code: def test_pickle(test_dataset):
      pickle.dumps(test_dataset)
      pickle.dumps(test_dataset.to_dataloader())
  
imports: from copy import deepcopy
  import itertools
  import pickle
  from typing import Dict
  import networkx
  import numpy
  import pandas
  import pytest
  from sklearn.preprocessing import StandardScaler
  import torch
  from torch.utils.data.sampler import SequentialSampler
  from pytorch_forecasting.data import EncoderNormalizer, GroupNormalizer, NaNLabelEncoder, TimeSeriesDataSet
  from pytorch_forecasting.data.encoders import MultiNormalizer, TorchNormalizer
  from pytorch_forecasting.data.examples import get_stallion_data
  from pytorch_forecasting.data.timeseries import _find_end_indices
  from pytorch_forecasting.utils import to_list
label_desc: Use image node_id 4 for calling a global function with example usage: test_pickle(test_dataset) without return types