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remove cfg cutoff node

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This commit is contained in:
Yousef Rafat 2025-12-22 21:15:12 +02:00
parent a4e9d071e8
commit 5db5da790f
2 changed files with 1 additions and 33 deletions
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17
comfy/samplers.py
View File

@ -949,19 +949,8 @@ class CFGGuider:
for k in conds: for k in conds:
self.original_conds[k] = comfy.sampler_helpers.convert_cond(conds[k]) self.original_conds[k] = comfy.sampler_helpers.convert_cond(conds[k])
def __call__(self, *args, **kwargs): def __call__(self, *args, **kwargs):
return self.outer_predict_noise(*args, **kwargs) return self.outer_predict_noise(*args, **kwargs)
def handle_dynamic_cfg(self, timestep, model_options):
if hasattr(self.model_patcher.model.diffusion_model, "stop_cfg_index"):
stop_index = self.model_patcher.model.diffusion_model.stop_cfg_index
transformer_options = model_options.get("transformer_options", {})
sigmas = transformer_options.get("sample_sigmas", None)
if sigmas is not None or self.cfg != 1.0:
dist = torch.abs(sigmas - timestep)
i = torch.argmin(dist).item()
if stop_index == i or (stop_index == -1 and i == len(sigmas) - 2):
self.set_cfg(1.0)
def outer_predict_noise(self, x, timestep, model_options={}, seed=None): def outer_predict_noise(self, x, timestep, model_options={}, seed=None):
return comfy.patcher_extension.WrapperExecutor.new_class_executor( return comfy.patcher_extension.WrapperExecutor.new_class_executor(
@ -971,7 +960,6 @@ class CFGGuider:
).execute(x, timestep, model_options, seed) ).execute(x, timestep, model_options, seed)
def predict_noise(self, x, timestep, model_options={}, seed=None): def predict_noise(self, x, timestep, model_options={}, seed=None):
self.handle_dynamic_cfg(timestep, model_options)
return sampling_function(self.inner_model, x, timestep, self.conds.get("negative", None), self.conds.get("positive", None), self.cfg, model_options=model_options, seed=seed) return sampling_function(self.inner_model, x, timestep, self.conds.get("negative", None), self.conds.get("positive", None), self.cfg, model_options=model_options, seed=seed)
def inner_sample(self, noise, latent_image, device, sampler, sigmas, denoise_mask, callback, disable_pbar, seed, latent_shapes=None): def inner_sample(self, noise, latent_image, device, sampler, sigmas, denoise_mask, callback, disable_pbar, seed, latent_shapes=None):
@ -996,9 +984,6 @@ class CFGGuider:
self.inner_model, self.conds, self.loaded_models = comfy.sampler_helpers.prepare_sampling(self.model_patcher, noise.shape, self.conds, self.model_options) self.inner_model, self.conds, self.loaded_models = comfy.sampler_helpers.prepare_sampling(self.model_patcher, noise.shape, self.conds, self.model_options)
device = self.model_patcher.load_device device = self.model_patcher.load_device
if denoise_mask is not None:
denoise_mask = comfy.sampler_helpers.prepare_mask(denoise_mask, noise.shape, device)
noise = noise.to(device) noise = noise.to(device)
latent_image = latent_image.to(device) latent_image = latent_image.to(device)
sigmas = sigmas.to(device) sigmas = sigmas.to(device)

17
comfy_extras/nodes_model_advanced.py
View File

@ -5,22 +5,6 @@ import nodes
import torch import torch
import node_helpers import node_helpers
class CFGCutoff:
@classmethod
def INPUT_TYPES(s):
return {"required": {"model": ("MODEL",), "cfg_stop_index": ("INT", {"default": -1, "min": -1, })}}
RETURN_TYPES = ("MODEL",)
FUNCTION = "patch"
CATEGORY = "advanced/model"
def patch(self, model, cfg_stop_index):
diff_model = model.model.diffusion_model
if hasattr(diff_model, "set_cfg_stop_index"):
diff_model.set_cfg_stop_index(cfg_stop_index)
return (model,)
class LCM(comfy.model_sampling.EPS): class LCM(comfy.model_sampling.EPS):
def calculate_denoised(self, sigma, model_output, model_input): def calculate_denoised(self, sigma, model_output, model_input):
@ -342,5 +326,4 @@ NODE_CLASS_MAPPINGS = {
"ModelSamplingFlux": ModelSamplingFlux, "ModelSamplingFlux": ModelSamplingFlux,
"RescaleCFG": RescaleCFG, "RescaleCFG": RescaleCFG,
"ModelComputeDtype": ModelComputeDtype, "ModelComputeDtype": ModelComputeDtype,
"CFGCutoff": CFGCutoff
} }