T.Normalize()

T.Normalize() is a method in PyTorch's transform module that normalizes a tensor image with mean and standard deviation values. It takes two arguments, mean and std, which are sequences of length corresponding to the number of channels in the tensor image.

For example, if we have a tensor image with 3 channels (RGB), we can normalize it using the following code:

transform = transforms.Compose([
    transforms.ToTensor(),
    transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
])

Here, we first convert the image to a tensor using ToTensor(), and then normalize it using Normalize() with mean and std values of 0.485, 0.456, 0.406 and 0.229, 0.224, 0.225 respectively.

This normalization is commonly used in pre-trained neural networks, as it helps to improve the network's performance and convergence during training.