Prototype new benchmark design.

  """

  time_start_fitting = time.time()

  train_score = {}

  valid_score = {}

  test_score = {}

  train_score = .0

  valid_score = .0

  test_score = .0

  train_dataset, valid_dataset, test_dataset = all_dataset

  model.fit(train_dataset)

  train_score['user_defined'] = model.evaluate(train_dataset, metric,

  train_score = model.evaluate(train_dataset, metric,

                               transformers)

  valid_score['user_defined'] = model.evaluate(valid_dataset, metric,

  valid_score = model.evaluate(valid_dataset, metric,

                               transformers)

  if test:

    test_score['user_defined'] = model.evaluate(test_dataset, metric,

    test_score = model.evaluate(test_dataset, metric,

                                transformers)

  else:

    test_score['user_defined'] = None

  time_finish_fitting = time.time()

  time_for_running = time_finish_fitting - time_start_fitting