should I normalize across all the examples in training set or all examples in my entire dataset? I meant should I find the mean and std of images across all the training set images or all the images in the datasets? Is there an example that shows how to do this from scratch not how to use some mean and std already known? The transfer learning tutorial for example uses an already known mean and std for normalization of images.
transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])

  
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Transfer Learning for Computer Vision Tutorial — PyTorch Tutorials 1.6.0...