code: public double score(DataSet data, boolean training) {
          try{
              return scoreHelper(data, training);
          } catch (OutOfMemoryError e){
              CrashReportingUtil.writeMemoryCrashDump(this, e);
              throw e;
          }
      }
docs: Sets the input and labels and calculates the score (value of the output layer loss function plus l1/l2 if applicable)
  for the prediction with respect to the true labels<br>
  @param data data to calculate score for
  @param training If true: score during training. If false: score at test time. This can affect the application of
  certain features, such as dropout and dropconnect (which are applied at training time only)
  @return the score (value of the loss function)