Hello, I have learn the tensorboard with tensorboard_tutorial,there is a class Net, the official code as following:
class Net(nn.Module):
def __init__(self):
super(Net, self).__init__()
self.conv1 = nn.Conv2d(1, 6, 5)
self.pool = nn.MaxPool2d(2, 2)
self.conv2 = nn.Conv2d(6, 16, 5)
self.fc1 = nn.Linear(16 * 4 * 4, 120)
self.fc2 = nn.Linear(120, 84)
self.fc3 = nn.Linear(84, 10)
def forward(self, x):
x = self.pool(F.relu(self.conv1(x)))
x = self.pool(F.relu(self.conv2(x)))
x = x.view(-1, 16 * 4 * 4)
x = F.relu(self.fc1(x))
x = F.relu(self.fc2(x))
x = self.fc3(x)
return x
net = Net()
well, it’ work well when I run to the codewriter.add_graph(net, images), I recently see another way to implement it, my personal code as following
def __init__(self):
super(Net, self).__init__()
self.feature1 = nn.Sequential(
nn.Conv2d(1,6,5),
nn.ReLU(inplace=True),
nn.MaxPool2d(2,2),
nn.Conv2d(6,16,5),
nn.ReLU(inplace=True),
nn.MaxPool2d(2,2)
)
self.feature2 = nn.Sequential(
nn.Linear(256, 120),
nn.ReLU(inplace=True),
nn.Linear(120,84),
nn.ReLU(inplace=True),
nn.Linear(84,10)
)
def forward(self, x):
x = self.feature1(x)
x.view(-1, 256)
x = self.feature2(x)
return x
I use the nn.Sequential,when I run to the code writer.add_graph(net, images), it report Error as follows
RuntimeError: size mismatch, m1: [256 x 4], m2: [256 x 120] at C:\w\1\s\tmp_conda_3.7_055457\conda\conda-bld\pytorch_1565416617654\work\aten\src\TH/generic/THTensorMath.cpp:752
Process finished with exit code 1
So what is the different between them?
Thanks for you answer my question~~~
