class_docstr: Replica Exchange MCMC [@swendsen1986replica; @hukushima1996exchange].
  
  #### Examples
  ```python
  cat = Categorical(probs=[0.5,0.5])
  x = Mixture(cat=cat, components=[
      MultivariateNormalDiag([0.0,0.0], [1.0,1.0]),
      MultivariateNormalDiag([10.0,10.0], [1.0,1.0])])
  proposal_x = MultivariateNormalDiag(x, [1.0,1.0])
  qx = Empirical(tf.Variable(tf.zeros([10000, 2])))
  inference = ed.ReplicaExchangeMC(latent_vars={x: qx},
                                   proposal_vars={x: proposal_x})
  ```
class_docstr_tok: ["Replica","Exchange","MCMC","[","@","swendsen1986replica",";","@","hukushima1996exchange","]",".","#","#","#","#","Examples","``","`","python","cat","=","Categorical","(","probs=","[","0.5,0.5","]",")","x","=","Mixture","(","cat=cat",",","components=","[","MultivariateNormalDiag","(","[","0.0,0.0","]",",","[","1.0,1.0","]",")",",","MultivariateNormalDiag","(","[","10.0,10.0","]",",","[","1.0,1.0","]",")","]",")","proposal_x","=","MultivariateNormalDiag","(","x",",","[","1.0,1.0","]",")","qx","=","Empirical","(","tf.Variable","(","tf.zeros","(","[","10000",",","2","]",")",")",")","inference","=","ed.ReplicaExchangeMC","(","latent_vars=","{","x",":","qx","}",",","proposal_vars=","{","x",":","proposal_x","}",")","``","`"]
code: def initialize(self, *args, **kwargs):
      kwargs["auto_transform"] = False
      return super(ReplicaExchangeMC, self).initialize(*args, **kwargs)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import six
  import tensorflow
  import numpy
  from collections import OrderedDict
  from edward.inferences.monte_carlo import MonteCarlo
  from edward.models import Empirical, RandomVariable
  from edward.util import check_latent_vars, copy
label_desc: Use image node_id 2 for calling the ReplicaExchangeMC obj's underlying member method code with example usage: obj.initialize() and returns: super