class_docstr: Base class for univariate and multivariate time series models.
class_docstr_tok: ["Base","class","for","univariate","and","multivariate","time","series","models","."]
docstr: Log probability function.
  
  :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
  :returns torch.Tensor: A 0-dimensional log probability for the case of properly
      multivariate time series models in which the output dimensions are correlated;
      otherwise returns a 1-dimensional tensor of log probabilities for batched
      univariate time series models.
docstr_tok: ["Log","probability","function",".",":","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",":","returns","torch.Tensor",":","A","0-dimensional","log","probability","for","the","case","of","properly","multivariate","time","series","models","in","which","the","output","dimensions","are","correlated",";","otherwise","returns","a","1-dimensional","tensor","of","log","probabilities","for","batched","univariate","time","series","models","."]
code: def log_prob(self, targets):
      """
      Log probability function.
  
      :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
      :returns torch.Tensor: A 0-dimensional log probability for the case of properly
          multivariate time series models in which the output dimensions are correlated;
          otherwise returns a 1-dimensional tensor of log probabilities for batched
          univariate time series models.
      """
      raise NotImplementedError
  
imports: from pyro.nn import PyroModule, pyro_method
label_desc: Use image node_id 1 for calling the TimeSeriesModel obj's underlying member method code with example usage: obj.log_prob(targets) without return types