class_docstr: Base class for univariate and multivariate time series models.
class_docstr_tok: ["Base","class","for","univariate","and","multivariate","time","series","models","."]
docstr: :param torch.Tensor targets: A 2-dimensional tensor of real-valued targets
      of shape ``(T, obs_dim)``, where ``T`` is the length of the time series and ``obs_dim``
      is the dimension of the real-valued targets at each time step. These
      represent the training data that are conditioned on for the purpose of making
      forecasts.
  :param torch.Tensor dts: A 1-dimensional tensor of times to forecast into the future,
      with zero corresponding to the time of the final target ``targets[-1]``.
  :returns torch.distributions.Distribution: Returns a predictive distribution with batch shape ``(S,)`` and
      event shape ``(obs_dim,)``, where ``S`` is the size of ``dts``. That is, the resulting
      predictive distributions do not encode correlations between distinct times in ``dts``.
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code: def forecast(self, targets, dts):
      """
      :param torch.Tensor targets: A 2-dimensional tensor of real-valued targets
          of shape ``(T, obs_dim)``, where ``T`` is the length of the time series and ``obs_dim``
          is the dimension of the real-valued targets at each time step. These
          represent the training data that are conditioned on for the purpose of making
          forecasts.
      :param torch.Tensor dts: A 1-dimensional tensor of times to forecast into the future,
          with zero corresponding to the time of the final target ``targets[-1]``.
      :returns torch.distributions.Distribution: Returns a predictive distribution with batch shape ``(S,)`` and
          event shape ``(obs_dim,)``, where ``S`` is the size of ``dts``. That is, the resulting
          predictive distributions do not encode correlations between distinct times in ``dts``.
      """
      raise NotImplementedError
  
imports: from pyro.nn import PyroModule, pyro_method
label_desc: Use image node_id 2 for calling the TimeSeriesModel obj's underlying member method code with example usage: obj.forecast(targets, dts) without return types