code: def test_svi_custom_smoke(subsample_aware):
      t_obs = 5
      t_forecast = 4
      cov_dim = 3
      obs_dim = 2
  
      model = Model0()
      data = torch.randn(t_obs, obs_dim)
      covariates = torch.randn(t_obs + t_forecast, cov_dim)
      guide = AutoDelta(model)
      optim = Adam({})
  
      Forecaster(
          model,
          data,
          covariates[..., :t_obs, :],
          guide=guide,
          optim=optim,
          subsample_aware=subsample_aware,
          num_steps=2,
          log_every=1,
      )
  
imports: import pytest
  import torch
  import pyro
  import pyro.distributions
  import pyro.poutine
  from pyro.contrib.forecast import Forecaster, ForecastingModel, HMCForecaster
  from pyro.infer.autoguide import AutoDelta
  from pyro.infer.reparam import LinearHMMReparam, StableReparam
  from pyro.optim import Adam
label_desc: Use image node_id 3 for calling a global function with example usage: test_svi_custom_smoke(subsample_aware) without return types