SD VAE rework 2

- the setting for preferring opts.sd_vae has been inverted and reworded
- resolve_vae function made easier to read and now returns an object rather than a tuple
- if the checkbox for overriding per-model preferences is checked, opts.sd_vae overrides checkpoint user metadata
- changing VAE in user metadata  for currently loaded model immediately applies the selection

modules/sd_models.py

@@ -356,7 +356,7 @@ def load_model_weights(model, checkpoint_info: CheckpointInfo, state_dict, timer
 
     sd_vae.delete_base_vae()
     sd_vae.clear_loaded_vae()
-    vae_file, vae_source = sd_vae.resolve_vae(checkpoint_info.filename)
+    vae_file, vae_source = sd_vae.resolve_vae(checkpoint_info.filename).tuple()
     sd_vae.load_vae(model, vae_file, vae_source)
     timer.record("load VAE")
 

modules/sd_vae.py

@@ -1,5 +1,7 @@
 import os
 import collections
+from dataclasses import dataclass
+
 from modules import paths, shared, devices, script_callbacks, sd_models, extra_networks
 import glob
 from copy import deepcopy
@@ -97,37 +99,74 @@ def find_vae_near_checkpoint(checkpoint_file):
     return None
 
 
-def resolve_vae(checkpoint_file):
+@dataclass
-    if shared.cmd_opts.vae_path is not None:
+class VaeResolution:
-        return shared.cmd_opts.vae_path, 'from commandline argument'
+    vae: str = None
+    source: str = None
+    resolved: bool = True
 
+    def tuple(self):
+        return self.vae, self.source
+
+
+def is_automatic():
+    return shared.opts.sd_vae in {"Automatic", "auto"}  # "auto" for people with old config
+
+
+def resolve_vae_from_setting() -> VaeResolution:
+    if shared.opts.sd_vae == "None":
+        return VaeResolution()
+
+    vae_from_options = vae_dict.get(shared.opts.sd_vae, None)
+    if vae_from_options is not None:
+        return VaeResolution(vae_from_options, 'specified in settings')
+
+    if not is_automatic():
+        print(f"Couldn't find VAE named {shared.opts.sd_vae}; using None instead")
+
+    return VaeResolution(resolved=False)
+
+
+def resolve_vae_from_user_metadata(checkpoint_file) -> VaeResolution:
     metadata = extra_networks.get_user_metadata(checkpoint_file)
     vae_metadata = metadata.get("vae", None)
     if vae_metadata is not None and vae_metadata != "Automatic":
         if vae_metadata == "None":
-            return None, None
+            return VaeResolution()
 
         vae_from_metadata = vae_dict.get(vae_metadata, None)
         if vae_from_metadata is not None:
-            return vae_from_metadata, "from user metadata"
+            return VaeResolution(vae_from_metadata, "from user metadata")
 
-    is_automatic = shared.opts.sd_vae in {"Automatic", "auto"}  # "auto" for people with old config
+    return VaeResolution(resolved=False)
 
+
+def resolve_vae_near_checkpoint(checkpoint_file) -> VaeResolution:
     vae_near_checkpoint = find_vae_near_checkpoint(checkpoint_file)
     if vae_near_checkpoint is not None and (shared.opts.sd_vae_as_default or is_automatic):
-        return vae_near_checkpoint, 'found near the checkpoint'
+        return VaeResolution(vae_near_checkpoint, 'found near the checkpoint')
 
-    if shared.opts.sd_vae == "None":
+    return VaeResolution(resolved=False)
-        return None, None
 
-    vae_from_options = vae_dict.get(shared.opts.sd_vae, None)
-    if vae_from_options is not None:
-        return vae_from_options, 'specified in settings'
 
-    if not is_automatic:
+def resolve_vae(checkpoint_file) -> VaeResolution:
-        print(f"Couldn't find VAE named {shared.opts.sd_vae}; using None instead")
+    if shared.cmd_opts.vae_path is not None:
+        return VaeResolution(shared.cmd_opts.vae_path, 'from commandline argument')
 
