code: def model(self, zero_data, covariates):
      with pyro.plate_stack(
          "batch", zero_data.shape[:-2], rightmost_dim=-2
      ):
          loc = zero_data[..., :1, 0]
          scale = pyro.sample("scale", dist.LogNormal(loc, 1))
  
          with self.time_plate:
              jumps = pyro.sample("jumps", dist.Normal(0, scale))
          prediction = jumps.cumsum(-1).unsqueeze(-1) + zero_data
  
          noise_dist = dist.Laplace(zero_data, 1)
          self.predict(noise_dist, prediction)
  
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 1 for calling the Model0 obj's underlying member method code with example usage: obj.model(zero_data, covariates) without return types