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Remove hard coding of bias_downsample in resnet methods #6848

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merged 2 commits into from
Aug 10, 2023
Merged

Remove hard coding of bias_downsample in resnet methods #6848

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0216067
Remove hardcoded flag
surajpaib Aug 10, 2023
0278491
Merge branch 'dev' into dev
surajpaib Aug 10, 2023
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4 changes: 3 additions & 1 deletion monai/networks/nets/resnet.py
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Original file line number Diff line number Diff line change
Expand Up @@ -333,14 +333,16 @@ def _resnet(
progress: bool,
**kwargs: Any,
) -> ResNet:
model: ResNet = ResNet(block, layers, block_inplanes, bias_downsample=not pretrained, **kwargs)
model: ResNet = ResNet(block, layers, block_inplanes, **kwargs)
if pretrained:
# Author of paper zipped the state_dict on googledrive,
# so would need to download, unzip and read (2.8gb file for a ~150mb state dict).
# Would like to load dict from url but need somewhere to save the state dicts.
raise NotImplementedError(
"Currently not implemented. You need to manually download weights provided by the paper's author"
" and load then to the model with `state_dict`. See https://github.com/Tencent/MedicalNet"
"Please ensure you pass the appropriate `shortcut_type` and `bias_downsample` args. as specified"
"here: https://github.com/Tencent/MedicalNet/tree/18c8bb6cd564eb1b964bffef1f4c2283f1ae6e7b#update20190730"
)
return model

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