code: def forward(self, y_dict, design, observation_labels, target_labels):
      pyro.module("ba_guide", self)
  
      mu, scale_tril, alpha, beta = self.get_params(
          y_dict, design, target_labels
      )
  
      if self.tau_label in target_labels:
          tau_dist = dist.Gamma(alpha, beta)
          tau = pyro.sample(self.tau_label, tau_dist)
          obs_sd = 1.0 / tau.sqrt().unsqueeze(-1).unsqueeze(-1)
  
      for label in target_labels:
          if label != self.tau_label:
              if self.mf:
                  w_dist = dist.MultivariateNormal(
                      mu[label], scale_tril=scale_tril[label]
                  )
              else:
                  w_dist = dist.MultivariateNormal(
                      mu[label], scale_tril=scale_tril[label] * obs_sd
                  )
              pyro.sample(label, w_dist)
  
imports: from contextlib import ExitStack
  import torch
  from torch import nn
  import pyro
  import pyro.distributions
  from pyro import poutine
  from pyro.contrib.util import iter_plates_to_shape, lexpand, rmv, rtril, rvv, tensor_to_dict
  from pyro.ops.linalg import rinverse
label_desc: Use image node_id 3 for calling the NormalInverseGammaGuide obj's underlying member method code with example usage: obj.forward(y_dict, design, observation_labels, target_labels) without return types