lllyasviel/stable-diffusion-webui-forge
1
0
Fork 0
mirror of https://github.com/lllyasviel/stable-diffusion-webui-forge.git synced 2026-04-30 19:21:21 +00:00
Code Issues Packages Projects Releases Wiki Activity

add edit model

Browse Source
This commit is contained in:
lllyasviel
2024-02-10 03:24:40 -08:00
parent 44b647a83e
commit 998327c744
1 changed files with 5 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

5
ldm_patched/modules/samplers.py
View File

@@ -272,6 +272,8 @@ def calc_cond_uncond_batch(model, cond, uncond, x_in, timestep, model_options):
#The main sampling function shared by all the samplers #The main sampling function shared by all the samplers
#Returns denoised #Returns denoised
def sampling_function(model, x, timestep, uncond, cond, cond_scale, model_options={}, seed=None): def sampling_function(model, x, timestep, uncond, cond, cond_scale, model_options={}, seed=None):
edit_strength = sum((item['strength'] if 'strength' in item else 1) for item in cond)
if math.isclose(cond_scale, 1.0) and model_options.get("disable_cfg1_optimization", False) == False: if math.isclose(cond_scale, 1.0) and model_options.get("disable_cfg1_optimization", False) == False:
uncond_ = None uncond_ = None
else: else:
@@ -281,10 +283,13 @@ def sampling_function(model, x, timestep, uncond, cond, cond_scale, model_option
model, cond, uncond_, x, timestep, model_options = fn(model, cond, uncond_, x, timestep, model_options) model, cond, uncond_, x, timestep, model_options = fn(model, cond, uncond_, x, timestep, model_options)
cond_pred, uncond_pred = calc_cond_uncond_batch(model, cond, uncond_, x, timestep, model_options) cond_pred, uncond_pred = calc_cond_uncond_batch(model, cond, uncond_, x, timestep, model_options)
if "sampler_cfg_function" in model_options: if "sampler_cfg_function" in model_options:
args = {"cond": x - cond_pred, "uncond": x - uncond_pred, "cond_scale": cond_scale, "timestep": timestep, "input": x, "sigma": timestep, args = {"cond": x - cond_pred, "uncond": x - uncond_pred, "cond_scale": cond_scale, "timestep": timestep, "input": x, "sigma": timestep,
"cond_denoised": cond_pred, "uncond_denoised": uncond_pred, "model": model, "model_options": model_options} "cond_denoised": cond_pred, "uncond_denoised": uncond_pred, "model": model, "model_options": model_options}
cfg_result = x - model_options["sampler_cfg_function"](args) cfg_result = x - model_options["sampler_cfg_function"](args)
elif not math.isclose(edit_strength, 1.0):
cfg_result = uncond_pred + (cond_pred - uncond_pred) * cond_scale * edit_strength
else: else:
cfg_result = uncond_pred + (cond_pred - uncond_pred) * cond_scale cfg_result = uncond_pred + (cond_pred - uncond_pred) * cond_scale