anchor.diff:  
   (defun make-bpn (defs chunk-name &key class initargs)
     (let ((bpn-def `(build-bpn (:class ',class
  -                                     :max-n-stripes 1000
  +                                     :max-n-stripes 10000
                                        :initargs ',initargs)
                       ,@defs
                       ,@(tack-cross-entropy-softmax-error-on
  
positive.code: 
  (defmethod log-test-error ((trainer mnist-rbm-trainer) (rbm mnist-rbm))
    (call-next-method)
    (log-dbn-cesc-accuracy rbm (make-training-sampler) "training")
    (map nil (lambda (counter)
               (log-msg "dbn test: ~:_test ~:_~A~%" counter))
         (collect-dbn-mean-field-errors/labeled
  
negative.code: ;;;; DBN-to-DBM-to-BPN
  ;;;;
  ;;;; A 784-500-1000 DBM is pretrained as a DBN then the DBM is
  ;;;; translated to a BPN. It's pretty much the same training process
  ;;;; except that after the DBN the DBM is trained by PCD before
  ;;;; unrolling that into a BPN. Accuracy is ~99.09% a bit higher than
  ;;;; the reported 99.05%.
  
  (in-package :mgl-example-mnist)
  
  