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