-    return None, None
+    if shared.opts.sd_vae_overrides_per_model_preferences and not is_automatic():
+        return resolve_vae_from_setting()
+
+    res = resolve_vae_from_user_metadata(checkpoint_file)
+    if res.resolved:
+        return res
+
+    res = resolve_vae_near_checkpoint(checkpoint_file)
+    if res.resolved:
+        return res
+
+    res = resolve_vae_from_setting()
+
+    return res
 
 
 def load_vae_dict(filename, map_location):
@@ -201,7 +240,7 @@ def reload_vae_weights(sd_model=None, vae_file=unspecified):
     checkpoint_file = checkpoint_info.filename
 
     if vae_file == unspecified:
-        vae_file, vae_source = resolve_vae(checkpoint_file)
+        vae_file, vae_source = resolve_vae(checkpoint_file).tuple()
     else:
         vae_source = "from function argument"
 

modules/shared.py

@@ -479,7 +479,7 @@ For img2img, VAE is used to process user's input image before the sampling, and
 """),
     "sd_vae_checkpoint_cache": OptionInfo(0, "VAE Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}),
     "sd_vae": OptionInfo("Automatic", "SD VAE", gr.Dropdown, lambda: {"choices": shared_items.sd_vae_items()}, refresh=shared_items.refresh_vae_list).info("choose VAE model: Automatic = use one with same filename as checkpoint; None = use VAE from checkpoint"),
-    "sd_vae_as_default": OptionInfo(True, "Ignore selected VAE for stable diffusion checkpoints that have their own .vae.pt next to them"),
+    "sd_vae_overrides_per_model_preferences": OptionInfo(True, "Selected VAE overrides per-model preferences").info("you can set per-model VAE either by editing user metadata for checkpoints, or by making the VAE have same name as checkpoint"),
     "auto_vae_precision": OptionInfo(True, "Automaticlly revert VAE to 32-bit floats").info("triggers when a tensor with NaNs is produced in VAE; disabling the option in this case will result in a black square image"),
     "sd_vae_encode_method": OptionInfo("Full", "VAE type for encode", gr.Radio, {"choices": ["Full", "TAESD"]}).info("method to encode image to latent (use in img2img, hires-fix or inpaint mask)"),
     "sd_vae_decode_method": OptionInfo("Full", "VAE type for decode", gr.Radio, {"choices": ["Full", "TAESD"]}).info("method to decode latent to image"),
@@ -733,6 +733,10 @@ class Options:
         with open(filename, "r", encoding="utf8") as file:
             self.data = json.load(file)
 
+        # 1.6.0 VAE defaults
+        if self.data.get('sd_vae_as_default') is not None and self.data.get('sd_vae_overrides_per_model_preferences') is None:
+            self.data['sd_vae_overrides_per_model_preferences'] = not self.data.get('sd_vae_as_default')
+
         # 1.1.1 quicksettings list migration
         if self.data.get('quicksettings') is not None and self.data.get('quicksettings_list') is None:
             self.data['quicksettings_list'] = [i.strip() for i in self.data.get('quicksettings').split(',')]

modules/ui_extra_networks_checkpoints_user_metadata.py

@@ -1,6 +1,6 @@
 import gradio as gr
 
-from modules import ui_extra_networks_user_metadata, sd_vae
+from modules import ui_extra_networks_user_metadata, sd_vae, shared
 from modules.ui_common import create_refresh_button
 
 
@@ -18,6 +18,10 @@ class CheckpointUserMetadataEditor(ui_extra_networks_user_metadata.UserMetadataE
 
         self.write_user_metadata(name, user_metadata)
 
+    def update_vae(self, name):
+        if name == shared.sd_model.sd_checkpoint_info.name_for_extra:
+            sd_vae.reload_vae_weights()
+
     def put_values_into_components(self, name):
         user_metadata = self.get_user_metadata(name)
         values = super().put_values_into_components(name)
@@ -58,3 +62,5 @@ class CheckpointUserMetadataEditor(ui_extra_networks_user_metadata.UserMetadataE
         ]
 
         self.setup_save_handler(self.button_save, self.save_user_metadata, edited_components)
+        self.button_save.click(fn=self.update_vae, inputs=[self.edit_name_input])
+

webui.py

@@ -211,7 +211,7 @@ def configure_sigint_handler():
 def configure_opts_onchange():
     shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights()), call=False)
     shared.opts.onchange("sd_vae", wrap_queued_call(lambda: modules.sd_vae.reload_vae_weights()), call=False)
-    shared.opts.onchange("sd_vae_as_default", wrap_queued_call(lambda: modules.sd_vae.reload_vae_weights()), call=False)
+    shared.opts.onchange("sd_vae_overrides_per_model_preferences", wrap_queued_call(lambda: modules.sd_vae.reload_vae_weights()), call=False)
     shared.opts.onchange("temp_dir", ui_tempdir.on_tmpdir_changed)
     shared.opts.onchange("gradio_theme", shared.reload_gradio_theme)
     shared.opts.onchange("cross_attention_optimization", wrap_queued_call(lambda: modules.sd_hijack.model_hijack.redo_hijack(shared.sd_model)), call=False)