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Zero-init the residual branch in resnet #498

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Merged
fmassa merged 3 commits into from
Dec 6, 2018
Merged

Zero-init the residual branch in resnet #498

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b2cc15b
Zero-init the residual branch in resnet
ppwwyyxx May 11, 2018
f21b41f
Add zero_init_residual as an option
ppwwyyxx Jul 8, 2018
dbff743
Merge branch 'master' into master
ppwwyyxx Nov 26, 2018
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12 changes: 11 additions & 1 deletion torchvision/models/resnet.py
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Original file line number Diff line number Diff line change
Expand Up @@ -98,7 +98,7 @@ def forward(self, x):

class ResNet(nn.Module):

def __init__(self, block, layers, num_classes=1000):
def __init__(self, block, layers, num_classes=1000, zero_init_residual=False):
super(ResNet, self).__init__()
self.inplanes = 64
self.conv1 = nn.Conv2d(3, 64, kernel_size=7, stride=2, padding=3,
Expand All @@ -120,6 +120,16 @@ def __init__(self, block, layers, num_classes=1000):
nn.init.constant_(m.weight, 1)
nn.init.constant_(m.bias, 0)

# Zero-initialize the last BN in each residual branch,
# so that the residual branch starts with zeros, and each residual block behaves like an identity.
# This improves the model by 0.2~0.3% according to https://arxiv.org/abs/1706.02677
if zero_init_residual:
for m in self.modules():
if isinstance(m, Bottleneck):
nn.init.constant_(m.bn3.weight, 0)
elif isinstance(m, BasicBlock):
nn.init.constant_(m.bn2.weight, 0)

def _make_layer(self, block, planes, blocks, stride=1):
downsample = None
if stride != 1 or self.inplanes != planes * block.expansion:
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