RuntimeError: size mismatch, m1: [512 x 12800], m2: [2048 x 1024] at C

RuntimeError: size mismatch, m1: [512 x 12800], m2: [2048 x 1024] at C
说一下这错误，意思就是m1和m2两个数组尺寸不一样。
为啥不一样，那就看看自己构建的网络是不是有问题
或者传入数据是不是有问题，我的网络少了一层池化层
在self.layer2层少了最后一层。

注意

一定要在每次输出后面标注出来维度，这样就不会容易犯错。

class CNN(nn.Module):
    def __init__(self):
        super(CNN, self).__init__()
        self.layer1 = nn.Sequential(
            nn.Conv2d(1, 16, kernel_size=3),  # 16, 26 ,26
            nn.BatchNorm2d(16),
            nn.ReLU(inplace=True))  # BatchNorm2d 归一化

        self.layer2 = nn.Sequential(
            nn.Conv2d(16, 32, kernel_size=3),  # 32, 24, 24
            nn.BatchNorm2d(32),
            nn.ReLU(inplace=True),
            # nn.MaxPool2d(kernel_size=2, stride=2)
        )  # 32, 12,12     (24-2) /2 +1

        self.layer3 = nn.Sequential(
            nn.Conv2d(32, 64, kernel_size=3),
            nn.BatchNorm2d(64),
            nn.ReLU(inplace=True))

        self.layer4 = nn.Sequential(
            nn.Conv2d(64, 128, kernel_size=3),
            nn.BatchNorm2d(128),
            nn.ReLU(inplace=True),
            nn.MaxPool2d(kernel_size=2, stride=2))

        self.fc = nn.Sequential(
            nn.Linear(128 * 4 * 4, 1024),
            nn.ReLU(inplace=True),
            nn.Linear(1024, 128),
            nn.ReLU(inplace=True),
            nn.Linear(128, 10))

    def forward(self, x):
        x = self.layer1(x)
        x = self.layer2(x)
        x = self.layer3(x)
        x = self.layer4(x)
        x = x.view(x.size(0), -1)
        x = self.fc(x)
        return x