code: def load_multivariate_constant_dataset():
      metadata, train_ds, test_ds = constant_dataset()
      grouper_train = MultivariateGrouper(max_target_dim=NUM_SERIES)
      grouper_test = MultivariateGrouper(max_target_dim=NUM_SERIES)
      return TrainDatasets(
          metadata=metadata,
          train=grouper_train(train_ds),
          test=grouper_test(test_ds),
      )
  
file_path: gluonts/test/mx/model/lstnet/test_lstnet.py
imports: import tempfile
  from pathlib import Path
  import numpy
  import pandas
  import pytest
  from gluonts.dataset.artificial import constant_dataset
  from gluonts.dataset.common import TrainDatasets
  from gluonts.dataset.multivariate_grouper import MultivariateGrouper
  from gluonts.evaluation import make_evaluation_predictions, MultivariateEvaluator
  from gluonts.mx.model.lstnet import LSTNetEstimator
  from gluonts.model.predictor import Predictor
  from gluonts.mx.trainer import Trainer
label_desc: Use image node_id 1 for calling a global function with example usage: load_multivariate_constant_dataset() and returns: TrainDatasets