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auto updates (#7723)
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Signed-off-by: monai-bot <monai.miccai2019@gmail.com>

Signed-off-by: monai-bot <monai.miccai2019@gmail.com>
Co-authored-by: YunLiu <55491388+KumoLiu@users.noreply.github.com>
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monai-bot and KumoLiu authored Apr 29, 2024
1 parent 4c193ea commit 5650899
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2 changes: 0 additions & 2 deletions monai/networks/nets/resnet.py
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"resnet200",
]


resnet_params = {
# model_name: (block, layers, shortcut_type, bias_downsample, datasets23)
"resnet10": ("basic", [1, 1, 1, 1], "B", False, True),
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"resnet200": ("bottleneck", [3, 24, 36, 3], "B", False, False),
}


logger = logging.getLogger(__name__)


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1 change: 1 addition & 0 deletions tests/test_median_filter.py
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class MedianFilterTestCase(unittest.TestCase):

@parameterized.expand([(torch.ones(1, 1, 2, 3, 5), [1, 2, 4]), (torch.ones(1, 1, 4, 3, 4), 1)]) # 3d_big # 3d
def test_3d(self, input_tensor, radius):
filter = MedianFilter(radius).to(torch.device("cpu:0"))
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1 change: 0 additions & 1 deletion tests/test_resnet.py
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Expand Up @@ -198,7 +198,6 @@
[model, *TEST_CASE_1] for model in [resnet10, resnet18, resnet34, resnet50, resnet101, resnet152, resnet200]
]


CASE_EXTRACT_FEATURES = [
(
{"model_name": "resnet10", "pretrained": True, "spatial_dims": 3, "in_channels": 1},
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