From a14a5569628c4b251a134571bc07ee2a2b5f5674 Mon Sep 17 00:00:00 2001 From: Behrooz <3968947+drbeh@users.noreply.github.com> Date: Wed, 19 Apr 2023 12:42:03 -0400 Subject: [PATCH 1/2] remove deprecated arg in torchvision models Signed-off-by: Behrooz <3968947+drbeh@users.noreply.github.com> --- monai/networks/nets/torchvision_fc.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/monai/networks/nets/torchvision_fc.py b/monai/networks/nets/torchvision_fc.py index 6f63a34951..5744d1e207 100644 --- a/monai/networks/nets/torchvision_fc.py +++ b/monai/networks/nets/torchvision_fc.py @@ -114,8 +114,10 @@ def __init__( ): if weights is not None: model = getattr(models, model_name)(weights=weights, **kwargs) + elif pretrained: + model = getattr(models, model_name)(weights="DEFAULT", **kwargs) else: - model = getattr(models, model_name)(pretrained=pretrained, **kwargs) # 'pretrained' deprecated 0.13 + model = getattr(models, model_name)(weights=None, **kwargs) super().__init__( model=model, From 862fe46f67a4cc38d6067506859c8fa0bc13fed2 Mon Sep 17 00:00:00 2001 From: Wenqi Li Date: Thu, 20 Apr 2023 07:57:26 +0100 Subject: [PATCH 2/2] resume previous test cases Signed-off-by: Wenqi Li --- tests/test_dynunet.py | 12 ++++++++++++ 1 file changed, 12 insertions(+) diff --git a/tests/test_dynunet.py b/tests/test_dynunet.py index c37158ded4..247da14b7d 100644 --- a/tests/test_dynunet.py +++ b/tests/test_dynunet.py @@ -19,8 +19,11 @@ from monai.networks import eval_mode from monai.networks.nets import DynUNet +from monai.utils import optional_import from tests.utils import assert_allclose, skip_if_no_cuda, skip_if_windows, test_script_save +InstanceNorm3dNVFuser, _ = optional_import("apex.normalization", name="InstanceNorm3dNVFuser") + device = "cuda" if torch.cuda.is_available() else "cpu" strides: Sequence[Sequence[int] | int] @@ -125,6 +128,15 @@ def test_script(self): @skip_if_no_cuda @skip_if_windows class TestDynUNetWithInstanceNorm3dNVFuser(unittest.TestCase): + def setUp(self): + try: + layer = InstanceNorm3dNVFuser(num_features=1, affine=False).to("cuda:0") + inp = torch.randn([1, 1, 1, 1, 1]).to("cuda:0") + out = layer(inp) + del inp, out, layer + except Exception: + self.skipTest("NVFuser not available") + @parameterized.expand([TEST_CASE_DYNUNET_3D[0]]) def test_consistency(self, input_param, input_shape, _): for eps in [1e-4, 1e-5]: