anchor.diff:           bpn)
     (log-msg "Starting to train the whole BPN~%")
     (train (make-sampler *training-images*
  -                       :max-n (* 95 (length *training-images*))
  +                       :max-n (* n-epochs (length *training-images*))
                          :omit-label-p t)
            (make-instance 'mnist-cg-bp-trainer
                           :cg-args (list :max-n-line-searches 3)
                           :batch-size batch-size)
            bpn)
  -  (log-msg "Full batches on the whole BPN~%")
  +  (log-msg "Starting full batches on the whole BPN~%")
     (train (make-sampler *training-images*
                          :max-n (* 1 (length *training-images*))
                          :omit-label-p t)
  
positive.code:                           :decay (flt 0.0002) :visible-sampling nil)
           (save-weights *mnist-1-dbn-filename* *dbn/1*)))
    (setq *bpn/1* (unroll-mnist-dbn/1 *dbn/1*))
    (train-mnist-bpn *bpn/1*)
    (save-weights *mnist-1-bpn-filename* *bpn/1*))
  
  
negative.code:       (populate-map-cache *bpn/2* *dbm/2* (concatenate 'vector *training-images*
                                                         *test-images*)
                            :if-exists :error))
      (train-mnist-bpn *bpn/2* :batch-size 10000 :n-epochs 100)
      (save-weights *mnist-2-bpn-filename* *bpn/2*)))
  
  (defmethod negative-phase (batch (trainer mnist-dbm-trainer) bm)
  