Hello all, I have trained my model with my dataset. At that time, my model is
class LeNet(nn.Module):
def __init__(self):
super(LeNet, self).__init__()
self.conv1 = nn.Conv2d(3, 6, 5)
self.conv2 = nn.Conv2d(6, 16, 5)
self.fc1 = nn.Linear(16*5*5, 120)
self.fc2 = nn.Linear(120, 84)
self.fc3 = nn.Linear(84, 10)
def forward(self, x):
out = F.relu(self.conv1(x))
out = F.max_pool2d(out, 2)
out = F.relu(self.conv2(out))
out = F.max_pool2d(out, 2)
out = out.view(out.size(0), -1)
out = F.relu(self.fc1(out))
out = F.relu(self.fc2(out))
out = self.fc3(out)
return out
net = LeNet()
net.train()
The network has trained and save the model to lenet.pth
. Now, I changed the network to support multiple GPU and I want to load the pre-trained model lenet.pth
. Then I change it to
net = LeNet()
net = torch.nn.DataParallel(net, [0,1])
ckpt = torch.load('./lenet.pth', map_location=lambda storage, loc: storage)
net.load_state_dict(ckpt['checkpoints'])
However, it does not allow to load it. How to fix it? Thanks