change checkpoint merger to work in a more obvious way

remove sigmoid and inverse sigmoid because they just did the same thing as weighed sum only with changed multiplier

1 files changed, 5 insertions, 19 deletions

diff --git a/modules/extras.py b/modules/extras.py
index 2e7b3751..f2f5a7b0 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -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)