Mirrors
/
stable-diffusion-webui
mirror of https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

improve performance of 3-way merge on machines with not enough ram, by only accessing two of the models at a time

This commit is contained in:
MrCheeze 2022-10-16 18:44:39 -04:00 committed by AUTOMATIC1111
parent a1d3cbf92c
commit 0fd1307671
1 changed files with 17 additions and 10 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

27
modules/extras.py
View File

@ -175,11 +175,14 @@ def run_pnginfo(image):
def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_name, interp_method, multiplier, save_as_half, custom_name): def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_name, interp_method, multiplier, save_as_half, custom_name):
def weighted_sum(theta0, theta1, theta2, alpha): def weighted_sum(theta0, theta1, alpha):
return ((1 - alpha) * theta0) + (alpha * theta1) return ((1 - alpha) * theta0) + (alpha * theta1)
def add_difference(theta0, theta1, theta2, alpha): def get_difference(theta1, theta2):
return theta0 + (theta1 - theta2) * alpha return theta1 - theta2
def add_difference(theta0, theta1_2_diff, alpha):
return theta0 + (alpha * theta1_2_diff)
primary_model_info = sd_models.checkpoints_list[primary_model_name] primary_model_info = sd_models.checkpoints_list[primary_model_name]
secondary_model_info = sd_models.checkpoints_list[secondary_model_name] secondary_model_info = sd_models.checkpoints_list[secondary_model_name]
@ -201,20 +204,24 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam
theta_2 = None theta_2 = None
theta_funcs = { theta_funcs = {
"Weighted sum": weighted_sum, "Weighted sum": (None, weighted_sum),
"Add difference": add_difference, "Add difference": (get_difference, add_difference),
} }
theta_func = theta_funcs[interp_method] theta_func1, theta_func2 = theta_funcs[interp_method]
print(f"Merging...") print(f"Merging...")
if theta_func1:
for key in tqdm.tqdm(theta_1.keys()):
if 'model' in key:
t2 = theta_2.get(key, torch.zeros_like(theta_1[key]))
theta_1[key] = theta_func1(theta_1[key], t2)
del theta_2, teritary_model
for key in tqdm.tqdm(theta_0.keys()): for key in tqdm.tqdm(theta_0.keys()):
if 'model' in key and key in theta_1: if 'model' in key and key in theta_1:
t2 = (theta_2 or {}).get(key)
if t2 is None:
t2 = torch.zeros_like(theta_0[key])
theta_0[key] = theta_func(theta_0[key], theta_1[key], t2, multiplier) theta_0[key] = theta_func2(theta_0[key], theta_1[key], multiplier)
if save_as_half: if save_as_half:
theta_0[key] = theta_0[key].half() theta_0[key] = theta_0[key].half()