What is the reason of such issue in joblib? 'Multiprocessing backed parallel loops cannot be nested below threads, setting n_jobs=1' What should I do to avoid such issue?
Actually I need to implement XMLRPC server which run heavy computation in background thread and report current progress through polling from UI client. It uses scikit-learn which are based on joblib.
P.S.: I've simply changed name of the thread to "MainThread" to avoid such warning and everything looks working good (run in parallel as expected without issues). What might be a problem in future for such workaround?
This seems to be due to this issue in JobLib library. At the moment of writing this seems to be fixed but not released yet. As written in the question, a dirty fix would to rename the main thread back to MainThread:
threading.current_thread().name = 'MainThread'
I had the same warning while doing predictions with sklearn within a thread, using a model I loaded and which was fitted with n_jobs > 1. It appears when you pickle a model it is saved with its parameters, including n_jobs.
To avoid the warning (and potential serialization cost), set n_jobs to 1 when pickling your models:
clf = joblib.load(model_filename).set_params(n_jobs=1)
来源：https://stackoverflow.com/questions/27646052/multiprocessing-backed-parallel-loops-cannot-be-nested-below-threads