Pytorch dataloader transforms and keras 3.0 model training

Keras
,
1

In most pytorch training, one of the augmentations applied to both the train and validation set is Normalization especially when doing transfer learning like so for Imagenet dataset;

transforms.Normalization(
                mean=[0.485, 0.456, 0.406],
                std=[0.229, 0.224, 0.225]
            )

I want to know if it is a good idea to apply a similar transform when using pytorch dataloaders with keras 3.0 model architecture for training?