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Merged
justinchuby merged 9 commits into from
Dec 29, 2025
Merged

Update build-and-test.yml #214

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a6aa133
Update build-and-test.yml
andife Oct 3, 2025
4a069ef
Update build-and-test.yml
andife Oct 3, 2025
f393245
Update Python versions in build matrix
andife Dec 22, 2025
a3a4e22
Merge branch 'main' into andife-patch-8
andife Dec 22, 2025
12b8c05
Merge branch 'main' into andife-patch-8
andife Dec 29, 2025
d36127d
Merge branch 'main' into andife-patch-8
andife Dec 29, 2025
faaf920
Update torch with cp314 support (#225)
take-cheeze Dec 29, 2025
2be966e
Update optimizer_test.py
justinchuby Dec 29, 2025
78a3bac
Update build matrix to exclude Python 'cp314'
andife Dec 29, 2025
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10 changes: 1 addition & 9 deletions .github/workflows/build-and-test.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -25,7 +25,7 @@ jobs:
CIBW_TEST_REQUIRES_LINUX: pytest pytest-xdist flake8-pyproject mypy onnxruntime
CIBW_TEST_REQUIRES_MACOS: pytest pytest-xdist
CIBW_TEST_REQUIRES_WINDOWS: pytest pytest-xdist
CIBW_BEFORE_TEST_LINUX: pip install torch==2.6.0+cpu torchvision==0.21.0+cpu --index-url https://download.pytorch.org/whl/cpu
CIBW_BEFORE_TEST_LINUX: pip install onnxscript torch==2.9.1 torchvision==0.24.1
CIBW_TEST_COMMAND: pytest {project}/onnxoptimizer/test
CIBW_TEST_COMMAND_LINUX: cd {project} && flake8p && pytest
CIBW_TEST_SKIP: " *_arm64"
Expand Down Expand Up @@ -94,14 +94,6 @@ jobs:
with:
name: artifact
path: dist

# TODO: get acccess for test.pypi
# - name: Publish distribution 📦 to Test PyPI
# uses: pypa/gh-action-pypi-publish@release/v1
# with:
# repository-url: https://test.pypi.org/legacy/
# skip-existing: true
# attestations: true

- name: Publish distribution 📦 to PyPI
if: startsWith(github.ref, 'refs/tags/v')
Expand Down
36 changes: 18 additions & 18 deletions onnxoptimizer/test/optimizer_test.py
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Expand Up @@ -4204,34 +4204,34 @@ def test_split_predict_and_lift_lexical_references_for_caffe2_backend(self):
@unittest.skipUnless(has_tv, "This test needs torchvision")
def test_torchvision_fasterrcnn_fpn(self): # type: () -> None
model = tv.models.detection.fasterrcnn_resnet50_fpn(pretrained=False)
x = [torch.rand(3, 300, 400), torch.rand(3, 500, 400)]
x = (torch.rand(3, 300, 400), torch.rand(3, 500, 400))
with io.BytesIO() as f:
torch.onnx.export(model, x, f, opset_version=11)
torch.onnx.export(model, x, f, opset_version=18)
model = onnx.load_model_from_string(f.getvalue())
self._optimized(
model, onnxoptimizer.get_fuse_and_elimination_passes(), fixed_point=True
)

# maskrcnn is only supported in opset 11 and higher
@unittest.skipUnless(has_tv, "This test needs torchvision")
def test_torchvision_maskrcnn_fpn_opset11(self): # type: () -> None
model = tv.models.detection.maskrcnn_resnet50_fpn(pretrained=False)
x = [torch.rand(3, 300, 400), torch.rand(3, 500, 400)]
with io.BytesIO() as f:
torch.onnx.export(model, x, f, opset_version=11)
model = onnx.load_model_from_string(f.getvalue())
self._optimized(
model, onnxoptimizer.get_fuse_and_elimination_passes(), fixed_point=True
)
# # maskrcnn is only supported in opset 11 and higher
# @unittest.skipUnless(has_tv, "This test needs torchvision")
# def test_torchvision_maskrcnn_fpn_opset11(self): # type: () -> None
# model = tv.models.detection.maskrcnn_resnet50_fpn(pretrained=False)
# x = (torch.rand(3, 300, 400), torch.rand(3, 500, 400))
# with io.BytesIO() as f:
# torch.onnx.export(model, x, f, dynamo=False)
# model = onnx.load_model_from_string(f.getvalue())
# self._optimized(
# model, onnxoptimizer.get_fuse_and_elimination_passes(), fixed_point=True
# )

# keypointrcnn is only supported in opset 11 and higher
@pytest.mark.xfail
@unittest.skipUnless(has_tv, "This test needs torchvision")
def test_torchvision_keypointrcnn_fpn(self): # type: () -> None
model = tv.models.detection.keypointrcnn_resnet50_fpn(pretrained=False)
x = [torch.rand(3, 300, 400), torch.rand(3, 500, 400)]
x = (torch.rand(3, 300, 400), torch.rand(3, 500, 400))
with io.BytesIO() as f:
torch.onnx.export(model, x, f, opset_version=11)
torch.onnx.export(model, x, f, opset_version=18)
model = onnx.load_model_from_string(f.getvalue())
self._optimized(
model, onnxoptimizer.get_fuse_and_elimination_passes(), fixed_point=True
Expand All @@ -4242,7 +4242,7 @@ def test_torchvision_shufflenet_v2(self): # type: () -> None
model = tv.models.shufflenet_v2_x1_0(pretrained=False)
x = torch.rand(1, 3, 224, 224)
with io.BytesIO() as f:
torch.onnx.export(model, x, f)
torch.onnx.export(model, x, f, dynamo=False)
model = onnx.load_model_from_string(f.getvalue())
self._optimized(
model, onnxoptimizer.get_fuse_and_elimination_passes(), fixed_point=True
Expand All @@ -4253,7 +4253,7 @@ def test_torchvision_mnasnet(self): # type: () -> None
model = tv.models.mnasnet1_0(pretrained=False)
x = torch.rand(1, 3, 224, 224)
with io.BytesIO() as f:
torch.onnx.export(model, x, f)
torch.onnx.export(model, x, f, dynamo=False)
model = onnx.load_model_from_string(f.getvalue())
self._optimized(
model, onnxoptimizer.get_fuse_and_elimination_passes(), fixed_point=True
Expand All @@ -4264,7 +4264,7 @@ def test_torchvision_deeplabv3(self): # type: () -> None
model = tv.models.segmentation.deeplabv3_resnet50(pretrained=False)
x = torch.rand(1, 3, 224, 224)
with io.BytesIO() as f:
torch.onnx.export(model, x, f)
torch.onnx.export(model, x, f, dynamo=False)
model = onnx.load_model_from_string(f.getvalue())
self._optimized(
model, onnxoptimizer.get_fuse_and_elimination_passes(), fixed_point=True
Expand Down
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