Merge branch 'dev' into move-start-timer

modules/api/models.py

@@ -1,5 +1,4 @@
 import inspect
-import types
 
 from pydantic import BaseModel, Field, create_model
 from typing import Any, Optional
@@ -209,11 +208,9 @@ class PreprocessResponse(BaseModel):
 fields = {}
 for key, metadata in opts.data_labels.items():
     value = opts.data.get(key)
-    if key == 'sd_model_checkpoint':
-        value = None
-    optType = opts.typemap.get(type(metadata.default), type(value))
+    optType = opts.typemap.get(type(metadata.default), type(metadata.default))
 
-    if isinstance(optType, types.NoneType):
+    if metadata.default is None:
         pass
     elif metadata is not None:
         fields.update({key: (Optional[optType], Field(default=metadata.default, description=metadata.label))})

modules/cmd_args.py

@@ -15,6 +15,7 @@ parser.add_argument("--update-check", action='store_true', help="launch.py argum
 parser.add_argument("--test-server", action='store_true', help="launch.py argument: configure server for testing")
 parser.add_argument("--skip-prepare-environment", action='store_true', help="launch.py argument: skip all environment preparation")
 parser.add_argument("--skip-install", action='store_true', help="launch.py argument: skip installation of packages")
+parser.add_argument("--do-not-download-clip", action='store_true', help="do not download CLIP model even if it's not included in the checkpoint")
 parser.add_argument("--data-dir", type=str, default=os.path.dirname(os.path.dirname(os.path.realpath(__file__))), help="base path where all user data is stored")
 parser.add_argument("--config", type=str, default=sd_default_config, help="path to config which constructs model",)
 parser.add_argument("--ckpt", type=str, default=sd_model_file, help="path to checkpoint of stable diffusion model; if specified, this checkpoint will be added to the list of checkpoints and loaded",)

modules/script_loading.py

@@ -12,11 +12,12 @@ def load_module(path):
     return module
 
 
-def preload_extensions(extensions_dir, parser):
+def preload_extensions(extensions_dir, parser, extension_list=None):
     if not os.path.isdir(extensions_dir):
         return
 
-    for dirname in sorted(os.listdir(extensions_dir)):
+    extensions = extension_list if extension_list is not None else os.listdir(extensions_dir)
+    for dirname in sorted(extensions):
         preload_script = os.path.join(extensions_dir, dirname, "preload.py")
         if not os.path.isfile(preload_script):
             continue

modules/sd_models.py

@@ -494,7 +494,7 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None):
 
     sd_model = None
     try:
-        with sd_disable_initialization.DisableInitialization(disable_clip=clip_is_included_into_sd):
+        with sd_disable_initialization.DisableInitialization(disable_clip=clip_is_included_into_sd or shared.cmd_opts.do_not_download_clip):
             sd_model = instantiate_from_config(sd_config.model)
     except Exception:
         pass

modules/shared.py

@@ -11,6 +11,7 @@ import gradio as gr
 import torch
 import tqdm
 
+import launch
 import modules.interrogate
 import modules.memmon
 import modules.styles
@@ -26,7 +27,7 @@ demo = None
 
 parser = cmd_args.parser
 
-script_loading.preload_extensions(extensions_dir, parser)
+script_loading.preload_extensions(extensions_dir, parser, extension_list=launch.list_extensions(launch.args.ui_settings_file))
 script_loading.preload_extensions(extensions_builtin_dir, parser)
 
 if os.environ.get('IGNORE_CMD_ARGS_ERRORS', None) is None:
@@ -409,7 +410,7 @@ options_templates.update(options_section(('training', "Training"), {
 }))
 
 options_templates.update(options_section(('sd', "Stable Diffusion"), {
-    "sd_model_checkpoint": OptionInfo("", "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": list_checkpoint_tiles()}, refresh=refresh_checkpoints),
+    "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": list_checkpoint_tiles()}, refresh=refresh_checkpoints),
     "sd_checkpoint_cache": OptionInfo(0, "Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}),
     "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"),