diff --git a/CHANGELOG.md b/CHANGELOG.md index 8d2f96e5..d1727864 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,3 +1,48 @@ +## 1.2.0 + +### Features: + * do not wait for stable diffusion model to load at startup + * add filename patterns: [denoising] + * directory hiding for extra networks: dirs starting with . will hide their cards on extra network tabs unless specifically searched for + * Lora: for the `<...>` text in prompt, use name of Lora that is in the metdata of the file, if present, instead of filename (both can be used to activate lora) + * Lora: read infotext params from kohya-ss's extension parameters if they are present and if his extension is not active + * Lora: Fix some Loras not working (ones that have 3x3 convolution layer) + * Lora: add an option to use old method of applying loras (producing same results as with kohya-ss) + * add version to infotext, footer and console output when starting + * add links to wiki for filename pattern settings + * add extended info for quicksettings setting and use multiselect input instead of a text field + +### Minor: + * gradio bumped to 3.29.0 + * torch bumped to 2.0.1 + * --subpath option for gradio for use with reverse proxy + * linux/OSX: use existing virtualenv if already active (the VIRTUAL_ENV environment variable) + * possible frontend optimization: do not apply localizations if there are none + * Add extra `None` option for VAE in XYZ plot + * print error to console when batch processing in img2img fails + * create HTML for extra network pages only on demand + * allow directories starting with . to still list their models for lora, checkpoints, etc + * put infotext options into their own category in settings tab + * do not show licenses page when user selects Show all pages in settings + +### Extensions: + * Tooltip localization support + * Add api method to get LoRA models with prompt + +### Bug Fixes: + * re-add /docs endpoint + * fix gamepad navigation + * make the lightbox fullscreen image function properly + * fix squished thumbnails in extras tab + * keep "search" filter for extra networks when user refreshes the tab (previously it showed everthing after you refreshed) + * fix webui showing the same image if you configure the generation to always save results into same file + * fix bug with upscalers not working properly + * Fix MPS on PyTorch 2.0.1, Intel Macs + * make it so that custom context menu from contextMenu.js only disappears after user's click, ignoring non-user click events + * prevent Reload UI button/link from reloading the page when it's not yet ready + * fix prompts from file script failing to read contents from a drag/drop file + + ## 1.1.1 ### Bug Fixes: * fix an error that prevents running webui on torch<2.0 without --disable-safe-unpickle diff --git a/extensions-builtin/Lora/extra_networks_lora.py b/extensions-builtin/Lora/extra_networks_lora.py index 45f899fc..ccb249ac 100644 --- a/extensions-builtin/Lora/extra_networks_lora.py +++ b/extensions-builtin/Lora/extra_networks_lora.py @@ -1,6 +1,7 @@ from modules import extra_networks, shared import lora + class ExtraNetworkLora(extra_networks.ExtraNetwork): def __init__(self): super().__init__('lora') diff --git a/extensions-builtin/Lora/lora.py b/extensions-builtin/Lora/lora.py index 6f246921..ba1293df 100644 --- a/extensions-builtin/Lora/lora.py +++ b/extensions-builtin/Lora/lora.py @@ -4,7 +4,7 @@ import re import torch from typing import Union -from modules import shared, devices, sd_models, errors +from modules import shared, devices, sd_models, errors, scripts metadata_tags_order = {"ss_sd_model_name": 1, "ss_resolution": 2, "ss_clip_skip": 3, "ss_num_train_images": 10, "ss_tag_frequency": 20} @@ -93,6 +93,7 @@ class LoraOnDisk: self.metadata = m self.ssmd_cover_images = self.metadata.pop('ssmd_cover_images', None) # those are cover images and they are too big to display in UI as text + self.alias = self.metadata.get('ss_output_name', self.name) class LoraModule: @@ -165,8 +166,10 @@ def load_lora(name, filename): module = torch.nn.Linear(weight.shape[1], weight.shape[0], bias=False) elif type(sd_module) == torch.nn.MultiheadAttention: module = torch.nn.Linear(weight.shape[1], weight.shape[0], bias=False) - elif type(sd_module) == torch.nn.Conv2d: + elif type(sd_module) == torch.nn.Conv2d and weight.shape[2:] == (1, 1): module = torch.nn.Conv2d(weight.shape[1], weight.shape[0], (1, 1), bias=False) + elif type(sd_module) == torch.nn.Conv2d and weight.shape[2:] == (3, 3): + module = torch.nn.Conv2d(weight.shape[1], weight.shape[0], (3, 3), bias=False) else: print(f'Lora layer {key_diffusers} matched a layer with unsupported type: {type(sd_module).