code: def _cpu_map(fun, param_grid, n_jobs, verbose=True):
      return Parallel(
          n_jobs=n_jobs,
          verbose=verbose,
          backend="threading",  # any sklearn backend should work here
      )(delayed(fun)(params) for params in param_grid)
  
imports: from __future__ import absolute_import
  import numpy
  from sklearn.base import BaseEstimator, clone
  from sklearn.utils import check_array, as_float_array
  from joblib import Parallel, delayed
  from functools import partial
  from .inverse_covariance import _init_coefs
  from .None import QuicGraphicalLasso
label_desc: Use image node_id 7 for calling a global function with example usage: _cpu_map(fun, param_grid, n_jobs, verbose) and returns: Parallel