Skip to content

Add generator and worker seed #8602

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

Merged
glenn-jocher merged 6 commits into from
Jul 22, 2022
Merged

Add generator and worker seed #8602

Changes from all commits
Commits
Show all changes
6 commits
Select commit Hold shift + click to select a range
284eab6
Add generator and worker seed
UnglvKitDe Jul 16, 2022
a01894f
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Jul 16, 2022
3bd609b
Merge branch 'master' into new_feature/rseed_worker
glenn-jocher Jul 22, 2022
2660752
Update dataloaders.py
glenn-jocher Jul 22, 2022
5fc1067
Update dataloaders.py
glenn-jocher Jul 22, 2022
5992a7f
Update dataloaders.py
glenn-jocher Jul 22, 2022
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
13 changes: 12 additions & 1 deletion utils/dataloaders.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -91,6 +91,13 @@ def exif_transpose(image):
return image


def seed_worker(worker_id):
# Set dataloader worker seed https://pytorch.org/docs/stable/notes/randomness.html#dataloader
worker_seed = torch.initial_seed() % 2 ** 32
np.random.seed(worker_seed)
random.seed(worker_seed)


def create_dataloader(path,
imgsz,
batch_size,
Expand Down Expand Up @@ -130,13 +137,17 @@ def create_dataloader(path,
nw = min([os.cpu_count() // max(nd, 1), batch_size if batch_size > 1 else 0, workers]) # number of workers
sampler = None if rank == -1 else distributed.DistributedSampler(dataset, shuffle=shuffle)
loader = DataLoader if image_weights else InfiniteDataLoader # only DataLoader allows for attribute updates
generator = torch.Generator()
generator.manual_seed(0)
return loader(dataset,
batch_size=batch_size,
shuffle=shuffle and sampler is None,
num_workers=nw,
sampler=sampler,
pin_memory=True,
collate_fn=LoadImagesAndLabels.collate_fn4 if quad else LoadImagesAndLabels.collate_fn), dataset
collate_fn=LoadImagesAndLabels.collate_fn4 if quad else LoadImagesAndLabels.collate_fn,
worker_init_fn=seed_worker,
generator=generator), dataset


class InfiniteDataLoader(dataloader.DataLoader):
Expand Down