__name__}') continue @@ -199,11 +202,11 @@ def load_loras(names, multipliers=None): loaded_loras.clear() - loras_on_disk = [available_loras.get(name, None) for name in names] + loras_on_disk = [available_lora_aliases.get(name, None) for name in names] if any([x is None for x in loras_on_disk]): list_available_loras() - loras_on_disk = [available_loras.get(name, None) for name in names] + loras_on_disk = [available_lora_aliases.get(name, None) for name in names] for i, name in enumerate(names): lora = already_loaded.get(name, None) @@ -232,6 +235,8 @@ def lora_calc_updown(lora, module, target): if up.shape[2:] == (1, 1) and down.shape[2:] == (1, 1): updown = (up.squeeze(2).squeeze(2) @ down.squeeze(2).squeeze(2)).unsqueeze(2).unsqueeze(3) + elif up.shape[2:] == (3, 3) or down.shape[2:] == (3, 3): + updown = torch.nn.functional.conv2d(down.permute(1, 0, 2, 3), up).permute(1, 0, 2, 3) else: updown = up @ down @@ -240,6 +245,19 @@ def lora_calc_updown(lora, module, target): return updown +def lora_restore_weights_from_backup(self: Union[torch.nn.Conv2d, torch.nn.Linear, torch.nn.MultiheadAttention]): + weights_backup = getattr(self, "lora_weights_backup", None) + + if weights_backup is None: + return + + if isinstance(self, torch.nn.MultiheadAttention): + self.in_proj_weight.copy_(weights_backup[0]) + self.out_proj.weight.copy_(weights_backup[1]) + else: + self.weight.copy_(weights_backup) + + def lora_apply_weights(self: Union[torch.nn.Conv2d, torch.nn.Linear, torch.nn.MultiheadAttention]): """ Applies the currently selected set of Loras to the weights of torch layer self. @@ -264,12 +282,7 @@ def lora_apply_weights(self: Union[torch.nn.Conv2d, torch.nn.Linear, torch.nn.Mu self.lora_weights_backup = weights_backup if current_names != wanted_names: - if weights_backup is not None: - if isinstance(self, torch.nn.MultiheadAttention): - self.in_proj_weight.copy_(weights_backup[0]) - self.out_proj.weight.copy_(weights_backup[1]) - else: - self.weight.copy_(weights_backup) + lora_restore_weights_from_backup(self) for lora in loaded_loras: module = lora.modules.get(lora_layer_name, None) @@ -300,12 +313,45 @@ def lora_apply_weights(self: Union[torch.nn.Conv2d, torch.nn.Linear, torch.nn.Mu setattr(self, "lora_current_names", wanted_names) +def lora_forward(module, input, original_forward): + """ + Old way of applying Lora by executing operations during layer's forward. + Stacking many loras this way results in big performance degradation. + """ + + if len(loaded_loras) == 0: + return original_forward(module, input) + + input = devices.cond_cast_unet(input) + + lora_restore_weights_from_backup(module) + lora_reset_cached_weight(module) + + res = original_forward(module, input) + + lora_layer_name = getattr(module, 'lora_layer_name', None) + for lora in loaded_loras: + module = lora.modules.get(lora_layer_name, None) + if module is None: + continue + + module.up.to(device=devices.device) + module.down.to(device=devices.device) + + res = res + module.up(module.down(input)) * lora.multiplier * (module.alpha / module.up.weight.shape[1] if module.alpha else 1.0) + + return res + + def lora_reset_cached_weight(self: Union[torch.nn.Conv2d, torch.nn.Linear]): setattr(self, "lora_current_names", ()) setattr(self, "lora_weights_backup", None) def lora_Linear_forward(self, input): + if shared.opts.lora_functional: + return lora_forward(self, input, torch.nn.Linear_forward_before_lora) + lora_apply_weights(self) return torch.nn.Linear_forward_before_lora(self, input) @@ -318,6 +364,9 @@ def lora_Linear_load_state_dict(self, *args, **kwargs): def lora_Conv2d_forward(self, input): + if shared.opts.lora_functional: + return