code: def print_job(lc, start_message):
      """Print job details.
  
      Parameters
      ----------
      lc : :class:`Sequential`
          The LayerContainer instance running the job.
  
      start_message : str
          Initial message.
      """
      f = "stdout" if lc.verbose < 10 else "stderr"
      if lc.verbose:
          safe_print(
              "\n%s %d layers" % (start_message, len(lc.stack)),
              file=f,
              flush=True,
          )
          if lc.verbose >= 5:
              safe_print(
                  """[INFO] n_jobs = %i
  [INFO] backend = %r
  [INFO] start_method = %r
  [INFO] cache = %r
  """
                  % (
                      lc.n_jobs,
                      lc.backend,
                      config.get_start_method(),
                      config.get_tmpdir(),
                  ),
                  file=f,
                  flush=True,
              )
  
      t0 = time()
      return f, t0
  
imports: from __future__ import division, print_function, with_statement
  from abc import ABCMeta, abstractmethod
  import warnings
  from ..None import config
  from ..parallel import Layer, ParallelProcessing, make_group
  from ..parallel.base import BaseStacker
  from ..externals.sklearn.validation import check_random_state
  from ..utils import check_ensemble_build, print_time, safe_print, IdTrain, format_name
  from ..utils.exceptions import LayerSpecificationWarning, NotFittedError, NotInitializedError
  from ..metrics import Data
  from ..externals.sklearn.base import BaseEstimator, clone
label_desc: Use image node_id 2 for calling a global function with example usage: print_job(lc, start_message) and returns: f,  t0