code: def softmax_model():
      a = pyro.sample("a", dist.Dirichlet(torch.ones(6)))
      b = pyro.sample(
          "b", dist.RelaxedOneHotCategorical(probs=a, temperature=2.0)
      )
      c = pyro.sample("c", dist.Normal(torch.ones(7), 1).to_event(1))
      d = pyro.sample(
          "d", dist.RelaxedOneHotCategorical(logits=c, temperature=1.0)
      )
      e = pyro.sample(
          "e",
          dist.RelaxedOneHotCategorical(logits=c, temperature=0.5),
          obs=d.round(),
      )
      return a, b, c, d, e
  
imports: import pytest
  import torch
  import pyro
  import pyro.distributions
  from pyro import poutine
  from pyro.infer import SVI, Predictive, Trace_ELBO
  from pyro.infer.autoguide import AutoNormal
  from pyro.infer.reparam import AutoReparam, MinimalReparam
  from pyro.optim import Adam
label_desc: Use image node_id 11 for calling a global function with example usage: softmax_model() and returns: a,  b,  c,  d,  e