListDataset, MetaData, TrainDatasets
  from gluonts.dataset.field_names import FieldName
  from gluonts.dataset.stat import DatasetStatistics, calculate_dataset_statistics
label_desc: Use image node_id 5 for calling the ArtificialDataset obj's underlying member method code with example usage: obj.generate() and returns: TrainDatasets