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change checkpoint merger to work in a more obvious way

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remove sigmoid and inverse sigmoid because they just did the same thing as weighed sum only with changed multiplier
This commit is contained in:
AUTOMATIC
2022-10-14 22:01:49 +03:00
parent 02382f7ce4
commit c250cb289c
3 changed files with 9 additions and 23 deletions
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24
modules/extras.py
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@@ -159,24 +159,12 @@ def run_pnginfo(image):
return '', geninfo, info
def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_name, interp_method, interp_amount, save_as_half, custom_name):
# Linear interpolation (https://en.wikipedia.org/wiki/Linear_interpolation)
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):
return ((1 - alpha) * theta0) + (alpha * theta1)
# Smoothstep (https://en.wikipedia.org/wiki/Smoothstep)
def sigmoid(theta0, theta1, theta2, alpha):
alpha = alpha * alpha * (3 - (2 * alpha))
return theta0 + ((theta1 - theta0) * alpha)
# Inverse Smoothstep (https://en.wikipedia.org/wiki/Smoothstep)
def inv_sigmoid(theta0, theta1, theta2, alpha):
import math
alpha = 0.5 - math.sin(math.asin(1.0 - 2.0 * alpha) / 3.0)
return theta0 + ((theta1 - theta0) * alpha)
def add_difference(theta0, theta1, theta2, alpha):
return theta0 + (theta1 - theta2) * (1.0 - alpha)
return theta0 + (theta1 - theta2) * alpha
primary_model_info = sd_models.checkpoints_list[primary_model_name]
secondary_model_info = sd_models.checkpoints_list[secondary_model_name]
@@ -198,9 +186,7 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam
theta_2 = None
theta_funcs = {
"Weighted Sum": weighted_sum,
"Sigmoid": sigmoid,
"Inverse Sigmoid": inv_sigmoid,
"Weighted sum": weighted_sum,
"Add difference": add_difference,
}
theta_func = theta_funcs[interp_method]
@@ -213,7 +199,7 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam
if t2 is None:
t2 = torch.zeros_like(theta_0[key])
theta_0[key] = theta_func(theta_0[key], theta_1[key], t2, (float(1.0) - interp_amount)) # Need to reverse the interp_amount to match the desired mix ration in the merged checkpoint
theta_0[key] = theta_func(theta_0[key], theta_1[key], t2, multiplier)
if save_as_half:
theta_0[key] = theta_0[key].half()
@@ -227,7 +213,7 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam
ckpt_dir = shared.cmd_opts.ckpt_dir or sd_models.model_path
filename = primary_model_info.model_name + '_' + str(round(interp_amount, 2)) + '-' + secondary_model_info.model_name + '_' + str(round((float(1.0) - interp_amount), 2)) + '-' + interp_method.replace(" ", "_") + '-merged.ckpt'
filename = primary_model_info.model_name + '_' + str(round(1-multiplier, 2)) + '-' + secondary_model_info.model_name + '_' + str(round(multiplier, 2)) + '-' + interp_method.replace(" ", "_") + '-merged.ckpt'
filename = filename if custom_name == '' else (custom_name + '.ckpt')
output_modelname = os.path.join(ckpt_dir, filename)