anchor.diff:  (defun init-bpn-lump-weights (name bpn stddev)
     (gaussian-random! (nodes (find-lump name bpn :errorp t)) :stddev stddev))
   
  -(defun train-mnist-bpn (bpn training test &key
  -                        (batch-size (min (length training) 1000))
  -                        (n-softmax-epochs 5) n-epochs)
  +(defun train-mnist-bpn-cg (bpn training test &key
  +                           (batch-size (min (length training) 1000))
  +                           (n-softmax-epochs 5) n-epochs)
     (log-msg "Starting to train the softmax layer of BPN~%")
     (train (make-sampler training :n-epochs n-softmax-epochs :omit-label-p t)
            (make-instance 'mnist-cg-bp-trainer
  
positive.code:              (unless quick-run-p
                 (save-weights bpn-filename bpn)))
              (t
               (train-mnist-bpn bpn training test :batch-size 10000
                                :n-softmax-epochs (if quick-run-p 1 5)
                                :n-epochs (if quick-run-p 1 100))
               (unless quick-run-p
                 (save-weights bpn-filename bpn)))))))
  
  
negative.code:            (unless quick-run-p
               (save-weights bpn-filename bpn)))
            (t
             (train-mnist-bpn-cg bpn training test
                                 :n-softmax-epochs (if quick-run-p 1 5)
                                 :n-epochs (if quick-run-p 1 37))
             (unless quick-run-p
               (save-weights bpn-filename bpn))))
      (values bpn dbn)))
  