code: def prior(self, n, **kwargs):
      state = ModelState(
          x=torch.zeros(n, self.x_size, self.x_size, **self.options),
          z_pres=torch.ones(n, self.z_pres_size, **self.options),
          z_where=None,
      )
  
      z_pres = []
      z_where = []
  
      for t in range(self.num_steps):
          state = self.prior_step(t, n, state, **kwargs)
          z_where.append(state.z_where)
          z_pres.append(state.z_pres)
  
      return (z_where, z_pres), state.x
  
imports: from collections import namedtuple
  import torch
  import torch.nn
  import torch.nn.functional
  from modules import MLP, Decoder, Encoder, Identity, Predict
  import pyro
  import pyro.distributions
label_desc: Use image node_id 2 for calling the AIR obj's underlying member method code with example usage: obj.prior(n) and returns: z_where,  z_pres,  state