# Relationship between input range and channel means, standard deviations for CNNs

So, I'm using a pretrained PNASNet-5-Large model to do some image classification.

In the file, it says that the input range is in [0,1] (I'm assuming pixel values of input images). The images I have are already in this range. The channel means and standard deviation for RGB channels are stated as [0.5, 0.5, 0.5], [0.5, 0.5, 0.5] respectively. Now when I use the torchvision.transforms.Normalize to normalize the images using the stated means and standard deviations, the pixel values get to the range [-1,1].

The code I wrote for normalization:

transforms.Normalize([0.5, 0.5, 0.5],[0.5, 0.5, 0.5])


I believe I'm missing something fundamental. Should I normalize the images or should I not? Thanks!