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sampler_cfg_function now gets the noisy output as argument again.
This should make things that use sampler_cfg_function behave like before. Added an input argument for those that want the denoised output. This means you can calculate the x0 prediction of the model by doing: (input - cond) for example.
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@ -251,8 +251,8 @@ def sampling_function(model_function, x, timestep, uncond, cond, cond_scale, mod
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cond, uncond = calc_cond_uncond_batch(model_function, cond, uncond, x, timestep, max_total_area, model_options)
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if "sampler_cfg_function" in model_options:
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args = {"cond": cond, "uncond": uncond, "cond_scale": cond_scale, "timestep": timestep}
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return model_options["sampler_cfg_function"](args)
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args = {"cond": x - cond, "uncond": x - uncond, "cond_scale": cond_scale, "timestep": timestep, "input": x}
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return x - model_options["sampler_cfg_function"](args)
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else:
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return uncond + (cond - uncond) * cond_scale
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