Several services implement numpy generalised universal functions using from numba import guvectorize.
Unless I'm misunderstanding, numba.set_num_threads(PISA_NUM_THREADS) in https://github.com/icecube/pisa/blob/master/pisa/utils/numba_tools.py#L71 is always executed (for the parallel target) only after some involved chain of imports.
For example, take stages/xsec/dis_sys.py, which does not explicitly import from pisa.utils.vectorizer unlike other services (e.g., stages/pid/shift_scale_pid.py).
I believe we reach the line above via from pisa.core.stage import Stage -> from pisa.core.container import ContainerSet -> from pisa.core.translation import histogram, lookup, resample -> from pisa.utils import vectorizer -> from pisa.utils.numba_tools import cuda_copy :sweat_smile:
Since all services import the Stage base class, it always seems to work out fine, but shouldn't we attempt to call numba.set_num_threads already upon initialising the pisa package (in particular, given that numba is an install requirement now)?
Several services implement numpy generalised universal functions using
from numba import guvectorize. Unless I'm misunderstanding,numba.set_num_threads(PISA_NUM_THREADS)in https://github.com/icecube/pisa/blob/master/pisa/utils/numba_tools.py#L71 is always executed (for the parallel target) only after some involved chain of imports.For example, take
stages/xsec/dis_sys.py, which does not explicitly import frompisa.utils.vectorizerunlike other services (e.g.,stages/pid/shift_scale_pid.py). I believe we reach the line above viafrom pisa.core.stage import Stage->from pisa.core.container import ContainerSet->from pisa.core.translation import histogram, lookup, resample->from pisa.utils import vectorizer->from pisa.utils.numba_tools import cuda_copy:sweat_smile:Since all services import the
Stagebase class, it always seems to work out fine, but shouldn't we attempt to callnumba.set_num_threadsalready upon initialising the pisa package (in particular, given that numba is an install requirement now)?