Okay, but isn’t it odd. I already included the transforms.Resize() in the transforms.Compose() as seen here
# define transforms
    if augment:
        train_transform = transforms.Compose([
            transforms.Resize(img_size),
            transforms.RandomHorizontalFlip(0.3),
            transforms.ToTensor(),
            normalize,
        ])
    else:
        train_transform = transforms.Compose([
            transforms.Resize(img_size),
            transforms.ToTensor(),
            normalize,
        ])

    # load the dataset
    train_dataset = datasets.ImageFolder(
        root=train_dir,
        transform=torchvision.transforms.Compose([
            transforms.Resize(img_size),
            transforms.RandomHorizontalFlip(0.3),
            transforms.ToTensor()])
    )

    valid_dataset = train_dataset = datasets.ImageFolder(
        root=train_dir,
        transform=transforms.Compose([
            transforms.Resize(img_size),
            transforms.ToTensor(),
            normalize,])
        )

I even checked the image size as i defined the batch_size to be 64 and img_size to be 224
IN: trainimages, trainlabels = next(iter(train_loader))
IN: trainimages.shape
OUT: torch.Size([64, 3, 224, 224])