code: def load(filename, mmap_mode=None):
      """Reconstruct a Python object from a file persisted with joblib.dump.
  
      Parameters
      -----------
      filename: str or pathlib.Path
          The path of the file from which to load the object
      mmap_mode: {None, 'r+', 'r', 'w+', 'c'}, optional
          If not None, the arrays are memory-mapped from the disk. This
          mode has no effect for compressed files. Note that in this
          case the reconstructed object might no longer match exactly
          the originally pickled object.
  
      Returns
      -------
      result: any Python object
          The object stored in the file.
  
      See Also
      --------
      joblib.dump : function to save an object
  
      Notes
      -----
  
      This function can load numpy array files saved separately during the
      dump. If the mmap_mode argument is given, it is passed to np.load and
      arrays are loaded as memmaps. As a consequence, the reconstructed
      object might not match the original pickled object. Note that if the
      file was saved with compression, the arrays cannot be memmaped.
      """
      if Path is not None and isinstance(filename, Path):
          filename = str(filename)
  
      if hasattr(filename, "read"):
          fobj = filename
          filename = getattr(fobj, "name", "")
          with _read_fileobject(fobj, filename, mmap_mode) as fobj:
              obj = _unpickle(fobj)
      else:
          with open(filename, "rb") as f:
              with _read_fileobject(f, filename, mmap_mode) as fobj:
                  if isinstance(fobj, _basestring):
                      # if the returned file object is a string, this means we
                      # try to load a pickle file generated with an version of
                      # Joblib so we load it with joblib compatibility function.
                      return load_compatibility(fobj)
  
                  obj = _unpickle(fobj, filename, mmap_mode)
  
      return obj
  
imports: import pickle
  import os
  import sys
  import warnings
  from .numpy_pickle_utils import _COMPRESSORS
  from .numpy_pickle_utils import BinaryZlibFile
  from .numpy_pickle_utils import Unpickler, Pickler
  from .numpy_pickle_utils import _read_fileobject, _write_fileobject
  from .numpy_pickle_utils import _read_bytes, BUFFER_SIZE
  from .numpy_pickle_compat import load_compatibility
  from .numpy_pickle_compat import NDArrayWrapper
  from .numpy_pickle_compat import ZNDArrayWrapper
  from ._compat import _basestring, PY3_OR_LATER
  from .backports import make_memmap
label_desc: Use image node_id 3 for calling a global function with example usage: load(filename, mmap_mode) and returns: obj, load_compatibility