recover changes

        feed_dict[self._training_placeholder] = 0.0

        feed_results = self.session.run(outputs, feed_dict=feed_dict)

        if len(feed_results) > 1:

          result = undo_transforms(np.stack(feed_results, 1), transformers)

          feed_results = [result[:, i] for i in range(result.shape[1])]

          if len(transformers):

            raise ValueError("Does not support transformations "

                             "for multiple outputs.")  

        elif len(feed_results) == 1:

          result = undo_transforms(feed_results[0], transformers)

          feed_results = [result]

"""

import sys

def classification_table_to_csv(lines):

  output = []

  headers = [

    output.append(",".join([split, dataset, model, train, test]))

  for l in output:

    print(l)

  #with open('desired_results.csv', 'a') as f:

  #  for l in output:

  #    f.write(l + '\n')

def regression_table_to_csv(lines):

    output.append(",".join([split, dataset, model, train, test]))

  for l in output:

    print(l)

  #with open('desired_results.csv', 'a') as f:

  #  for l in output:

  #    f.write(l + '\n')

def split_classification_regression(lines):