new_contents: #!/usr/bin/env python3
  
  import argparse
  import numpy
  import sys
  import re
  import os
  import os.path
  import tempfile
  
  parser = argparse.ArgumentParser()
  parser.add_argument('model',
                      type=argparse.FileType('rb'),
                      nargs='+',
                      help='path to .mdl to extract plot data from'
                      )
  parser.add_argument('-n', '--names', help='set experiment names', nargs="+")
  parser.add_argument('-s', '--set', help='plot only the given dataset', choices=['training', 'validation'], default='validation')
  parser.add_argument('-k', '--atk', help='plot only accuracy at top-k', type=int, choices=[5, 1], default=1)
  args = parser.parse_args()
  
  i = -1
  for model in args.model:
      i += 1
      try:
          import pickle
          model.seek(0)
          formatver = pickle.load(model)
          if type(formatver) != int:
              formatver = 0
              model.seek(0)
  
          # add imports for unpickle to work
          import lasagne
          import theano
          pickle.load(model)  # state
  
          # the things we actually care about
          epoch = pickle.load(model)
          if args.set == "training":
              vals = pickle.load(model)
              pickle.load(model) # validation
          else:
              pickle.load(model) # training
              vals = pickle.load(model)
  
          if args.atk == 1:
              val = numpy.max([v[1] for v in vals])
          else:
              val = numpy.max([v[2] for v in vals])
  
          num = re.sub(r'^.*?(\d+(\.\d+)?).*$', r'\1', args.names[i])
          print("{}\t{}\t{}\t{}".format(args.names[i], epoch, val, num))
      except EOFError:
          print("Model {} is invalid".format(model.name))
          sys.exit(1)
  
subject: Add script for printing max accuracy across many networks