class_docstr: generic mean-field guide for continuous random effects
class_docstr_tok: ["generic","mean-field","guide","for","continuous","random","effects"]
code: def initialize_params(self):
      # dictionary of guide random effect parameters
      params = {"eps_g": {}, "eps_i": {}}
  
      N_state = self.config["sizes"]["state"]
  
      # initialize group-level parameters
      if self.config["group"]["random"] == "continuous":
          params["eps_g"]["loc"] = Tensor(
              pyro.param(
                  "loc_group", lambda: torch.zeros((N_state, N_state))
              ),
              OrderedDict([("y_prev", Bint[N_state])]),
          )
  
          params["eps_g"]["scale"] = Tensor(
              pyro.param(
                  "scale_group",
                  lambda: torch.ones((N_state, N_state)),
                  constraint=constraints.positive,
              ),
              OrderedDict([("y_prev", Bint[N_state])]),
          )
  
      # initialize individual-level random effect parameters
      N_c = self.config["sizes"]["group"]
      if self.config["individual"]["random"] == "continuous":
          params["eps_i"]["loc"] = Tensor(
              pyro.param(
                  "loc_individual",
                  lambda: torch.zeros((N_c, N_state, N_state)),
              ),
              OrderedDict(
                  [("g", Bint[N_c]), ("y_prev", Bint[N_state])]
              ),
          )
  
          params["eps_i"]["scale"] = Tensor(
              pyro.param(
                  "scale_individual",
                  lambda: torch.ones((N_c, N_state, N_state)),
                  constraint=constraints.positive,
              ),
              OrderedDict(
                  [("g", Bint[N_c]), ("y_prev", Bint[N_state])]
              ),
          )
  
      self.params = params
      return self.params
  
imports: from collections import OrderedDict
  import pyro
  import torch
  from torch.distributions import constraints
  import funsor.ops
  import funsor.torch.distributions
  from funsor.domains import Bint, Reals
  from funsor.tensor import Tensor
  from funsor.terms import Stack, Variable, to_funsor
label_desc: Use image node_id 2 for calling the Guide obj's underlying member method code with example usage: obj.initialize_params() and returns: self