I think a simple approach here, albeit more tedious, is to write your own transformation function directly via the functional versions of the transforms e.g.,
def buildmytransform(hflip_prob, vflip_prob, ...):
    def _transform(image):
        if torch.rand(1) < hflip_prob:
            blur_tmp = albumentations.augmentations.functional.hflip(image)
            sharp_tmp = albumentations.augmentations.functional.hflip(image)
        blur_tmp = albumentations.augmentations.functional.rotate(blur_tmp, ...)
        sharp_tmp = albumentations.augmentations.functional.rotate(sharp_tmp, ...)
        if torch.rand(1) < vflip_prob:
        ...
        return blur_tmp, sharp_tmp
    return _transform