From 7acfaca05a13352a7d86d281db6ad64dfd9350e0 Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Thu, 29 Sep 2022 00:59:44 +0300
Subject: update lists of models after merging them in checkpoints tab support
 saving as half

---
 modules/extras.py | 27 +++++++++++++++++----------
 1 file changed, 17 insertions(+), 10 deletions(-)

(limited to 'modules/extras.py')

diff --git a/modules/extras.py b/modules/extras.py
index dcc0148c..9a825530 100644
--- a/modules/extras.py
+++ b/modules/extras.py
@@ -13,6 +13,7 @@ from modules.ui import plaintext_to_html
 import modules.codeformer_model
 import piexif
 import piexif.helper
+import gradio as gr
 
 
 cached_images = {}
@@ -140,7 +141,7 @@ def run_pnginfo(image):
     return '', geninfo, info
 
 
-def run_modelmerger(primary_model_name, secondary_model_name, interp_method, interp_amount):
+def run_modelmerger(primary_model_name, secondary_model_name, interp_method, interp_amount, save_as_half):
     # Linear interpolation (https://en.wikipedia.org/wiki/Linear_interpolation)
     def weighted_sum(theta0, theta1, alpha):
         return ((1 - alpha) * theta0) + (alpha * theta1)
@@ -156,14 +157,14 @@ def run_modelmerger(primary_model_name, secondary_model_name, interp_method, int
         alpha = 0.5 - math.sin(math.asin(1.0 - 2.0 * alpha) / 3.0)
         return theta0 + ((theta1 - theta0) * alpha)
 
-    primary_model_filename = sd_models.checkpoints_list[primary_model_name].filename
-    secondary_model_filename = sd_models.checkpoints_list[secondary_model_name].filename
+    primary_model_info = sd_models.checkpoints_list[primary_model_name]
+    secondary_model_info = sd_models.checkpoints_list[secondary_model_name]
 
-    print(f"Loading {primary_model_filename}...")
-    primary_model = torch.load(primary_model_filename, map_location='cpu')
+    print(f"Loading {primary_model_info.filename}...")
+    primary_model = torch.load(primary_model_info.filename, map_location='cpu')
 
-    print(f"Loading {secondary_model_filename}...")
-    secondary_model = torch.load(secondary_model_filename, map_location='cpu')
+    print(f"Loading {secondary_model_info.filename}...")
+    secondary_model = torch.load(secondary_model_info.filename, map_location='cpu')
    
     theta_0 = primary_model['state_dict']
     theta_1 = secondary_model['state_dict']
@@ -178,17 +179,23 @@ def run_modelmerger(primary_model_name, secondary_model_name, interp_method, int
     print(f"Merging...")
     for key in tqdm.tqdm(theta_0.keys()):
         if 'model' in key and key in theta_1:
-            theta_0[key] = theta_func(theta_0[key], theta_1[key], (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], (float(1.0) - interp_amount))  # Need to reverse the interp_amount to match the desired mix ration in the merged checkpoint
+            if save_as_half:
+                theta_0[key] = theta_0[key].half()
     
     for key in theta_1.keys():
         if 'model' in key and key not in theta_0:
             theta_0[key] = theta_1[key]
+            if save_as_half:
+                theta_0[key] = theta_0[key].half()
 
-    filename = primary_model_name + '_' + str(round(interp_amount,2)) + '-' + secondary_model_name + '_' + str(round((float(1.0) - interp_amount),2)) + '-' + interp_method.replace(" ", "_") + '-merged.ckpt'
+    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'
     output_modelname = os.path.join(shared.cmd_opts.ckpt_dir, filename)
 
     print(f"Saving to {output_modelname}...")
     torch.save(primary_model, output_modelname)
 
+    sd_models.list_models()
+
     print(f"Checkpoint saved.")
-    return "Checkpoint saved to " + output_modelname
+    return ["Checkpoint saved to " + output_modelname] + [gr.Dropdown.update(choices=sd_models.checkpoint_tiles()) for _ in range(3)]
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