Class BasicBlock

CV/Pytorch_classification/ResNet/model.py:9–38

# 此处定义的块结构是针对resnet18和resnet34这两种结构的，expansion参数表述主分支结构上卷积通道数的变化
# 在18和34两种结构中，每一个基础块结构中，主分支上的通道数事不发生变化的，故expansion=1
class BasicBlock(nn.Module):
    expansion = 1

    def __init__(self, in_channel, out_channel, stride=1, downsample=None, **kwargs):
        super(BasicBlock, self).__init__()
        self.conv1 = nn.Conv2d(in_channels=in_channel, out_channels=out_channel, 
                               kernel_size=3, stride=stride, padding=1, bias=False)
        self.bn1 = nn.BatchNorm2d(out_channel)
        self.relu = nn.ReLU()
        self.conv2 = nn.Conv2d(in_channels=out_channel, out_channels=out_channel,
                               kernel_size=3, stride=1, padding=1, bias=False)
        self.bn2 = nn.BatchNorm2d(out_channel)
        self.downsample = downsample

    def forward(self, x):
        identity = x
        if self.downsample is not None:
            identity  = self.downsample(x)

        out = self.conv1(x)
        out = self.bn1(out)
        out = self.relu(out)

        out = self.conv2(out)
        out = self.bn2(out)
        
        out += identity
        out = self.relu(out)

        return out

class Bottleneck(nn.Module):
    expansion = 4