Thank you very much for your quick reply. Let me explain my task for you. I worked on Imagenet validation dataset to train an adversarial perturbation generator in which a freezed googlenet model was used.
I saw this line 3 of code and I inferred that when we set pretrained=True in Googlenet constructor, the forward function normalized the input image differently (seems it works with different statistics).
About the accuracy, I did not directly calculate it but in terms of fooling rate in adversarial attack task which I achieved, I saw that the input image with the range [0,1] had far better performance.