class_docstr: Reducer callable to dump large arrays to memmap files.
  
  Parameters
  ----------
  max_nbytes: int
      Threshold to trigger memmaping of large arrays to files created
      a folder.
  temp_folder: str
      Path of a folder where files for backing memmaped arrays are created.
  mmap_mode: 'r', 'r+' or 'c'
      Mode for the created memmap datastructure. See the documentation of
      numpy.memmap for more details. Note: 'w+' is coerced to 'r+'
      automatically to avoid zeroing the data on unpickling.
  verbose: int, optional, 0 by default
      If verbose > 0, memmap creations are logged.
      If verbose > 1, both memmap creations, reuse and array pickling are
      logged.
  prewarm: bool, optional, False by default.
      Force a read on newly memmaped array to make sure that OS pre-cache it
      memory. This can be useful to avoid concurrent disk access when the
      same data array is passed to different worker processes.
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code: def __init__(
      self,
      max_nbytes,
      temp_folder,
      mmap_mode,
      verbose=0,
      context_id=None,
      prewarm=True,
  ):
      self._max_nbytes = max_nbytes
      self._temp_folder = temp_folder
      self._mmap_mode = mmap_mode
      self.verbose = int(verbose)
      self._prewarm = prewarm
      if context_id is not None:
          warnings.warn(
              "context_id is deprecated and ignored in joblib"
              " 0.9.4 and will be removed in 0.11",
              DeprecationWarning,
          )
  
imports: from mmap import mmap
  import errno
  import os
  import stat
  import sys
  import threading
  import atexit
  import tempfile
  import shutil
  import warnings
  from time import sleep
  from pickle import whichmodule
  from pickle import Pickler
  from pickle import HIGHEST_PROTOCOL
  from io import BytesIO
  from ._multiprocessing_helpers import mp, assert_spawning
  from multiprocessing.pool import Pool
  from .numpy_pickle import load
  from .numpy_pickle import dump
  from .hashing import hash
label_desc: Use image node_id 1 to create a new ArrayMemmapReducer object from inherited base classes: object with example: obj = ArrayMemmapReducer(max_nbytes, temp_folder, mmap_mode, verbose, context_id, prewarm)