class StableUnCLIPImageNormalizer(ModelMixin, ConfigMixin):
    """
    This class is used to hold the mean and standard deviation of the CLIP embedder used in stable unCLIP.

    It is used to normalize the image embeddings before the noise is applied and un-normalize the noised image
    embeddings.
    """

    @register_to_config
    def __init__(
        self,
        embedding_dim: int = 768,
    ):
        super().__init__()

        self.mean = nn.Parameter(torch.zeros(1, embedding_dim))
        self.std = nn.Parameter(torch.ones(1, embedding_dim))

    def to(
        self,
        torch_device: Optional[Union[str, torch.device]] = None,
        torch_dtype: Optional[torch.dtype] = None,
    ):
        self.mean = nn.Parameter(self.mean.to(torch_device).to(torch_dtype))
        self.std = nn.Parameter(self.std.to(torch_device).to(torch_dtype))
        return self

    def scale(self, embeds):
        embeds = (embeds - self.mean) * 1.0 / self.std
        return embeds

    def unscale(self, embeds):
        embeds = (embeds * self.std) + self.mean
        return embeds
/Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/pipelines/stable_diffusion/stable_unclip_image_normalizer.py