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import comfy.model_patcher |
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import comfy.samplers |
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import re |
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class SkipLayerGuidanceDiT: |
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''' |
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Enhance guidance towards detailed dtructure by having another set of CFG negative with skipped layers. |
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Inspired by Perturbed Attention Guidance (https://arxiv.org/abs/2403.17377) |
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Original experimental implementation for SD3 by Dango233@StabilityAI. |
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''' |
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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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"double_layers": ("STRING", {"default": "7, 8, 9", "multiline": False}), |
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"single_layers": ("STRING", {"default": "7, 8, 9", "multiline": False}), |
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"scale": ("FLOAT", {"default": 3.0, "min": 0.0, "max": 10.0, "step": 0.1}), |
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"start_percent": ("FLOAT", {"default": 0.01, "min": 0.0, "max": 1.0, "step": 0.001}), |
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"end_percent": ("FLOAT", {"default": 0.15, "min": 0.0, "max": 1.0, "step": 0.001}) |
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}} |
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RETURN_TYPES = ("MODEL",) |
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FUNCTION = "skip_guidance" |
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EXPERIMENTAL = True |
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DESCRIPTION = "Generic version of SkipLayerGuidance node that can be used on every DiT model." |
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CATEGORY = "advanced/guidance" |
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def skip_guidance(self, model, scale, start_percent, end_percent, double_layers="", single_layers=""): |
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def skip(args, extra_args): |
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return args |
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model_sampling = model.get_model_object("model_sampling") |
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sigma_start = model_sampling.percent_to_sigma(start_percent) |
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sigma_end = model_sampling.percent_to_sigma(end_percent) |
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double_layers = re.findall(r'\d+', double_layers) |
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double_layers = [int(i) for i in double_layers] |
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single_layers = re.findall(r'\d+', single_layers) |
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single_layers = [int(i) for i in single_layers] |
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if len(double_layers) == 0 and len(single_layers) == 0: |
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return (model, ) |
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def post_cfg_function(args): |
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model = args["model"] |
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cond_pred = args["cond_denoised"] |
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cond = args["cond"] |
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cfg_result = args["denoised"] |
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sigma = args["sigma"] |
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x = args["input"] |
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model_options = args["model_options"].copy() |
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for layer in double_layers: |
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model_options = comfy.model_patcher.set_model_options_patch_replace(model_options, skip, "dit", "double_block", layer) |
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for layer in single_layers: |
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model_options = comfy.model_patcher.set_model_options_patch_replace(model_options, skip, "dit", "single_block", layer) |
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model_sampling.percent_to_sigma(start_percent) |
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sigma_ = sigma[0].item() |
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if scale > 0 and sigma_ >= sigma_end and sigma_ <= sigma_start: |
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(slg,) = comfy.samplers.calc_cond_batch(model, [cond], x, sigma, model_options) |
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cfg_result = cfg_result + (cond_pred - slg) * scale |
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return cfg_result |
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m = model.clone() |
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m.set_model_sampler_post_cfg_function(post_cfg_function) |
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return (m, ) |
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NODE_CLASS_MAPPINGS = { |
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"SkipLayerGuidanceDiT": SkipLayerGuidanceDiT, |
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} |
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