class_docstr: Benchmark engine without hyper-parameter grid search.
  
  A simplified version of the :class:`Evaluator` that performs a single
  pass over a set of estimators and preprocessing pipelines for
  benchmarking purposes.
  
  .. versionadded:: 0.2.0
  
  Parameters
  ----------
  verbose : bool, int, optional
      Verbosity during estimation.
  
  **kwargs : optional
      Optional keyword argument to :class:`~mlens.parallel.base.BaseBackend`.
code: def __init__(self, verbose=False, **kwargs):
      super(Benchmark, self).__init__(verbose=verbose, **kwargs)
      self.results = None
      self.indexer = None
  
imports: from __future__ import division, with_statement
  import warnings
  import numpy
  from ._base_functions import parse_key, set_job, cat, check_scorer, make_learners, make_tansformers, check_instances
  from ..index import FoldIndex
  from ..parallel import ParallelEvaluation
  from ..parallel.base import BaseBackend, IndexMixin
  from ..metrics import Data, assemble_data
  from ..utils.formatting import _flatten, _check_instances
  from ..utils import print_time, safe_print, assert_correct_format
  from ..externals.joblib import delayed
  from ..externals.sklearn.base import clone
label_desc: Use image node_id 1 to create a new Benchmark object from inherited base classes: BaseEval with example: obj = Benchmark(verbose)