Hi,
My code is
class Tenet(nn.Module):
def __init__(self):
super(Tenet, self).__init__()
self.conv1 = nn.Conv2d(in_channels=3, out_channels=16, kernel_size=(3,3), padding=(3,3), stride=(2,2))
def forward(self, x):
conv1 = self.conv1(x)
out = conv1.reshape(conv1.size(0), 32*32, 16)
return out
tenet = Tenet()
rand = torch.randn(1,3,60,60)
out=tenet(rand)
conv1.shape is torch.Size([1, 16, 32, 32])
and out.shape is torch.Size([1, 1024, 16])
After I plotted the architecture on tensorboard, I got:
I don’t understand, what the nodes 28, 29, 30, 31, 34, and 35 are doing really.
Help!