code: def guide(self, x):
      # register PyTorch module `encoder` with Pyro
      pyro.module("encoder", self.encoder)
      with pyro.plate("data", x.shape[0]):
          # use the encoder to get the parameters used to define q(z|x)
          z_loc, z_scale = self.encoder.forward(x)
          # sample the latent code z
          pyro.sample("latent", dist.Normal(z_loc, z_scale).to_event(1))
  
imports: import argparse
  import numpy
  import torch
  import torch.nn
  import visdom
  from utils.mnist_cached import MNISTCached
  from utils.mnist_cached import setup_data_loaders
  from utils.vae_plots import mnist_test_tsne, plot_llk, plot_vae_samples
  import pyro
  import pyro.distributions
  from pyro.infer import SVI, JitTrace_ELBO, Trace_ELBO
  from pyro.optim import Adam
label_desc: Use image node_id 3 for calling the VAE obj's underlying member method code with example usage: obj.guide(x) without return types