code: def load(path, name, raise_on_exception=True):
      """Utility for loading from cache"""
      if isinstance(path, str):
          f = os.path.join(path, name)
          obj = _load(f, raise_on_exception)
      elif isinstance(path, list):
          obj = [tup[1] for tup in path if tup[0] == name]
          if not obj:
              raise ValueError(
                  "No preprocessing pipeline in cache. Auxiliary Transformer "
                  "have not cached pipelines, or cached to another sub-cache."
              )
          elif not len(obj) == 1:
              raise ValueError(
                  "Could not load unique preprocessing pipeline. "
                  "Transformer and/or Learner names are not unique"
              )
          obj = obj[0]
      else:
          raise ValueError("Expected str or list. Got %r" % path)
      return obj
  
file_path: mlens/mlens/parallel/_base_functions.py
imports: from __future__ import division
  import os
  import warnings
  from scipy.sparse import issparse
  import numpy
  from ..utils import pickle_load, pickle_save, load
  from ..utils.exceptions import MetricWarning, ParameterChangeWarning
label_desc: Use image node_id 1 for calling a global function with example usage: load(path, name, raise_on_exception) and returns: obj