code: def create_training_network(
      self, device: torch.device
  ) -> DeepVARTrainingNetwork:
      return DeepVARTrainingNetwork(
          input_size=self.input_size,
          target_dim=self.target_dim,
          num_layers=self.num_layers,
          num_cells=self.num_cells,
          cell_type=self.cell_type,
          history_length=self.history_length,
          context_length=self.context_length,
          prediction_length=self.prediction_length,
          distr_output=self.distr_output,
          dropout_rate=self.dropout_rate,
          cardinality=self.cardinality,
          embedding_dimension=self.embedding_dimension,
          lags_seq=self.lags_seq,
          scaling=self.scaling,
      ).to(device)
  
imports: from typing import List, Optional, Callable
  import numpy
  import torch
  from gluonts.core.component import validated
  from gluonts.dataset.field_names import FieldName
  from gluonts.time_feature import TimeFeature
  from gluonts.torch.modules.distribution_output import DistributionOutput
  from gluonts.torch.util import copy_parameters
  from gluonts.torch.model.predictor import PyTorchPredictor
  from gluonts.model.predictor import Predictor
  from gluonts.transform import AddObservedValuesIndicator, AddTimeFeatures, AsNumpyArray, CDFtoGaussianTransform, Chain, ExpandDimArray, ExpectedNumInstanceSampler, InstanceSplitter, ValidationSplitSampler, TestSplitSampler, RenameFields, SetField, TargetDimIndicator, Transformation, VstackFeatures, RemoveFields, AddAgeFeature, cdf_to_gaussian_forward_transform
  from pts import Trainer
  from pts.model.utils import get_module_forward_input_names
  from pts.feature import fourier_time_features_from_frequency, lags_for_fourier_time_features_from_frequency
  from pts.model import PyTorchEstimator
  from pts.modules import LowRankMultivariateNormalOutput
  from .deepvar_network import DeepVARTrainingNetwork, DeepVARPredictionNetwork
label_desc: Use image node_id 4 for calling the DeepVAREstimator obj's underlying member method code with example usage: obj.create_training_network(device) and returns: DeepVARTrainingNetwork