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성만쌤 확인 사항
@Sungman-Cho
- arguments로 attention block (e.g. non-local block) 추가
- arguments로 weight standardization 추가
- weight standardization 추가된 conv 부분 (nnunet/network_architecture/generic_UNet.py : line 28-40)
class Conv2d(nn.Conv2d):
def __init__(self, in_channels, output_channels, kernel_size, stride=1,
padding=0, dilation=1, groups=1, bias=True):
super(Conv2d, self).__init__(in_channels, output_channels, kernel_size, stride, padding,
dilation, groups, bias)
def forward(self, x):
weight = self.weight
weight_mean = weight.mean(dim=1, keepdim=True).mean(dim=2, keepdim=True).mean(dim=3, keepdim=True)
weight = weight - weight_mean
std = weight.view(weight.size(0), -1).std(dim=1).view(-1,1,1,1) + 1e-5
weight = weight / std.expand_as(weight)
return F.conv2d(x, weight, self.bias, self.stride, self.padding, self.dilation, self.groups) <--------
화살표 부분에 F.conv2d로 되어있는데, 코드 상에서 F를 불러오는 부분이 없습니다.
import torch.nn.functional
정도로만 되어 있네욤 (line 23)
다른 부분에서는 nn.Conv2d
으로 불러오는데 확인좀요!
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