upapa / ComfyUI /comfy_extras /nodes_pag.py
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#Modified/simplified version of the node from: https://github.com/pamparamm/sd-perturbed-attention
#If you want the one with more options see the above repo.
#My modified one here is more basic but has less chances of breaking with ComfyUI updates.
import comfy.model_patcher
import comfy.samplers
class PerturbedAttentionGuidance:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"model": ("MODEL",),
"scale": ("FLOAT", {"default": 3.0, "min": 0.0, "max": 100.0, "step": 0.01, "round": 0.01}),
}
}
RETURN_TYPES = ("MODEL",)
FUNCTION = "patch"
CATEGORY = "model_patches/unet"
def patch(self, model, scale):
unet_block = "middle"
unet_block_id = 0
m = model.clone()
def perturbed_attention(q, k, v, extra_options, mask=None):
return v
def post_cfg_function(args):
model = args["model"]
cond_pred = args["cond_denoised"]
cond = args["cond"]
cfg_result = args["denoised"]
sigma = args["sigma"]
model_options = args["model_options"].copy()
x = args["input"]
if scale == 0:
return cfg_result
# Replace Self-attention with PAG
model_options = comfy.model_patcher.set_model_options_patch_replace(model_options, perturbed_attention, "attn1", unet_block, unet_block_id)
(pag,) = comfy.samplers.calc_cond_batch(model, [cond], x, sigma, model_options)
return cfg_result + (cond_pred - pag) * scale
m.set_model_sampler_post_cfg_function(post_cfg_function)
return (m,)
NODE_CLASS_MAPPINGS = {
"PerturbedAttentionGuidance": PerturbedAttentionGuidance,
}