class_docstr: Parallel cross-validation engine.
  
  Minimal parallel processing engine. Similar to :class:`ParallelProcessing`,
  but offers less features, only fits the *callers* indexer, and excepts
  no task output.
class_docstr_tok: ["Parallel","cross-validation","engine",".","Minimal","parallel","processing","engine",".","Similar","to",":","class",":","`","ParallelProcessing","`",",","but","offers","less","features",",","only","fits","the","*","callers","*","indexer",",","and","excepts","no","task","output","."]
code: def __init__(self, *args, **kwargs):
      super(ParallelEvaluation, self).__init__(*args, **kwargs)
  
imports: from __future__ import with_statement, division
  import gc
  import os
  import shutil
  import subprocess
  import tempfile
  import warnings
  from abc import ABCMeta, abstractmethod
  import numpy
  from scipy.sparse import issparse, hstack
  from ..None import config
  from ..externals.joblib import Parallel, dump, load
  from ..utils import check_initialized
  from ..utils.exceptions import ParallelProcessingError, ParallelProcessingWarning
  from ..externals.sklearn.validation import check_random_state
label_desc: Use image node_id 1 to create a new ParallelEvaluation object from inherited base classes: BaseProcessor with example: obj = ParallelEvaluation()