RicLaGra
(Ric)
February 6, 2021, 5:31pm
1
I used a Resnet-18 pretrained on Imagenet as you can see in torchvision library.
The site report 69.7, but I obtained 68.9.
I used the same preprocessing (test set) as reported in torchvision:
normalize = transforms.Normalize(mean=[0.485, 0.456, 0.406], 0.229, 0.224, 0.225])
torchvision.transforms.Resize(256)
torchvision.transforms.CenterCrop(224)
Can anyone help me? Is it possible an error on the table reported in torchvision?
https://pytorch.org/vision/0.8/models.html
MrPositron
(Nauryzbay K)
February 6, 2021, 5:34pm
2
Did you use model.eval()
?
RicLaGra
(Ric)
February 6, 2021, 6:09pm
3
Sure.
def test(model, testloader):
model.eval()
correct, total = 0, 0
with torch.no_grad():
for idx, (data, labels) in enumerate(testloader):
data, labels = data.cuda(), labels.cuda()
outputs = model(data)
_, predicted = torch.max(outputs.data, 1)
total += labels.size(0)
correct += (predicted == labels).sum().float().item()
acc = correct * 100. / total
err = 100. - acc
return acc, err
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