update lists of models after merging them in checkpoints tab

support saving as half

4 files changed, 52 insertions, 34 deletions

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)]

diff --git a/modules/sd_models.py b/modules/sd_models.py
index 9decc911..dd47dffb 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -23,6 +23,11 @@ except Exception:
     pass

 

 

+def checkpoint_tiles():

+    print(sorted([x.title for x in checkpoints_list.values()]))

+    return sorted([x.title for x in checkpoints_list.values()])

+

+

 def list_models():

     checkpoints_list.clear()

 

@@ -39,13 +44,14 @@ def list_models():
         if name.startswith("\\") or name.startswith("/"):

             name = name[1:]

 

-        return f'{name} [{h}]'

+        shortname = os.path.splitext(name.replace("/", "_").replace("\\", "_"))[0]

+

+        return f'{name} [{h}]', shortname

 

     cmd_ckpt = shared.cmd_opts.ckpt

     if os.path.exists(cmd_ckpt):

         h = model_hash(cmd_ckpt)

-        title = modeltitle(cmd_ckpt, h)

-        model_name = title.rsplit(".",1)[0] # remove extension if present

+        title, model_name = modeltitle(cmd_ckpt, h)

         checkpoints_list[title] = CheckpointInfo(cmd_ckpt, title, h, model_name)

     elif cmd_ckpt is not None and cmd_ckpt != shared.default_sd_model_file:

         print(f"Checkpoint in --ckpt argument not found: {cmd_ckpt}", file=sys.stderr)

@@ -53,8 +59,7 @@ def list_models():
     if os.path.exists(model_dir):

         for filename in glob.glob(model_dir + '/**/*.ckpt', recursive=True):

             h = model_hash(filename)

-            title = modeltitle(filename, h)

-            model_name = title.rsplit(".",1)[0] # remove extension if present

+            title, model_name = modeltitle(filename, h)

             checkpoints_list[title] = CheckpointInfo(filename, title, h, model_name)

 

 

diff --git a/modules/shared.py b/modules/shared.py
index 39cf89bc..ec1e569b 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -190,7 +190,7 @@ options_templates.update(options_section(('system', "System"), {
 }))

 

 options_templates.update(options_section(('sd', "Stable Diffusion"), {

-    "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Radio, lambda: {"choices": [x.title for x in modules.sd_models.checkpoints_list.values()]}),

+    "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Radio, lambda: {"choices": modules.sd_models.checkpoint_tiles()}),

     "img2img_color_correction": OptionInfo(False, "Apply color correction to img2img results to match original colors."),

     "save_images_before_color_correction": OptionInfo(False, "Save a copy of image before applying color correction to img2img results"),    

     "img2img_fix_steps": OptionInfo(False, "With img2img, do exactly the amount of steps the slider specifies (normally you'd do less with less denoising)."),

diff --git a/modules/ui.py b/modules/ui.py
index d51f7a08..4958036a 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -872,29 +872,16 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
                 gr.HTML(value="<p>A merger of the two checkpoints will be generated in your <b>/models</b> directory.</p>")

                 

                 with gr.Row():

-                    ckpt_name_list = sorted([x.title for x in modules.sd_models.checkpoints_list.values()])

-                    primary_model_name = gr.Dropdown(ckpt_name_list, elem_id="modelmerger_primary_model_name", label="Primary Model Name")

-                    secondary_model_name = gr.Dropdown(ckpt_name_list, elem_id="modelmerger_secondary_model_name", label="Secondary Model Name")

+                    primary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_primary_model_name", label="Primary Model Name")

+                    secondary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_secondary_model_name", label="Secondary Model Name")

                 interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Interpolation Amount', value=0.3)

                 interp_method = gr.Radio(choices=["Weighted Sum", "Sigmoid", "Inverse Sigmoid"], value="Weighted Sum", label="Interpolation Method")

-                submit = gr.Button(elem_id="modelmerger_merge", label="Merge", variant='primary')

+                save_as_half = gr.Checkbox(value=False, label="Safe as float16")

+                modelmerger_merge = gr.Button(elem_id="modelmerger_merge", label="Merge", variant='primary')

             

             with gr.Column(variant='panel'):

                 submit_result = gr.Textbox(elem_id="modelmerger_result", show_label=False)

 

-            submit.click(

-                fn=run_modelmerger,

-                inputs=[

-                    primary_model_name,

-                    secondary_model_name,

-                    interp_method,

-                    interp_amount

-                ],

-                outputs=[

-                    submit_result,

-                ]

-            )

-

     def create_setting_component(key):

         def fun():

             return opts.data[key] if key in opts.data else opts.data_labels[key].default

@@ -918,6 +905,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
         return comp(label=info.label, value=fun, **(args or {}))

 

     components = []

+    component_dict = {}

 

     def run_settings(*args):

         changed = 0

@@ -973,7 +961,9 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
 

                     gr.HTML(elem_id="settings_header_text_{}".format(item.section[0]), value='<h1 class="gr-button-lg">{}</h1>'.format(item.section[1]))

 

-                components.append(create_setting_component(k))

+                component = create_setting_component(k)

+                component_dict[k] = component

+                components.append(component)

                 items_displayed += 1

 

         request_notifications = gr.Button(value='Request browser notifications', elem_id="request_notifications")

@@ -1024,6 +1014,22 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo, run_modelmerger):
             outputs=[result, text_settings],

         )

 

+        modelmerger_merge.click(

+            fn=run_modelmerger,

+            inputs=[

+                primary_model_name,

+                secondary_model_name,

+                interp_method,

+                interp_amount,

+                save_as_half,

+            ],

+            outputs=[

+                submit_result,

+                primary_model_name,

+                secondary_model_name,

+                component_dict['sd_model_checkpoint'],

+            ]

+        )

         paste_field_names = ['Prompt', 'Negative prompt', 'Steps', 'Face restoration', 'Seed', 'Size-1', 'Size-2']

         txt2img_fields = [field for field,name in txt2img_paste_fields if name in paste_field_names]

         img2img_fields = [field for field,name in img2img_paste_fields if name in paste_field_names]