Skip to content

Split tests for transforms v2 and prototype #7278

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.

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 15 commits into from
Feb 17, 2023
Merged
Show file tree
Hide file tree
Changes from all commits
Commits
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: 14 additions & 1 deletion .circleci/unittest/linux/scripts/run_test.sh
Original file line number Diff line number Diff line change
Expand Up @@ -6,4 +6,17 @@ eval "$(./conda/bin/conda shell.bash hook)"
conda activate ./env

python -m torch.utils.collect_env
pytest --junitxml=test-results/junit.xml -v --durations 20

case "$(uname -s)" in
Darwin*)
# The largest macOS runner is not able to handle the regular test suite plus the transforms v2 tests at the same
# time due to insufficient resources. Thus, we ignore the transforms v2 tests at first and run them in a separate
# step afterwards.
GLOB='test/test_transforms_v2*'
pytest --junitxml=test-results/junit.xml -v --durations 20 --ignore-glob="${GLOB}"
eval "pytest --junitxml=test-results/junit-transforms-v2.xml -v --durations 20 ${GLOB}"
;;
*)
pytest --junitxml=test-results/junit.xml -v --durations 20
;;
esac
3 changes: 2 additions & 1 deletion test/builtin_dataset_mocks.py
Original file line number Diff line number Diff line change
Expand Up @@ -18,7 +18,8 @@
import numpy as np
import pytest
import torch
from datasets_utils import combinations_grid, create_image_file, create_image_folder, make_tar, make_zip
from common_utils import combinations_grid
from datasets_utils import create_image_file, create_image_folder, make_tar, make_zip
from torch.nn.functional import one_hot
from torch.testing import make_tensor as _make_tensor
from torchvision.prototype import datasets
Expand Down
Loading