Spaces:
Sleeping
Sleeping
File size: 1,838 Bytes
97b9880 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 |
#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": 0.1, "round": 0.01}),
}
}
RETURN_TYPES = ("MODEL",)
FUNCTION = "patch"
CATEGORY = "_for_testing"
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,
}
|