anchor.diff:                                           status-function
                                            randomize-weights)
             with start-time = (get-universal-time)
  -          with last-report-time
  -          with rf = (* (/ report-frequency 1000)
  -                       internal-time-units-per-second)
  +          with time-span-between-reports =
  +            (truncate (* (/ report-frequency 1000.0)
  +                         internal-time-units-per-second))
             for i from 1 to max-iterations
  -          for mse = 1.0 then (present-vectors net t-set)
  +          for mse = 1.0 then (present-vectors 
  +                              net t-set
  +                              i
  +                              start-time
  +                              report-function
  +                              time-span-between-reports)
             while (and (> mse target-mse) (not (stop-training net)))
             when (or
                   (and (> i 1)
  
positive.code:                 (shock net))
            do (shock-weights net target-mse mse rerandomize-weights
                              randomize-weights logger-function annealing i)
            when (and report-function
                      (or (not last-report-time)
                          (>= (- (get-internal-real-time) last-report-time) rf)))
            do (funcall report-function
                        :net net
                        :elapsed (elapsed start-time)
                        :iteration i
                        :mse mse)
              (setf last-report-time (get-internal-real-time))
            finally (let ((elapsed (elapsed start-time))
                          (status (if (> mse target-mse) "maxi" "target")))
                      (when report-function
  
negative.code:    (randomize :accessor randomize :type boolean :initform nil)
     (anneal :accessor anneal :type boolean :initform nil)
     (stop-training :accessor stop-training :type boolean :initform nil)
     (shock :accessor shock :type boolean :initform nil)
     (last-report-time :accessor last-report-time :type integer :initform nil))
    (:documentation "Describes a standard multilayer, fully-connected backpropagation neural network."))
  
  (defmethod output-layer ((net t-net))
  