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Fix batchnorm shapes for resnet.load_pretrained (#5167) 

* Fix batchnorm shapes

* make it general reshape
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reddyn12 2024-06-26 18:44:10 -04:00 committed by GitHub
parent 396ce6cfc9
commit f1c7944c44
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1 changed files with 3 additions and 6 deletions
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extra/models/resnet.py
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@ -146,15 +146,12 @@ class ResNet:
print("skipping fully connected layer")
continue # Skip FC if transfer learning
if dat.shape == ():
assert obj.shape == (1,), obj.shape
dat = dat.reshape(1)
assert obj.shape == dat.shape, (k, obj.shape, dat.shape)
obj.assign(dat)
if 'bn' not in k and 'downsample' not in k: assert obj.shape == dat.shape, (k, obj.shape, dat.shape)
obj.assign(dat.reshape(obj.shape))
ResNet18 = lambda num_classes=1000: ResNet(18, num_classes=num_classes)
ResNet34 = lambda num_classes=1000: ResNet(34, num_classes=num_classes)
ResNet50 = lambda num_classes=1000: ResNet(50, num_classes=num_classes)
ResNet101 = lambda num_classes=1000: ResNet(101, num_classes=num_classes)
ResNet152 = lambda num_classes=1000: ResNet(152, num_classes=num_classes)
ResNeXt50_32X4D = lambda num_classes=1000: ResNet(50, num_classes=num_classes, groups=32, width_per_group=4)
ResNeXt50_32X4D = lambda num_classes=1000: ResNet(50, num_classes=num_classes, groups=32, width_per_group=4)