code: def main(args):
      pyro.set_rng_seed(0)
  
      optim = Adam({"lr": 0.1})
      elbo = JitTrace_ELBO() if args.jit else Trace_ELBO()
      inference = SVI(model, guide, optim, loss=elbo)
      data = torch.tensor([0.0, 1.0, 2.0, 20.0, 30.0, 40.0])
      k = 2
  
      print("Step\tLoss")
      loss = 0.0
      for step in range(args.num_epochs):
          if step and step % 10 == 0:
              print("{}\t{:0.5g}".format(step, loss))
              loss = 0.0
          loss += inference.step(data, k=k)
  
      print("Parameters:")
      for name, value in sorted(pyro.get_param_store().items()):
          print("{} = {}".format(name, value.detach().cpu().numpy()))
  
file_path: pyro/examples/contrib/autoname/mixture.py
imports: import argparse
  import torch
  from torch.distributions import constraints
  import pyro
  import pyro.distributions
  from pyro.contrib.autoname import named
  from pyro.infer import SVI, JitTrace_ELBO, Trace_ELBO
  from pyro.optim import Adam
label_desc: Use image node_id 5 for calling a global function with example usage: main(args) without return types