Fix SamplerEulerCFGpp node.
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2f03201690
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@ -60,7 +60,7 @@ from comfy.k_diffusion.sampling import to_d
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import comfy.model_patcher
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import comfy.model_patcher
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@torch.no_grad()
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@torch.no_grad()
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def sample_euler_cfgpp(model, x, sigmas, extra_args=None, callback=None, disable=None):
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def sample_euler_pp(model, x, sigmas, extra_args=None, callback=None, disable=None):
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extra_args = {} if extra_args is None else extra_args
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extra_args = {} if extra_args is None else extra_args
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temp = [0]
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temp = [0]
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@ -75,11 +75,11 @@ def sample_euler_cfgpp(model, x, sigmas, extra_args=None, callback=None, disable
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for i in trange(len(sigmas) - 1, disable=disable):
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for i in trange(len(sigmas) - 1, disable=disable):
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sigma_hat = sigmas[i]
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sigma_hat = sigmas[i]
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denoised = model(x, sigma_hat * s_in, **extra_args)
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denoised = model(x, sigma_hat * s_in, **extra_args)
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d = to_d(x, sigma_hat, temp[0])
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d = to_d(x - denoised + temp[0], sigmas[i], denoised)
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if callback is not None:
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if callback is not None:
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callback({'x': x, 'i': i, 'sigma': sigmas[i], 'sigma_hat': sigma_hat, 'denoised': denoised})
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callback({'x': x, 'i': i, 'sigma': sigmas[i], 'sigma_hat': sigma_hat, 'denoised': denoised})
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dt = sigmas[i + 1] - sigma_hat
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dt = sigmas[i + 1] - sigma_hat
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x = denoised + sigmas[i + 1] * d
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x = x + d * dt
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return x
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return x
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@ -96,10 +96,10 @@ class SamplerEulerCFGpp:
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FUNCTION = "get_sampler"
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FUNCTION = "get_sampler"
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def get_sampler(self, version):
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def get_sampler(self, version):
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if version == "regular":
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if version == "alternative":
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sampler = comfy.samplers.KSAMPLER(sample_euler_cfgpp)
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sampler = comfy.samplers.KSAMPLER(sample_euler_pp)
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else:
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else:
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sampler = comfy.samplers.ksampler("euler_pp")
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sampler = comfy.samplers.ksampler("euler_cfg_pp")
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return (sampler, )
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return (sampler, )
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NODE_CLASS_MAPPINGS = {
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NODE_CLASS_MAPPINGS = {
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