I’m not sure I understand what you ask. Transforms can be use flexibly, like so:
    from torchvision.transforms import transforms
    from yourdataset import yourdatasetclass

    tf = transforms.ToTensor()
    dset = yourdatasetclass(root, transforms=tf)
    dloader = torch.utils.data.Dataloader(dset, batch_size=2,shuffle=True,num_workers=2)

You can use transforms.Compose to chain your transforms sequentially.