If you do something like this:

transform_train = transforms.Compose([
transforms.RandomCrop(32, padding=4),
transforms.RandomHorizontalFlip(),
transforms.ToTensor(),
transforms.Normalize((0.4914, 0.4822, 0.4465), (0.2023, 0.1994, 0.2010)),
])

Then the transformed data will be automatically used in training. Is that what you wanted?
See full example here with train / test transforms.
https://github.com/QuantScientist/Deep-Learning-Boot-Camp/blob/master/day%2002%20PyTORCH%20and%20PyCUDA/PyTorch/21-PyTorch-CIFAR-10-Custom-data-loader-from-scratch.ipynb 83