code: def _cpu_map(fun, param_grid, n_jobs, verbose):
      return Parallel(
          n_jobs=n_jobs,
          verbose=verbose,
          backend="threading",  # any sklearn backend should work here
      )(delayed(fun)(params) for params in param_grid)
  
file_path: skggm/inverse_covariance/profiling/monte_carlo_profile.py
imports: from __future__ import absolute_import
  import numpy
  from functools import partial
  from sklearn.base import clone
  from joblib import Parallel, delayed
  from .metrics import error_fro
  from .erdos_renyi_graph import ErdosRenyiGraph
  from ..None import QuicGraphicalLasso, QuicGraphicalLassoCV
label_desc: Use image node_id 4 for calling a global function with example usage: _cpu_map(fun, param_grid, n_jobs, verbose) and returns: Parallel