I thought with gradient calculations involved, the inference time must be fairly faster. Am I misunderstanding something here?
import torch
from torchvision.models import vgg16

vgg = vgg16(pretrained=True)
x = torch.randn(1, 3, 480, 640)

%timeit vgg(x)
# 1.36 s ± 93.9 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)

%%timeit
with torch.no_grad():
    vgg(x)
# 1.88 s ± 294 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)