lora_forward(self, input, torch.nn.Conv2d_forward_before_lora) + lora_apply_weights(self) return torch.nn.Conv2d_forward_before_lora(self, input) @@ -343,24 +392,59 @@ def lora_MultiheadAttention_load_state_dict(self, *args, **kwargs): def list_available_loras(): available_loras.clear() + available_lora_aliases.clear() os.makedirs(shared.cmd_opts.lora_dir, exist_ok=True) - candidates = \ - glob.glob(os.path.join(shared.cmd_opts.lora_dir, '**/*.pt'), recursive=True) + \ - glob.glob(os.path.join(shared.cmd_opts.lora_dir, '**/*.safetensors'), recursive=True) + \ - glob.glob(os.path.join(shared.cmd_opts.lora_dir, '**/*.ckpt'), recursive=True) - + candidates = list(shared.walk_files(shared.cmd_opts.lora_dir, allowed_extensions=[".pt", ".ckpt", ".safetensors"])) for filename in sorted(candidates, key=str.lower): if os.path.isdir(filename): continue name = os.path.splitext(os.path.basename(filename))[0] + entry = LoraOnDisk(name, filename) - available_loras[name] = LoraOnDisk(name, filename) + available_loras[name] = entry + available_lora_aliases[name] = entry + available_lora_aliases[entry.alias] = entry + + +re_lora_name = re.compile(r"(.*)\s*\([0-9a-fA-F]+\)") + + +def infotext_pasted(infotext, params): + if "AddNet Module 1" in [x[1] for x in scripts.scripts_txt2img.infotext_fields]: + return # if the other extension is active, it will handle those fields, no need to do anything + + added = [] + + for k, v in params.items(): + if not k.startswith("AddNet Model "): + continue + + num = k[13:] + + if params.get("AddNet Module " + num) != "LoRA": + continue + + name = params.get("AddNet Model " + num) + if name is None: + continue + + m = re_lora_name.match(name) + if m: + name = m.group(1) + + multiplier = params.get("AddNet Weight A " + num, "1.0") + + added.append(f"") + + if added: + params["Prompt"] += "\n" + "".join(added) available_loras = {} +available_lora_aliases = {} loaded_loras = [] list_available_loras() diff --git a/extensions-builtin/Lora/scripts/lora_script.py b/extensions-builtin/Lora/scripts/lora_script.py index 3fc38ab9..7db971fd 100644 --- a/extensions-builtin/Lora/scripts/lora_script.py +++ b/extensions-builtin/Lora/scripts/lora_script.py @@ -1,12 +1,12 @@ import torch import gradio as gr +from fastapi import FastAPI import lora import extra_networks_lora import ui_extra_networks_lora from modules import script_callbacks, ui_extra_networks, extra_networks, shared - def unload(): torch.nn.Linear.forward = torch.nn.Linear_forward_before_lora torch.nn.Linear._load_from_state_dict = torch.nn.Linear_load_state_dict_before_lora @@ -49,8 +49,33 @@ torch.nn.MultiheadAttention._load_from_state_dict = lora.lora_MultiheadAttention script_callbacks.on_model_loaded(lora.assign_lora_names_to_compvis_modules) script_callbacks.on_script_unloaded(unload) script_callbacks.on_before_ui(before_ui) +script_callbacks.on_infotext_pasted(lora.infotext_pasted) 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), })) + + +shared.options_templates.update(shared.options_section(('compatibility', "Compatibility"), { + "lora_functional": shared.OptionInfo(False, "Lora: use old method that takes longer when you have multiple Loras active and produces same results as kohya-ss/sd-webui-additional-networks extension"), +})) + + +def create_lora_json(obj: lora.LoraOnDisk): + return { + "name": obj.name, + "alias": obj.alias, + "path": obj.filename, + "metadata": obj.metadata, + } + + +def api_loras(_: gr.Blocks, app: FastAPI): + @app.get("/sdapi/v1/loras") + async def get_loras(): + return [create_lora_json(obj) for obj in lora.available_loras.values()] + + +script_callbacks.on_app_started(api_loras) + diff --git a/extensions-builtin/Lora/ui_extra_networks_lora.py b/extensions-builtin/Lora/ui_extra_networks_lora.py index e0c00971..9c4150fa 100644 --- a/extensions-builtin/Lora/ui_extra_networks_lora.py +++ b/extensions-builtin/Lora/ui_extra_networks_lora.py @@ -21,7 +21,7 @@ class ExtraNetworksPageLora(ui_extra_networks.ExtraNetworksPage): "preview": self.find_preview(path) if self.find_preview(path) else './file=html/card-no-preview.png', "description": self.find_description(path), "search_term": self.search_terms_from_path(lora_on_disk.filename), - "prompt": json.dumps(f""), + "prompt": json.dumps(f""), "local_preview": f"{path}.{shared.opts.samples_format}", "metadata": json.dumps(lora_on_disk.metadata, indent=4) if lora_on_disk.metadata else None, } diff --git a/html/extra-networks-card.html b/html/extra-networks-card.html index 7032f8d2..043939d5 100644 --- a/html/extra-networks-card.html +++ b/html/extra-networks-card.html @@ -12,7 +12,6 @@ {name} {description} - diff --git a/javascript/contextMenus.js b/javascript/contextMenus.js index 41b8582f..8c9a4d8e 100644 --- a/javascript/contextMenus.js +++ b/javascript/contextMenus.js @@ -97,42 +97,39 @@ contextMenuInit = function () { }); } - function addContextMenuEventListener() { - if (eventListenerApplied) { + function addContextMenuEventListener(){ + if(eventListenerApplied){ return; } - gradioApp().addEventListener("click", function (e) { - let source = e.composedPath()[0]; - if (source.id && source.id.indexOf("check_progress") > -1) { - return; + gradioApp().addEventListener("click", function(e) { + if(! e.isTrusted){ + return } - let oldMenu = gradioApp().querySelector("#context-menu"); - if (oldMenu) { - oldMenu.remove(); + let oldMenu = gradioApp().querySelector('#context-menu') + if(oldMenu){ + oldMenu.remove() } }); - gradioApp().addEventListener("contextmenu", function (e) { - let oldMenu = gradioApp().querySelector("#context-menu"); - if (oldMenu) { - oldMenu.remove(); + gradioApp().addEventListener("contextmenu", function(e) { + let oldMenu = gradioApp().querySelector('#context-menu') + if(oldMenu){ + oldMenu.remove() } - menuSpecs.forEach(function (v, k) { - if (e.composedPath()[0].matches(k)) { - showContextMenu(e, e.composedPath()[0], v); - e.preventDefault(); + menuSpecs.forEach(function(v,k) { + if(e.composedPath()[0].matches(k)){ + showContextMenu(e,e.composedPath()[0],v) + e.preventDefault() } - }); + }) }); - eventListenerApplied = true; + eventListenerApplied=true + } - return [ - appendContextMenuOption, - removeContextMenuOption, - addContextMenuEventListener, - ]; -}; + return [appendContextMenuOption, removeContextMenuOption, addContextMenuEventListener] +} + initResponse = contextMenuInit(); appendContextMenuOption = initResponse[0]; diff --git a/javascript/extraNetworks.js b/javascript/extraNetworks.js index da1ffc6b..c939d04b 100644 --- a/javascript/extraNetworks.js +++ b/javascript/extraNetworks.js @@ -3,11 +3,11 @@ function setupExtraNetworksForTab(tabname) { .querySelector("#" + tabname + "_extra_tabs") .classList.add("extra-networks"); - var tabs = gradioApp().querySelector("#" + tabname + "_extra_tabs > div"); - var search = gradioApp().querySelector( + let tabs = gradioApp().querySelector("#" + tabname + "_extra_tabs > div"); + let search = gradioApp().querySelector( "#" + tabname + "_extra_search textarea" ); - var refresh = gradioApp().getElementById(tabname + "_extra_refresh"); + let refresh = gradioApp().getElementById(tabname + "_extra_refresh"); let clear = document.createElement("div"); clear.id = tabname + "_extra_clear"; @@ -33,7 +33,7 @@ function setupExtraNetworksForTab(tabname) { gradioApp() .querySelectorAll("#" + tabname + "_extra_tabs div.card") .forEach(function (elem) { - var text = + let text = elem.querySelector(".name").textContent.toLowerCase() + " " + elem.querySelector(".search_term").textContent.toLowerCase(); @@ -43,6 +43,11 @@ function setupExtraNetworksForTab(tabname) { }); } +function applyExtraNetworkFilter(tabname){ + setTimeout(extraNetworksApplyFilter[tabname], 1); +} + +var extraNetworksApplyFilter = {} var activePromptTextarea = {}; function setupExtraNetworks() { diff --git a/javascript/hints.js b/javascript/hints.js index 6bce4696..d9e0399d 100644 --- a/javascript/hints.js +++ b/javascript/hints.js @@ -75,8 +75,8 @@ titles = { "Interrogate": "Reconstruct prompt from existing image and put it into the prompt field.", - "Images filename pattern": "Use following tags to define how filenames for images are chosen: [steps], [cfg], [clip_skip], [batch_number], [generation_number], [prompt_hash], [prompt], [prompt_no_styles], [prompt_spaces], [width], [height], [styles], [sampler], [seed], [model_hash], [model_name], [prompt_words], [date], [datetime], [datetime], [datetime