Why use Sequential or not will have different performance?

1

Hi,
All the other settings are the same, why these two methods will get different performance.

class net1(nn.Module):
def __init__(self):
    super(net1, self).__init__()
    self.conv1 = nn.Conv2d(1,16,5,1,2)
    self.conv2 = nn.Conv2d(16,32,5,1,2)
    self.pool1 = nn.MaxPool2d(2)
    self.pool2 = nn.MaxPool2d(2)
    self.fc1 = nn.Linear(32*7*7,10)

def forward(self, x):
    out = F.relu(self.conv1(x))
    out = self.pool1(out)
    out = F.relu(self.conv2(out))
    out = self.pool2(out)

    out = out.view(-1,32*7*7)
    out = F.relu(self.fc1(out))
    return out

class net2(nn.Module):
def __init__(self):
    super(net2, self).__init__()
    self.conv1 = nn.Sequential(
        nn.Conv2d(
            in_channels=1,
            out_channels=16,
            kernel_size=5,
            stride=1,
            padding=2,
        ),
        nn.ReLU(),
        nn.MaxPool2d(kernel_size=2),
    )
    self.conv2 = nn.Sequential(
        nn.Conv2d(16, 32, 5, 1, 2),
        nn.ReLU(),
        nn.MaxPool2d(2),
    )
    self.out = nn.Linear(32 * 7 * 7, 10)

def forward(self, x):
    x = self.conv1(x)
    x = self.conv2(x)
    x = x.view(x.size(0), -1)
    output = self.out(x)
    return output
2

Because unrolled computation is always faster than for-loops.

3

Please explain a bit more.

4

Hi, I am not talking about the speed, these two methods in the accuracy and accuracy are very different, net2 have higher accuracy.