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102 lines
3.8 KiB
102 lines
3.8 KiB
import torch |
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import comfy.model_management |
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import comfy.sampler_helpers |
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import comfy.samplers |
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import comfy.utils |
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import node_helpers |
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def perp_neg(x, noise_pred_pos, noise_pred_neg, noise_pred_nocond, neg_scale, cond_scale): |
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pos = noise_pred_pos - noise_pred_nocond |
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neg = noise_pred_neg - noise_pred_nocond |
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perp = neg - ((torch.mul(neg, pos).sum())/(torch.norm(pos)**2)) * pos |
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perp_neg = perp * neg_scale |
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cfg_result = noise_pred_nocond + cond_scale*(pos - perp_neg) |
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return cfg_result |
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#TODO: This node should be removed, it has been replaced with PerpNegGuider |
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class PerpNeg: |
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@classmethod |
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def INPUT_TYPES(s): |
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return {"required": {"model": ("MODEL", ), |
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"empty_conditioning": ("CONDITIONING", ), |
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"neg_scale": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 100.0, "step": 0.01}), |
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}} |
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RETURN_TYPES = ("MODEL",) |
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FUNCTION = "patch" |
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CATEGORY = "_for_testing" |
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def patch(self, model, empty_conditioning, neg_scale): |
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m = model.clone() |
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nocond = comfy.sampler_helpers.convert_cond(empty_conditioning) |
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def cfg_function(args): |
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model = args["model"] |
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noise_pred_pos = args["cond_denoised"] |
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noise_pred_neg = args["uncond_denoised"] |
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cond_scale = args["cond_scale"] |
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x = args["input"] |
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sigma = args["sigma"] |
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model_options = args["model_options"] |
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nocond_processed = comfy.samplers.encode_model_conds(model.extra_conds, nocond, x, x.device, "negative") |
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(noise_pred_nocond,) = comfy.samplers.calc_cond_batch(model, [nocond_processed], x, sigma, model_options) |
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cfg_result = x - perp_neg(x, noise_pred_pos, noise_pred_neg, noise_pred_nocond, neg_scale, cond_scale) |
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return cfg_result |
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m.set_model_sampler_cfg_function(cfg_function) |
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return (m, ) |
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class Guider_PerpNeg(comfy.samplers.CFGGuider): |
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def set_conds(self, positive, negative, empty_negative_prompt): |
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empty_negative_prompt = node_helpers.conditioning_set_values(empty_negative_prompt, {"prompt_type": "negative"}) |
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self.inner_set_conds({"positive": positive, "empty_negative_prompt": empty_negative_prompt, "negative": negative}) |
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def set_cfg(self, cfg, neg_scale): |
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self.cfg = cfg |
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self.neg_scale = neg_scale |
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def predict_noise(self, x, timestep, model_options={}, seed=None): |
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positive_cond = self.conds.get("positive", None) |
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negative_cond = self.conds.get("negative", None) |
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empty_cond = self.conds.get("empty_negative_prompt", None) |
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out = comfy.samplers.calc_cond_batch(self.inner_model, [negative_cond, positive_cond, empty_cond], x, timestep, model_options) |
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return perp_neg(x, out[1], out[0], out[2], self.neg_scale, self.cfg) |
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class PerpNegGuider: |
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@classmethod |
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def INPUT_TYPES(s): |
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return {"required": |
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{"model": ("MODEL",), |
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"positive": ("CONDITIONING", ), |
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"negative": ("CONDITIONING", ), |
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"empty_conditioning": ("CONDITIONING", ), |
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"cfg": ("FLOAT", {"default": 8.0, "min": 0.0, "max": 100.0, "step":0.1, "round": 0.01}), |
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"neg_scale": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 100.0, "step": 0.01}), |
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} |
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} |
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RETURN_TYPES = ("GUIDER",) |
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FUNCTION = "get_guider" |
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CATEGORY = "_for_testing" |
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def get_guider(self, model, positive, negative, empty_conditioning, cfg, neg_scale): |
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guider = Guider_PerpNeg(model) |
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guider.set_conds(positive, negative, empty_conditioning) |
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guider.set_cfg(cfg, neg_scale) |
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return (guider,) |
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NODE_CLASS_MAPPINGS = { |
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"PerpNeg": PerpNeg, |
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"PerpNegGuider": PerpNegGuider, |
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} |
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NODE_DISPLAY_NAME_MAPPINGS = { |
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"PerpNeg": "Perp-Neg (DEPRECATED by PerpNegGuider)", |
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}
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