code: def get_time_covs(
      self, future_start_date, num_ts, future_covariates, future_dti
  ):
      if self.use_time:
          future_time = TimeCovariates(
              start_date=future_start_date,
              freq=self.freq,
              normalized=True,
              num_ts=num_ts,
          )
          if future_dti is not None:
              future_time.dti = future_dti
          time_covariates = future_time.get_covariates()
          if future_covariates is None:
              covariates = time_covariates
          else:
              covariates = np.vstack(
                  [time_covariates, future_covariates]
              )
      else:
          covariates = future_covariates
      return covariates
  
imports: from __future__ import print_function
  import torch
  import numpy
  import pandas
  import torch.nn
  import torch.optim
  from torch.autograd import Variable
  from zoo.chronos.model.tcmf.data_loader import TCMFDataLoader
  from zoo.chronos.model.tcmf.local_model import TemporalConvNet, LocalModel
  from zoo.chronos.model.tcmf.time import TimeCovariates
  import copy
  import pickle
  import logging
label_desc: Use image node_id 19 for calling the DeepGLO obj's underlying member method code with example usage: obj.get_time_covs(future_start_date, num_ts, future_covariates, future_dti) and returns: covariates