resnext.py 文件源码

def _make_layer(self, block, planes, blocks, stride=1,
                    batch_norm=True):
        downsample = None
        if self.shortcut == 'C' or \
                self.shortcut == 'B' and \
                (stride != 1 or self.inplanes != planes * block.expansion):
            downsample = [nn.Conv2d(self.inplanes, planes * block.expansion,
                                    kernel_size=1, stride=stride, bias=not batch_norm)]
            if batch_norm:
                downsample.append(nn.BatchNorm2d(planes * block.expansion))
            downsample = nn.Sequential(*downsample)
        else:
            downsample = PlainDownSample(
                self.inplanes, planes * block.expansion, stride)

        layers = []
        layers.append(block(self.inplanes, planes,
                            stride, downsample, batch_norm))
        self.inplanes = planes * block.expansion
        for i in range(1, blocks):
            layers.append(block(self.inplanes, planes, batch_norm=batch_norm))

        return nn.Sequential(*layers)