code: def test_smoke(num_data, feature_dim, outcome_dist):
      x, t, y = generate_data(num_data, feature_dim)
      if outcome_dist == "exponential":
          y.clamp_(min=1e-20)
      cevae = CEVAE(feature_dim, outcome_dist)
      cevae.fit(x, t, y, num_epochs=2)
      ite = cevae.ite(x)
      assert ite.shape == (num_data,)
  
file_path: pyro/tests/contrib/cevae/test_cevae.py
imports: import io
  import warnings
  import pytest
  import torch
  import pyro
  import pyro.distributions
  from pyro.contrib.cevae import CEVAE, DistributionNet
  from tests.common import assert_close
label_desc: Use image node_id 2 for calling a global function with example usage: test_smoke(num_data, feature_dim, outcome_dist) without return types