code: def effective_n_jobs(self, n_jobs):
      eff_n_jobs = super(MarsDistributedBackend, self).effective_n_jobs(
          n_jobs
      )
      if n_jobs == -1 or not eff_n_jobs:
          eff_n_jobs = self.n_parallel
      return eff_n_jobs
  
file_path: mars/mars/learn/contrib/joblib/backend.py
imports: import concurrent.futures
  from ....None import remote
  from ....session import get_default_session, new_session
label_desc: Use image node_id 4 for calling the MarsDistributedBackend obj's underlying member method code with example usage: obj.effective_n_jobs(n_jobs) and returns: eff_n_jobs