multiprocessing_manager#
- class gammapy.utils.parallel.multiprocessing_manager(backend=None, pool_kwargs=None, method=None, method_kwargs=None)[source]#
Bases:
object
Context manager to update the default configuration for multiprocessing.
Only the default configuration will be modified, if class arguments like
n_jobs
andparallel_backend
are set they will overwrite the default configuration.- Parameters:
- backend{‘multiprocessing’, ‘ray’}
Backend to use.
- pool_kwargsdict
Keyword arguments passed to the pool. The number of processes is limited to the number of physical CPUs.
- method{‘starmap’, ‘apply_async’}
Pool method to use.
- method_kwargsdict
Keyword arguments passed to the method
Examples
import gammapy.utils.parallel as parallel from gammapy.estimators import FluxPointsEstimator fpe = FluxPointsEstimator(energy_edges=[1, 3, 10] * u.TeV) with parallel.multiprocessing_manager( backend="multiprocessing", pool_kwargs=dict(processes=2), ): fpe.run(datasets)