nodes/Extraltodeus-ComfyUI-AutomaticCFG
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Update nodes.py

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Extraltodeus
2024-04-16 01:18:31 +02:00
committed by GitHub
parent 22490695ed
commit ecc5f4c57b
1 changed files with 9 additions and 5 deletions
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nodes.py
+9 -5
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@@ -5,10 +5,11 @@ import math
original_sampling_function = deepcopy(comfy.samplers.sampling_function)
minimum_sigma_to_disable_uncond = 1
maximum_sigma_to_enable_uncond = 1000000
no_uncond_at_all = False
def sampling_function_patched(model, x, timestep, uncond, cond, cond_scale, model_options={}, seed=None):
if math.isclose(cond_scale, 1.0) and model_options.get("disable_cfg1_optimization", False) == False or timestep[0] <= minimum_sigma_to_disable_uncond or no_uncond_at_all:
if math.isclose(cond_scale, 1.0) and model_options.get("disable_cfg1_optimization", False) == False or timestep[0] <= minimum_sigma_to_disable_uncond or no_uncond_at_all or timestep[0] > maximum_sigma_to_enable_uncond:
uncond_ = None
if not no_uncond_at_all:
cond_scale = 1
@@ -65,6 +66,7 @@ class advancedDynamicCFG:
"post_cfg_scale" : ("BOOLEAN", {"default": False}),
"post_cfg_scale_value": ("FLOAT", {"default": 0, "min": 0.0, "max": 100.0, "step": 0.1, "round": 0.1}),
"no_uncond_mode" : ("BOOLEAN", {"default": False}),
"uncond_start_percentage": ("FLOAT", {"default": 100.0, "min": 0.0, "max": 100.0, "step": 0.01, "round": 0.01}),
"debug_print" : ("BOOLEAN", {"default": False}),
}}
RETURN_TYPES = ("MODEL",)
@@ -74,16 +76,18 @@ class advancedDynamicCFG:
def patch(self, model, center_mean_post_cfg, center_mean_to_sigma,
automatic_cfg, sigma_boost, sigma_boost_percentage, lerp_uncond=False, lerp_uncond_strength=1,
post_cfg_scale=False, post_cfg_scale_value=8, no_uncond_mode=False, debug_print=False):
post_cfg_scale=False, post_cfg_scale_value=8, no_uncond_mode=False, uncond_start_percentage=100, debug_print=False):
global minimum_sigma_to_disable_uncond, no_uncond_at_all
global minimum_sigma_to_disable_uncond, maximum_sigma_to_enable_uncond, no_uncond_at_all
no_uncond_at_all = no_uncond_mode
model_sampling = model.model.model_sampling
sigmin = model_sampling.sigma(model_sampling.timestep(model_sampling.sigma_min))
sigmax = model_sampling.sigma(model_sampling.timestep(model_sampling.sigma_max))
low_sigma_threshold = (sigmax - sigmin) / 100 * sigma_boost_percentage
high_sigma_threshold = (sigmax - sigmin) / 100 * uncond_start_percentage
low_sigma_threshold = (sigmax - sigmin) / 100 * sigma_boost_percentage
if sigma_boost_percentage > 0 and sigma_boost:
minimum_sigma_to_disable_uncond = low_sigma_threshold
maximum_sigma_to_enable_uncond = high_sigma_threshold
comfy.samplers.sampling_function = sampling_function_patched
print(f"Sampling function patched. Trigger when sigmas are at: {round(minimum_sigma_to_disable_uncond.item(),4)}")
else:
@@ -253,4 +257,4 @@ class simpleDynamicCFGNoUncond:
m = advcfg.patch(model=model, center_mean_post_cfg=True, center_mean_to_sigma=False,
automatic_cfg="None", sigma_boost="None", sigma_boost_percentage=6.86,
no_uncond_mode=True)[0]
return (m, )
return (m, )