| import torch |
|
|
|
|
| class RescaleClassifierFreeGuidance: |
| @classmethod |
| def INPUT_TYPES(s): |
| return {"required": { "model": ("MODEL",), |
| "multiplier": ("FLOAT", {"default": 0.7, "min": 0.0, "max": 1.0, "step": 0.01}), |
| }} |
| RETURN_TYPES = ("MODEL",) |
| FUNCTION = "patch" |
|
|
| CATEGORY = "custom_node_experiments" |
|
|
| def patch(self, model, multiplier): |
| |
| def rescale_cfg(args): |
| cond = args["cond"] |
| uncond = args["uncond"] |
| cond_scale = args["cond_scale"] |
|
|
| x_cfg = uncond + cond_scale * (cond - uncond) |
| ro_pos = torch.std(cond, dim=(1,2,3), keepdim=True) |
| ro_cfg = torch.std(x_cfg, dim=(1,2,3), keepdim=True) |
|
|
| x_rescaled = x_cfg * (ro_pos / ro_cfg) |
| x_final = multiplier * x_rescaled + (1.0 - multiplier) * x_cfg |
|
|
| return x_final |
|
|
| m = model.clone() |
| m.set_model_sampler_cfg_function(rescale_cfg) |
| return (m, ) |
|
|
|
|
| NODE_CLASS_MAPPINGS = { |
| "RescaleClassifierFreeGuidanceTest": RescaleClassifierFreeGuidance, |
| } |
|
|