Skip to content

More efficient multiprocessing for computing MI #2

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
CorentinJ wants to merge 1 commit into
base: master
Choose a base branch
from
Open

More efficient multiprocessing for computing MI #2

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
15 changes: 10 additions & 5 deletions ital/ital.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -117,17 +117,22 @@ def fetch_unlabelled(self, k, show_progress = False):
# Greedy batch construction
mutual_information = AppendedMutualInformation(self)
steps = trange(k) if show_progress else range(k)

if self.parallelized:
pool = Pool(initializer=_init_pool, initargs=(mutual_information,))

for it in steps:

if self.parallelized and (it > 0):
with Pool(initializer = _init_pool, initargs = (mutual_information,)) as p:
mi = p.map(_parallel_mi, candidates)
mi = pool.map(_parallel_mi, candidates)
else:
mi = [mutual_information(i) for i in candidates]

max_ind = np.argmax(mi)
mutual_information.append(candidates[max_ind])
del candidates[max_ind]

if self.parallelized:
pool.close()

return mutual_information.ret

Expand Down Expand Up @@ -620,4 +625,4 @@ def _init_pool(mi):


def _parallel_mi(i):
return _mi(i)
return _mi(i)