code: public INDArray scoreExamples(DataSet data, boolean addRegularizationTerms) {
          if (numInputArrays != 1 || numOutputArrays != 1)
              throw new UnsupportedOperationException("Cannot score ComputationGraph network with "
                      + " DataSet: network does not have 1 input and 1 output arrays");
          return scoreExamples(ComputationGraphUtil.toMultiDataSet(data), addRegularizationTerms);
      }
docs: Calculate the score for each example in a DataSet individually. Unlike {@link #score(DataSet)} and {@link #score(DataSet, boolean)}
  this method does not average/sum over examples. This method allows for examples to be scored individually (at test time only), which
  may be useful for example for autoencoder architectures and the like.<br>
  Each row of the output (assuming addRegularizationTerms == true) is equivalent to calling score(DataSet) with a single example.
  
  @param data                   The data to score
  @param addRegularizationTerms If true: add l1/l2 regularization terms (if any) to the score. If false: don't add regularization terms
  @return An INDArray (column vector) of size input.numRows(); the ith entry is the score (loss value) of the ith example