class_docstr: Parallel processing base class.
  
  Base class for parallel processing engines.
  
  Parameters
  ----------
  backend: str, optional
      Type of backend. One of ``'threading'``, ``'multiprocessing'``,
      ``'sequential'``.
  
  n_jobs : int, optional
      Degree of concurrency.
  
  verbose: bool, int, optional
      Level of verbosity of the
      :class:`~mlens.externals.joblib.parallel.Parallel` instance.
class_docstr_tok: ["Parallel","processing","base","class",".","Base","class","for","parallel","processing","engines",".","Parameters","--","--","--","--","--","backend",":","str",",","optional","Type","of","backend",".","One","of","``","'threading","'","``",",","``","'multiprocessing","'","``",",","``","'sequential","'","``",".","n_jobs",":","int",",","optional","Degree","of","concurrency",".","verbose",":","bool",",","int",",","optional","Level","of","verbosity","of","the",":","class",":","`","~mlens.externals.joblib.parallel.Parallel","`","instance","."]
docstr: Create a job instance for estimation.
  
  See :func:`~mlens.parallel.backend.BaseProcess.initialize` for
  further details.
docstr_tok: ["Create","a","job","instance","for","estimation",".","See",":","func",":","`","~mlens.parallel.backend.BaseProcess.initialize","`","for","further","details","."]
code: def _initialize(self, job, X, y=None, path=None, **kwargs):
      """Create a job instance for estimation.
  
      See :func:`~mlens.parallel.backend.BaseProcess.initialize` for
      further details.
      """
      job = Job(job, **kwargs)
      job = _set_path(job, path, self.__threading__)
  
      # --- Prepare inputs
      for name, arr in zip(("X", "y"), (X, y)):
          if arr is None:
              continue
  
          # Dump data in cache
          if self.__threading__:
              # No need to memmap
              f = None
              if isinstance(arr, str):
                  arr = _load(arr)
          else:
              f = dump_array(arr, name, job.dir)
  
          # Store data for processing
          if name == "y" and arr is not None:
              job.targets = arr if self.__threading__ else _load_mmap(f)
          elif name == "X":
              job.predict_in = (
                  arr if self.__threading__ else _load_mmap(f)
              )
  
      self.job = job
      self.__initialized__ = 1
      gc.collect()
      return self
  
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 4 for calling the BaseProcessor obj's underlying member method code with example usage: obj._initialize(job, X, y, path) and returns: self