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@ -165,7 +165,7 @@ class Model(nn.Module):
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# print('%10.3g' % (m.w.detach().sigmoid() * 2)) # shortcut weights
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def fuse(self): # fuse model Conv2d() + BatchNorm2d() layers
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print('Fusing layers... ')
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# print('Fusing layers... ')
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for m in self.model.modules():
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if type(m) is Conv and hasattr(m, 'bn'):
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m.conv = fuse_conv_and_bn(m.conv, m.bn) # update conv
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