Testing the model and show the result

test-model.py

# Show the images and the ground truth
dataiter = iter(dataloaders['test'])
images, labels = dataiter.next()
imshow(torchvision.utils.make_grid(images))
print('GroundTruth: ', ', '.join('%5s' % class_names[x] for x in labels))

# Predict the model
images = images.to(device)
labels = images.to(device)
output = model_resnet(images)
_, predicted = torch.max(output, 1)
print('Predicted: ', ', '.join('%5s' % class_names[x] for x in predicted))