Class LTXVPerStepStatNormPatcher

latent_norm.py:277–331

@comfy_node(name="LTXVPerStepStatNormPatcher")
class LTXVPerStepStatNormPatcher(PerStepNormPatcher):
    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": super().required()
            | {
                "target_mean": (
                    "FLOAT",
                    {
                        "default": 0.0,
                        "min": -10.0,
                        "max": 10.0,
                        "step": 0.01,
                        "round": 0.01,
                    },
                ),
                "target_std": (
                    "FLOAT",
                    {
                        "default": 1.0,
                        "min": 0.01,
                        "max": 10.0,
                        "step": 0.01,
                        "round": 0.01,
                    },
                ),
                "percentile": (
                    "FLOAT",
                    {
                        "default": 95.0,
                        "min": 50.0,
                        "max": 100.0,
                        "step": 0.1,
                        "round": 0.1,
                        "tooltip": "Percentile of distribution to use for statistics calculation",
                    },
                ),
                "clip_outliers": ("BOOLEAN", {"default": False}),
            },
        }

    RETURN_TYPES = ("MODEL",)
    FUNCTION = "patch_model"

    CATEGORY = "Lightricks/latents"

    def patch_model(
        self, model, factors, target_mean, target_std, percentile, clip_outliers
    ):
        def cfg_stat_norm(latent, factor):
            return LTXVStatNormLatent().statistical_normalize(
                latent, target_mean, target_std, percentile, factor, clip_outliers
            )

        return self.patch_smooth_norm(model, factors, cfg_stat_norm)