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b/tsflex/features/feature_collection.py @@ -35,6 +35,12 @@ from .segmenter import StridedRolling, StridedRollingFactory from .utils import _check_start_end_array, _determine_bounds +# This is not needed for multiprocessing on Windows +# if os.name == "nt": # If running on Windows +# # This enables pickling of globals on Windows +# dill.settings["byref"] = True +# dill.settings["recurse"] = True + class FeatureCollection: """Create a FeatureCollection. @@ -260,7 +266,8 @@ def add( self._check_feature_descriptors(skip_none=True) @staticmethod - def _executor(idx: int): + def _executor(zipped): + idx, get_stroll_func = zipped # global get_stroll_func stroll, function = get_stroll_func(idx) return stroll.apply_func(function) @@ -615,11 +622,7 @@ def calculate( ) nb_stroll_funcs = self._get_stroll_feat_length() - if ( - os.name == "nt" - ): # On Windows no multiprocessing is supported, see https://github.com/predict-idlab/tsflex/issues/51 - n_jobs = 1 - elif n_jobs is None: + if n_jobs is None: n_jobs = os.cpu_count() n_jobs = min(n_jobs, nb_stroll_funcs) @@ -629,12 +632,17 @@ def calculate( if show_progress: idxs = tqdm(idxs) try: - calculated_feature_list = [self._executor(idx) for idx in idxs] + calculated_feature_list = [ + self._executor((idx, get_stroll_func)) for idx in idxs + ] except Exception: traceback.print_exc() else: with Pool(processes=n_jobs) as pool: - results = pool.imap_unordered(self._executor, range(nb_stroll_funcs)) + results = pool.imap_unordered( + self._executor, + zip(range(nb_stroll_funcs), [get_stroll_func] * nb_stroll_funcs), + ) if show_progress: results = tqdm(results, total=nb_stroll_funcs) try: