Merge branch 'v1.2.0-hotfix' into release_candidate

This commit is contained in:
AUTOMATIC 2023-05-13 20:25:03 +03:00
commit 2053745c8f
9 changed files with 47 additions and 26 deletions

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@ -1,3 +1,14 @@
## Upcoming 1.2.1
### Features:
* add an option to always refer to lora by filenames
### Bug Fixes:
* never refer to lora by an alias if multiple loras have same alias or the alias is called none
* fix upscalers disappearing after the user reloads UI
* allow bf16 in safe unpickler (resolves problems with loading some loras)
* allow web UI to be ran fully offline
## 1.2.0 ## 1.2.0
### Features: ### Features:

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@ -393,6 +393,8 @@ def lora_MultiheadAttention_load_state_dict(self, *args, **kwargs):
def list_available_loras(): def list_available_loras():
available_loras.clear() available_loras.clear()
available_lora_aliases.clear() available_lora_aliases.clear()
forbidden_lora_aliases.clear()
forbidden_lora_aliases.update({"none": 1})
os.makedirs(shared.cmd_opts.lora_dir, exist_ok=True) os.makedirs(shared.cmd_opts.lora_dir, exist_ok=True)
@ -406,6 +408,9 @@ def list_available_loras():
available_loras[name] = entry available_loras[name] = entry
if entry.alias in available_lora_aliases:
forbidden_lora_aliases[entry.alias.lower()] = 1
available_lora_aliases[name] = entry available_lora_aliases[name] = entry
available_lora_aliases[entry.alias] = entry available_lora_aliases[entry.alias] = entry
@ -445,6 +450,7 @@ def infotext_pasted(infotext, params):
available_loras = {} available_loras = {}
available_lora_aliases = {} available_lora_aliases = {}
forbidden_lora_aliases = {}
loaded_loras = [] loaded_loras = []
list_available_loras() list_available_loras()

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@ -54,6 +54,7 @@ script_callbacks.on_infotext_pasted(lora.infotext_pasted)
shared.options_templates.update(shared.options_section(('extra_networks', "Extra Networks"), { shared.options_templates.update(shared.options_section(('extra_networks', "Extra Networks"), {
"sd_lora": shared.OptionInfo("None", "Add Lora to prompt", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in lora.available_loras]}, refresh=lora.list_available_loras), "sd_lora": shared.OptionInfo("None", "Add Lora to prompt", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in lora.available_loras]}, refresh=lora.list_available_loras),
"lora_preferred_name": shared.OptionInfo("Alias from file", "When adding to prompt, refer to lora by", gr.Radio, {"choices": ["Alias from file", "Filename"]}),
})) }))

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@ -15,13 +15,19 @@ class ExtraNetworksPageLora(ui_extra_networks.ExtraNetworksPage):
def list_items(self): def list_items(self):
for name, lora_on_disk in lora.available_loras.items(): for name, lora_on_disk in lora.available_loras.items():
path, ext = os.path.splitext(lora_on_disk.filename) path, ext = os.path.splitext(lora_on_disk.filename)
if shared.opts.lora_preferred_name == "Filename" or lora_on_disk.alias.lower() in lora.forbidden_lora_aliases:
alias = name
else:
alias = lora_on_disk.alias
yield { yield {
"name": name, "name": name,
"filename": path, "filename": path,
"preview": self.find_preview(path), "preview": self.find_preview(path),
"description": self.find_description(path), "description": self.find_description(path),
"search_term": self.search_terms_from_path(lora_on_disk.filename), "search_term": self.search_terms_from_path(lora_on_disk.filename),
"prompt": json.dumps(f"<lora:{lora_on_disk.alias}:") + " + opts.extra_networks_default_multiplier + " + json.dumps(">"), "prompt": json.dumps(f"<lora:{alias}:") + " + opts.extra_networks_default_multiplier + " + json.dumps(">"),
"local_preview": f"{path}.{shared.opts.samples_format}", "local_preview": f"{path}.{shared.opts.samples_format}",
"metadata": json.dumps(lora_on_disk.metadata, indent=4) if lora_on_disk.metadata else None, "metadata": json.dumps(lora_on_disk.metadata, indent=4) if lora_on_disk.metadata else None,
} }

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@ -117,20 +117,6 @@ def move_files(src_path: str, dest_path: str, ext_filter: str = None):
pass pass
builtin_upscaler_classes = []
forbidden_upscaler_classes = set()
def list_builtin_upscalers():
builtin_upscaler_classes.clear()
builtin_upscaler_classes.extend(Upscaler.__subclasses__())
def forbid_loaded_nonbuiltin_upscalers():
for cls in Upscaler.__subclasses__():
if cls not in builtin_upscaler_classes:
forbidden_upscaler_classes.add(cls)
def load_upscalers(): def load_upscalers():
# We can only do this 'magic' method to dynamically load upscalers if they are referenced, # We can only do this 'magic' method to dynamically load upscalers if they are referenced,
# so we'll try to import any _model.py files before looking in __subclasses__ # so we'll try to import any _model.py files before looking in __subclasses__
@ -146,10 +132,17 @@ def load_upscalers():
datas = [] datas = []
commandline_options = vars(shared.cmd_opts) commandline_options = vars(shared.cmd_opts)
for cls in Upscaler.__subclasses__():
if cls in forbidden_upscaler_classes:
continue
# some of upscaler classes will not go away after reloading their modules, and we'll end
# up with two copies of those classes. The newest copy will always be the last in the list,
# so we go from end to beginning and ignore duplicates
used_classes = {}
for cls in reversed(Upscaler.__subclasses__()):
classname = str(cls)
if classname not in used_classes:
used_classes[classname] = cls
for cls in reversed(used_classes.values()):
name = cls.__name__ name = cls.__name__
cmd_name = f"{name.lower().replace('upscaler', '')}_models_path" cmd_name = f"{name.lower().replace('upscaler', '')}_models_path"
scaler = cls(commandline_options.get(cmd_name, None)) scaler = cls(commandline_options.get(cmd_name, None))

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@ -40,7 +40,7 @@ class RestrictedUnpickler(pickle.Unpickler):
return getattr(collections, name) return getattr(collections, name)
if module == 'torch._utils' and name in ['_rebuild_tensor_v2', '_rebuild_parameter', '_rebuild_device_tensor_from_numpy']: if module == 'torch._utils' and name in ['_rebuild_tensor_v2', '_rebuild_parameter', '_rebuild_device_tensor_from_numpy']:
return getattr(torch._utils, name) return getattr(torch._utils, name)
if module == 'torch' and name in ['FloatStorage', 'HalfStorage', 'IntStorage', 'LongStorage', 'DoubleStorage', 'ByteStorage', 'float32']: if module == 'torch' and name in ['FloatStorage', 'HalfStorage', 'IntStorage', 'LongStorage', 'DoubleStorage', 'ByteStorage', 'float32', 'BFloat16Storage']:
return getattr(torch, name) return getattr(torch, name)
if module == 'torch.nn.modules.container' and name in ['ParameterDict']: if module == 'torch.nn.modules.container' and name in ['ParameterDict']:
return getattr(torch.nn.modules.container, name) return getattr(torch.nn.modules.container, name)

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@ -667,14 +667,19 @@ def reload_gradio_theme(theme_name=None):
if not theme_name: if not theme_name:
theme_name = opts.gradio_theme theme_name = opts.gradio_theme
default_theme_args = dict(
font=["Source Sans Pro", 'ui-sans-serif', 'system-ui', 'sans-serif'],
font_mono=['IBM Plex Mono', 'ui-monospace', 'Consolas', 'monospace'],
)
if theme_name == "Default": if theme_name == "Default":
gradio_theme = gr.themes.Default() gradio_theme = gr.themes.Default(**default_theme_args)
else: else:
try: try:
gradio_theme = gr.themes.ThemeClass.from_hub(theme_name) gradio_theme = gr.themes.ThemeClass.from_hub(theme_name)
except Exception as e: except Exception as e:
errors.display(e, "changing gradio theme") errors.display(e, "changing gradio theme")
gradio_theme = gr.themes.Default() gradio_theme = gr.themes.Default(**default_theme_args)

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@ -1,3 +1,6 @@
/* temporary fix to load default gradio font in frontend instead of backend */
@import url('https://fonts.googleapis.com/css2?family=Source+Sans+Pro:wght@400;600&display=swap');
/* general gradio fixes */ /* general gradio fixes */

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@ -181,14 +181,11 @@ def initialize():
gfpgan.setup_model(cmd_opts.gfpgan_models_path) gfpgan.setup_model(cmd_opts.gfpgan_models_path)
startup_timer.record("setup gfpgan") startup_timer.record("setup gfpgan")
modelloader.list_builtin_upscalers()
startup_timer.record("list builtin upscalers")
modules.scripts.load_scripts() modules.scripts.load_scripts()
startup_timer.record("load scripts") startup_timer.record("load scripts")
modelloader.load_upscalers() modelloader.load_upscalers()
#startup_timer.record("load upscalers") #Is this necessary? I don't know. startup_timer.record("load upscalers") #Is this necessary? I don't know.
modules.sd_vae.refresh_vae_list() modules.sd_vae.refresh_vae_list()
startup_timer.record("refresh VAE") startup_timer.record("refresh VAE")
@ -388,7 +385,6 @@ def webui():
localization.list_localizations(cmd_opts.localizations_dir) localization.list_localizations(cmd_opts.localizations_dir)
modelloader.forbid_loaded_nonbuiltin_upscalers()
modules.scripts.reload_scripts() modules.scripts.reload_scripts()
startup_timer.record("load scripts") startup_timer.record("load scripts")