anchor.diff:  (defmethod learning-rate ((trainer mnist-dbm-segment-trainer))
     ;; This is adjusted for each batch. Ruslan's code adjusts it per
     ;; epoch.
  +  ;; FIXME: min 0.0001
     (/ (slot-value trainer 'learning-rate)
        (expt 1.000015 (* (/ (n-inputs trainer)
                             (length *training-images*))
  
positive.code:                                                     (length *test-images*))
                                        dbm))
             (n-inputs trainer))
    (let ((counters-and-measurers
           (make-bm-reconstruction-misclassification-counters-and-measurers dbm)))
      (when counters-and-measurers
  
negative.code:                         :n-gibbs 5
                          :segmenter
                          (lambda (cloud)
                            (when (or t (equal 'label (name (chunk1 cloud)))
                                      (equal 'label (name (chunk2 cloud))))
                              (make-instance 'mnist-dbm-segment-trainer
                                             :learning-rate (flt 0.001)
                                             :weight-decay
                                             (if (bias-cloud-p cloud)
                                                 (flt 0)
                                                 (flt 0.0002))
                                             :batch-size 100)))
                          :sparser
                          (lambda (cloud chunk)
                            (when (and (member (name chunk) '(f1 f2))
  