Skip to content

Fixed failing tests on pytorch nightly using torch.load #3299

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
merged 2 commits into from
Nov 7, 2024
Merged

Fixed failing tests on pytorch nightly using torch.load #3299

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
61b67bb
Fixed failing tests on pytorch nightly using torch.load
vfdev-5 Nov 7, 2024
4b8ada6
Merge branch 'master' into fix-tests-torch-load
vfdev-5 Nov 7, 2024
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
7 changes: 6 additions & 1 deletion tests/ignite/engine/test_deterministic.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -8,6 +8,7 @@
import pytest
import torch
import torch.nn as nn
from packaging.version import Version
from torch.optim import SGD
from torch.utils.data import BatchSampler, DataLoader, RandomSampler

Expand Down Expand Up @@ -737,7 +738,11 @@ def write_data_grads_weights(e):
grad_norms.append([i, total[1]] + out2)

if sd is not None:
sd = torch.load(sd)
if Version(torch.__version__) >= Version("1.13.0"):
kwargs = {"weights_only": False}
else:
kwargs = {}
sd = torch.load(sd, **kwargs)
model.load_state_dict(sd[0])
opt.load_state_dict(sd[1])
from ignite.engine.deterministic import _repr_rng_state
Expand Down
6 changes: 5 additions & 1 deletion tests/ignite/handlers/test_state_param_scheduler.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -295,7 +295,11 @@ def test_torch_save_load(dirname):

filepath = Path(dirname) / "dummy_lambda_state_parameter_scheduler.pt"
torch.save(lambda_state_parameter_scheduler, filepath)
loaded_lambda_state_parameter_scheduler = torch.load(filepath)
if Version(torch.__version__) >= Version("1.13.0"):
kwargs = {"weights_only": False}
else:
kwargs = {}
loaded_lambda_state_parameter_scheduler = torch.load(filepath, **kwargs)

engine1 = Engine(lambda e, b: None)
lambda_state_parameter_scheduler.attach(engine1, Events.EPOCH_COMPLETED)
Expand Down
Loading