class_docstr: A data module which provides an arbitrary dataset from GlounTS.
  
  Parameters
  ----------
  dataset_name: str
      The GluonTS name of the dataset.
  context_length_multiple: int
      Context length is prediction length x ``context_length_multiple``.
  support_length_multiple: int
      Support time series length is prediction length x ``support_length_multiple``.
  support_set_size: int
      Number of time series in the support set.
  num_queries: int
      Number of queries used for the same support set.
  data_dir: pathlib.Path
      Path to data.
  prediction_length: int
      Number of predicted time steps.
  standardize: bool
      If each time series is standardized.
  batch_size_train: int
      Batch size during training.
  batch_size_val_test: int
      Batch size during validation and testing.
  num_workers: int
      Number of workers.
  seed: int
      The random seed.
  catch22_train: bool
      If catch22 similarity measure is used for support set selection during training.
  catch22_val_test: bool
      If catch22 similarity measure is used for support set selection during validation and testing.
  cheat: float
      Chance of hiding the ground truth in the support set.
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code: def support_length(self) -> int:
      return self.support_length_multiple * self.prediction_length
  
imports: from typing import List, Optional, Literal, Dict, Any
  from pathlib import Path
  from functools import cached_property
  import shutil
  import tempfile
  import pickle
  import pandas
  from tqdm import tqdm
  import catch22
  import pytorch_lightning
  from gluonts.dataset.repository.datasets import materialize_dataset
  from gluonts.dataset.common import MetaData
  from torch.utils.data import DataLoader
  from sklearn.neighbors import NearestNeighbors
  from meta.data.batch import TripletBatch
  from meta.data.sampling import SamplingTripletDataset, SequentialTripletDataset
  from meta.datasets.splits import DatasetSplits
  from meta.data.dataset import TimeSeries
  from meta.datasets.preprocessing import Filter, AbsoluteValueFilter, ConstantTargetFilter, EndOfSeriesCutFilter, MinLengthFilter, read_transform_write, ItemIDTransform
  from meta.datasets.registry import register_data_module
label_desc: Use image node_id 3 for calling the GluonTSDataModule obj's underlying member method code with example usage: obj.support_length() and returns: unknown