Basically like this:
def feature_extractor(x, extractor):
    out = extractor(x)
    return out

class MODEL(nn.Module):
    def __init__(self):
        super().__init__()
        self.conv1 = nn.Conv2d(3,32,kernel_size = 3,padding = 1)
        self.bn1 = nn.BatchNorm2d(32)
        self.pooling1 = nn.MaxPool2d(2,2)
        self.conv2 = nn.Conv2d(32,64,kernel_size = 3,padding = 1)
        self.bn2 = nn.BatchNorm2d(64)
        self.pooling2 = nn.MaxPool2d(2,2)
        self.extra_conv1 =feature_extractor
    
    def forward(self,x):
        x = self.conv1(x)
        x = self.bn1(x)
        x = F.relu(x)
        x = self.extra_conv1(x)
        x = self.pooling1(x)
        x = self.conv2(x)
        x = self.bn2(x)
        x = F.relu(x)
        x = self.pooling2(x)
        return x

extractor = nn.Conv2d(32, 32, kernel_size = 3,padding = 1)
model = MODEL()