class_docstr: Interface for Stochastic Variational Inference with an adaptive
  f-divergence as described in ref. [1]. Users should specify
  `num_particles` > 1 and `vectorize_particles==True`. The argument
  `tail_adaptive_beta` can be specified to modify how the adaptive
  f-divergence is constructed. See reference for details.
  
  Note that this interface does not support computing the varational
  objective itself; rather it only supports computing gradients of the
  variational objective. Consequently, one might want to use
  another SVI interface (e.g. `RenyiELBO`) in order to monitor convergence.
  
  Note that this interface only supports models in which all the latent
  variables are fully reparameterized. It also does not support data
  subsampling.
  
  References
  [1] "Variational Inference with Tail-adaptive f-Divergence", Dilin Wang,
  Hao Liu, Qiang Liu, NeurIPS 2018
  https://papers.nips.cc/paper/7816-variational-inference-with-tail-adaptive-f-divergence
docstr: It is not necessary to estimate the tail-adaptive f-divergence itself in order
  to compute the corresponding gradients. Consequently the loss method is left
  unimplemented.
docstr_tok: ["It","is","not","necessary","to","estimate","the","tail-adaptive","f-divergence","itself","in","order","to","compute","the","corresponding","gradients",".","Consequently","the","loss","method","is","left","unimplemented","."]
code: def loss(self, model, guide, *args, **kwargs):
      """
      It is not necessary to estimate the tail-adaptive f-divergence itself in order
      to compute the corresponding gradients. Consequently the loss method is left
      unimplemented.
      """
      raise NotImplementedError(
          "Loss method for TraceTailAdaptive_ELBO not implemented"
      )
  
file_path: pyro/pyro/infer/trace_tail_adaptive_elbo.py
imports: import warnings
  import torch
  from pyro.infer.trace_elbo import Trace_ELBO
  from pyro.infer.util import check_fully_reparametrized, is_validation_enabled
label_desc: Use image node_id 1 for calling the TraceTailAdaptive_ELBO obj's underlying member method code with example usage: obj.loss(model, guide) without return types