Port test_onnx.py to pytest

.circleci/config.yml

@@ -257,6 +257,7 @@ jobs:
             pip install --user --progress-bar off --editable .
             pip install --user onnx
             pip install --user onnxruntime
+            pip install --user pytest
             python test/test_onnx.py
 
   binary_linux_wheel:

.circleci/config.yml.in

@@ -257,6 +257,7 @@ jobs:
             pip install --user --progress-bar off --editable .
             pip install --user onnx
             pip install --user onnxruntime
+            pip install --user pytest
             python test/test_onnx.py
 
   binary_linux_wheel:

test/test_onnx.py

@@ -15,21 +15,19 @@
 from torchvision.models.detection.image_list import ImageList
 from torchvision.models.detection.transform import GeneralizedRCNNTransform
 from torchvision.models.detection.rpn import AnchorGenerator, RPNHead, RegionProposalNetwork
-from torchvision.models.detection.backbone_utils import resnet_fpn_backbone
 from torchvision.models.detection.roi_heads import RoIHeads
 from torchvision.models.detection.faster_rcnn import FastRCNNPredictor, TwoMLPHead
-from torchvision.models.detection.mask_rcnn import MaskRCNNHeads, MaskRCNNPredictor
 
 from collections import OrderedDict
 
-import unittest
+import pytest
 from torchvision.ops._register_onnx_ops import _onnx_opset_version
 
 
-@unittest.skipIf(onnxruntime is None, 'ONNX Runtime unavailable')
-class ONNXExporterTester(unittest.TestCase):
+@pytest.mark.skipif(onnxruntime is None, reason='ONNX Runtime unavailable')
+class TestONNXExporter:
     @classmethod
-    def setUpClass(cls):
+    def setup_class(cls):
         torch.manual_seed(123)
 
     def run_model(self, model, inputs_list, tolerate_small_mismatch=False, do_constant_folding=True, dynamic_axes=None,
@@ -80,7 +78,7 @@ def to_numpy(tensor):
                 torch.testing.assert_allclose(outputs[i], ort_outs[i], rtol=1e-03, atol=1e-05)
             except AssertionError as error:
                 if tolerate_small_mismatch:
-                    self.assertIn("(0.00%)", str(error), str(error))
+                    assert "(0.00%)" in str(error), str(error)
                 else:
                     raise
 
@@ -161,7 +159,7 @@ def test_roi_align_aligned(self):
         model = ops.RoIAlign((2, 2), 2.5, -1, aligned=True)
         self.run_model(model, [(x, single_roi)])
 
-    @unittest.skip  # Issue in exporting ROIAlign with aligned = True for malformed boxes
+    @pytest.mark.skip(reason="Issue in exporting ROIAlign with aligned = True for malformed boxes")
     def test_roi_align_malformed_boxes(self):
         x = torch.randn(1, 1, 10, 10, dtype=torch.float32)
         single_roi = torch.tensor([[0, 2, 0.3, 1.5, 1.5]], dtype=torch.float32)
@@ -527,4 +525,4 @@ def test_shufflenet_v2_dynamic_axes(self):
 
 
 if __name__ == '__main__':
-    unittest.main()
+    pytest.main([__file__])