code: def load_multivariate_constant_dataset():
      dataset_info, train_ds, test_ds = constant_dataset()
      grouper_train = MultivariateGrouper(max_target_dim=10)
      grouper_test = MultivariateGrouper(
          num_test_dates=1, max_target_dim=10
      )
      metadata = dataset_info.metadata
      metadata.prediction_length = dataset_info.prediction_length
      return TrainDatasets(
          metadata=dataset_info.metadata,
          train=grouper_train(train_ds),
          test=grouper_test(test_ds),
      )
  
file_path: gluonts/test/mx/model/gpvar/test_gpvar.py
imports: import mxnet
  import pytest
  from flaky import flaky
  from gluonts.dataset.artificial import constant_dataset
  from gluonts.dataset.common import TrainDatasets
  from gluonts.dataset.multivariate_grouper import MultivariateGrouper
  from gluonts.evaluation import backtest_metrics, MultivariateEvaluator
  from gluonts.mx.model.gpvar import GPVAREstimator
  from gluonts.mx.distribution import LowrankMultivariateGaussian
  from gluonts.mx.distribution.lowrank_gp import GPArgProj, LowrankGPOutput
  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