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SamplerDPMAdaptative node to test the different options.
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@ -559,11 +559,11 @@ def ksampler(sampler_name, extra_options={}, inpaint_options={}):
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return k_diffusion_sampling.sample_dpm_fast(model, noise, sigma_min, sigmas[0], total_steps, extra_args=extra_args, callback=callback, disable=disable)
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return k_diffusion_sampling.sample_dpm_fast(model, noise, sigma_min, sigmas[0], total_steps, extra_args=extra_args, callback=callback, disable=disable)
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sampler_function = dpm_fast_function
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sampler_function = dpm_fast_function
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elif sampler_name == "dpm_adaptive":
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elif sampler_name == "dpm_adaptive":
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def dpm_adaptive_function(model, noise, sigmas, extra_args, callback, disable):
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def dpm_adaptive_function(model, noise, sigmas, extra_args, callback, disable, **extra_options):
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sigma_min = sigmas[-1]
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sigma_min = sigmas[-1]
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if sigma_min == 0:
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if sigma_min == 0:
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sigma_min = sigmas[-2]
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sigma_min = sigmas[-2]
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return k_diffusion_sampling.sample_dpm_adaptive(model, noise, sigma_min, sigmas[0], extra_args=extra_args, callback=callback, disable=disable)
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return k_diffusion_sampling.sample_dpm_adaptive(model, noise, sigma_min, sigmas[0], extra_args=extra_args, callback=callback, disable=disable, **extra_options)
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sampler_function = dpm_adaptive_function
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sampler_function = dpm_adaptive_function
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else:
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else:
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sampler_function = getattr(k_diffusion_sampling, "sample_{}".format(sampler_name))
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sampler_function = getattr(k_diffusion_sampling, "sample_{}".format(sampler_name))
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@ -283,6 +283,33 @@ class SamplerLMS:
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sampler = comfy.samplers.ksampler("lms", {"order": order})
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sampler = comfy.samplers.ksampler("lms", {"order": order})
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return (sampler, )
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return (sampler, )
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class SamplerDPMAdaptative:
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@classmethod
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def INPUT_TYPES(s):
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return {"required":
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{"order": ("INT", {"default": 3, "min": 2, "max": 3}),
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"rtol": ("FLOAT", {"default": 0.05, "min": 0.0, "max": 100.0, "step":0.01, "round": False}),
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"atol": ("FLOAT", {"default": 0.0078, "min": 0.0, "max": 100.0, "step":0.01, "round": False}),
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"h_init": ("FLOAT", {"default": 0.05, "min": 0.0, "max": 100.0, "step":0.01, "round": False}),
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"pcoeff": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 100.0, "step":0.01, "round": False}),
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"icoeff": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 100.0, "step":0.01, "round": False}),
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"dcoeff": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 100.0, "step":0.01, "round": False}),
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"accept_safety": ("FLOAT", {"default": 0.81, "min": 0.0, "max": 100.0, "step":0.01, "round": False}),
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"eta": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 100.0, "step":0.01, "round": False}),
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"s_noise": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 100.0, "step":0.01, "round": False}),
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}
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}
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RETURN_TYPES = ("SAMPLER",)
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CATEGORY = "sampling/custom_sampling/samplers"
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FUNCTION = "get_sampler"
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def get_sampler(self, order, rtol, atol, h_init, pcoeff, icoeff, dcoeff, accept_safety, eta, s_noise):
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sampler = comfy.samplers.ksampler("dpm_adaptive", {"order": order, "rtol": rtol, "atol": atol, "h_init": h_init, "pcoeff": pcoeff,
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"icoeff": icoeff, "dcoeff": dcoeff, "accept_safety": accept_safety, "eta": eta,
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"s_noise":s_noise })
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return (sampler, )
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class SamplerCustom:
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class SamplerCustom:
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@classmethod
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@classmethod
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def INPUT_TYPES(s):
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def INPUT_TYPES(s):
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@ -348,6 +375,7 @@ NODE_CLASS_MAPPINGS = {
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"SamplerDPMPP_3M_SDE": SamplerDPMPP_3M_SDE,
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"SamplerDPMPP_3M_SDE": SamplerDPMPP_3M_SDE,
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"SamplerDPMPP_2M_SDE": SamplerDPMPP_2M_SDE,
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"SamplerDPMPP_2M_SDE": SamplerDPMPP_2M_SDE,
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"SamplerDPMPP_SDE": SamplerDPMPP_SDE,
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"SamplerDPMPP_SDE": SamplerDPMPP_SDE,
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"SamplerDPMAdaptative": SamplerDPMAdaptative,
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"SplitSigmas": SplitSigmas,
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"SplitSigmas": SplitSigmas,
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"FlipSigmas": FlipSigmas,
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"FlipSigmas": FlipSigmas,
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}
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}
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