From da464a3fb39ecc6ea7b22fe87271194480d8501c Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Wed, 12 Jul 2023 23:52:43 +0300 Subject: SDXL support --- modules/shared.py | 2 ++ 1 file changed, 2 insertions(+) (limited to 'modules/shared.py') diff --git a/modules/shared.py b/modules/shared.py index b7518de6..71afd94f 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -428,6 +428,8 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "CLIP_stop_at_last_layers": OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}).link("wiki", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#clip-skip").info("ignore last layers of CLIP network; 1 ignores none, 2 ignores one layer"), "upcast_attn": OptionInfo(False, "Upcast cross attention layer to float32"), "randn_source": OptionInfo("GPU", "Random number generator source.", gr.Radio, {"choices": ["GPU", "CPU"]}).info("changes seeds drastically; use CPU to produce the same picture across different videocard vendors"), + "sdxl_crop_top": OptionInfo(0, "SDXL top coordinate of the crop"), + "sdxl_crop_left": OptionInfo(0, "SDXL left coordinate of the crop"), })) options_templates.update(options_section(('optimizations', "Optimizations"), { -- cgit v1.2.3 From 6d8dcdefa07d5f8f7e528046b0facdcc51185e60 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Fri, 14 Jul 2023 09:16:01 +0300 Subject: initial SDXL refiner support --- modules/sd_hijack.py | 18 ++++++++++---- modules/sd_models.py | 3 ++- modules/sd_models_config.py | 3 +++ modules/sd_models_xl.py | 57 ++++++++++++++++++++++++++++++++++++--------- modules/shared.py | 9 +++++-- 5 files changed, 71 insertions(+), 19 deletions(-) (limited to 'modules/shared.py') diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py index 647cdfbe..2b274c18 100644 --- a/modules/sd_hijack.py +++ b/modules/sd_hijack.py @@ -180,21 +180,29 @@ class StableDiffusionModelHijack: def hijack(self, m): conditioner = getattr(m, 'conditioner', None) if conditioner: + text_cond_models = [] + for i in range(len(conditioner.embedders)): embedder = conditioner.embedders[i] typename = type(embedder).__name__ if typename == 'FrozenOpenCLIPEmbedder': embedder.model.token_embedding = EmbeddingsWithFixes(embedder.model.token_embedding, self) - m.cond_stage_model = sd_hijack_open_clip.FrozenOpenCLIPEmbedderWithCustomWords(embedder, self) - conditioner.embedders[i] = m.cond_stage_model + conditioner.embedders[i] = sd_hijack_open_clip.FrozenOpenCLIPEmbedderWithCustomWords(embedder, self) + text_cond_models.append(conditioner.embedders[i]) if typename == 'FrozenCLIPEmbedder': - model_embeddings = m.cond_stage_model.transformer.text_model.embeddings + model_embeddings = embedder.transformer.text_model.embeddings model_embeddings.token_embedding = EmbeddingsWithFixes(model_embeddings.token_embedding, self) - m.cond_stage_model = sd_hijack_clip.FrozenCLIPEmbedderForSDXLWithCustomWords(embedder, self) - conditioner.embedders[i] = m.cond_stage_model + conditioner.embedders[i] = sd_hijack_clip.FrozenCLIPEmbedderForSDXLWithCustomWords(embedder, self) + text_cond_models.append(conditioner.embedders[i]) if typename == 'FrozenOpenCLIPEmbedder2': embedder.model.token_embedding = EmbeddingsWithFixes(embedder.model.token_embedding, self) conditioner.embedders[i] = sd_hijack_open_clip.FrozenOpenCLIPEmbedder2WithCustomWords(embedder, self) + text_cond_models.append(conditioner.embedders[i]) + + if len(text_cond_models) == 1: + m.cond_stage_model = text_cond_models[0] + else: + m.cond_stage_model = conditioner if type(m.cond_stage_model) == xlmr.BertSeriesModelWithTransformation: model_embeddings = m.cond_stage_model.roberta.embeddings diff --git a/modules/sd_models.py b/modules/sd_models.py index 07702175..267f4d8e 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -414,6 +414,7 @@ def repair_config(sd_config): sd1_clip_weight = 'cond_stage_model.transformer.text_model.embeddings.token_embedding.weight' sd2_clip_weight = 'cond_stage_model.model.transformer.resblocks.0.attn.in_proj_weight' sdxl_clip_weight = 'conditioner.embedders.1.model.ln_final.weight' +sdxl_refiner_clip_weight = 'conditioner.embedders.0.model.ln_final.weight' class SdModelData: @@ -477,7 +478,7 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None): state_dict = get_checkpoint_state_dict(checkpoint_info, timer) checkpoint_config = sd_models_config.find_checkpoint_config(state_dict, checkpoint_info) - clip_is_included_into_sd = sd1_clip_weight in state_dict or sd2_clip_weight in state_dict or sdxl_clip_weight in state_dict + clip_is_included_into_sd = any([x for x in [sd1_clip_weight, sd2_clip_weight, sdxl_clip_weight, sdxl_refiner_clip_weight] if x in state_dict]) timer.record("find config") diff --git a/modules/sd_models_config.py b/modules/sd_models_config.py index 04c09ab0..8266fa39 100644 --- a/modules/sd_models_config.py +++ b/modules/sd_models_config.py @@ -14,6 +14,7 @@ config_sd2 = os.path.join(sd_repo_configs_path, "v2-inference.yaml") config_sd2v = os.path.join(sd_repo_configs_path, "v2-inference-v.yaml") config_sd2_inpainting = os.path.join(sd_repo_configs_path, "v2-inpainting-inference.yaml") config_sdxl = os.path.join(sd_xl_repo_configs_path, "sd_xl_base.yaml") +config_sdxl_refiner = os.path.join(sd_xl_repo_configs_path, "sd_xl_refiner.yaml") config_depth_model = os.path.join(sd_repo_configs_path, "v2-midas-inference.yaml") config_unclip = os.path.join(sd_repo_configs_path, "v2-1-stable-unclip-l-inference.yaml") config_unopenclip = os.path.join(sd_repo_configs_path, "v2-1-stable-unclip-h-inference.yaml") @@ -72,6 +73,8 @@ def guess_model_config_from_state_dict(sd, filename): if sd.get('conditioner.embedders.1.model.ln_final.weight', None) is not None: return config_sdxl + if sd.get('conditioner.embedders.0.model.ln_final.weight', None) is not None: + return config_sdxl_refiner elif sd.get('depth_model.model.pretrained.act_postprocess3.0.project.0.bias', None) is not None: return config_depth_model elif sd2_variations_weight is not None and sd2_variations_weight.shape[0] == 768: diff --git a/modules/sd_models_xl.py b/modules/sd_models_xl.py index a7240dc0..01320c7a 100644 --- a/modules/sd_models_xl.py +++ b/modules/sd_models_xl.py @@ -14,15 +14,20 @@ def get_learned_conditioning(self: sgm.models.diffusion.DiffusionEngine, batch: width = getattr(self, 'target_width', 1024) height = getattr(self, 'target_height', 1024) + is_negative_prompt = getattr(batch, 'is_negative_prompt', False) + aesthetic_score = shared.opts.sdxl_refiner_low_aesthetic_score if is_negative_prompt else shared.opts.sdxl_refiner_high_aesthetic_score + + devices_args = dict(device=devices.device, dtype=devices.dtype) sdxl_conds = { "txt": batch, - "original_size_as_tuple": torch.tensor([height, width]).repeat(len(batch), 1).to(devices.device, devices.dtype), - "crop_coords_top_left": torch.tensor([shared.opts.sdxl_crop_top, shared.opts.sdxl_crop_left]).repeat(len(batch), 1).to(devices.device, devices.dtype), - "target_size_as_tuple": torch.tensor([height, width]).repeat(len(batch), 1).to(devices.device, devices.dtype), + "original_size_as_tuple": torch.tensor([height, width], **devices_args).repeat(len(batch), 1), + "crop_coords_top_left": torch.tensor([shared.opts.sdxl_crop_top, shared.opts.sdxl_crop_left], **devices_args).repeat(len(batch), 1), + "target_size_as_tuple": torch.tensor([height, width], **devices_args).repeat(len(batch), 1), + "aesthetic_score": torch.tensor([aesthetic_score], **devices_args).repeat(len(batch), 1), } - force_zero_negative_prompt = getattr(batch, 'is_negative_prompt', False) and all(x == '' for x in batch) + force_zero_negative_prompt = is_negative_prompt and all(x == '' for x in batch) c = self.conditioner(sdxl_conds, force_zero_embeddings=['txt'] if force_zero_negative_prompt else []) return c @@ -35,25 +40,55 @@ def apply_model(self: sgm.models.diffusion.DiffusionEngine, x, t, cond): def get_first_stage_encoding(self, x): # SDXL's encode_first_stage does everything so get_first_stage_encoding is just there for compatibility return x + +sgm.models.diffusion.DiffusionEngine.get_learned_conditioning = get_learned_conditioning +sgm.models.diffusion.DiffusionEngine.apply_model = apply_model +sgm.models.diffusion.DiffusionEngine.get_first_stage_encoding = get_first_stage_encoding + + +def encode_embedding_init_text(self: sgm.modules.GeneralConditioner, init_text, nvpt): + res = [] + + for embedder in [embedder for embedder in self.embedders if hasattr(embedder, 'encode_embedding_init_text')]: + encoded = embedder.encode_embedding_init_text(init_text, nvpt) + res.append(encoded) + + return torch.cat(res, dim=1) + + +def process_texts(self, texts): + for embedder in [embedder for embedder in self.embedders if hasattr(embedder, 'process_texts')]: + return embedder.process_texts(texts) + + +def get_target_prompt_token_count(self, token_count): + for embedder in [embedder for embedder in self.embedders if hasattr(embedder, 'get_target_prompt_token_count')]: + return embedder.get_target_prompt_token_count(token_count) + + +# those additions to GeneralConditioner make it possible to use it as model.cond_stage_model from SD1.5 in exist +sgm.modules.GeneralConditioner.encode_embedding_init_text = encode_embedding_init_text +sgm.modules.GeneralConditioner.process_texts = process_texts +sgm.modules.GeneralConditioner.get_target_prompt_token_count = get_target_prompt_token_count + + def extend_sdxl(model): + """this adds a bunch of parameters to make SDXL model look a bit more like SD1.5 to the rest of the codebase.""" + dtype = next(model.model.diffusion_model.parameters()).dtype model.model.diffusion_model.dtype = dtype model.model.conditioning_key = 'crossattn' - - model.cond_stage_model = [x for x in model.conditioner.embedders if 'CLIPEmbedder' in type(x).__name__][0] - model.cond_stage_key = model.cond_stage_model.input_key + model.cond_stage_key = 'txt' + # model.cond_stage_model will be set in sd_hijack model.parameterization = "v" if isinstance(model.denoiser.scaling, sgm.modules.diffusionmodules.denoiser_scaling.VScaling) else "eps" discretization = sgm.modules.diffusionmodules.discretizer.LegacyDDPMDiscretization() model.alphas_cumprod = torch.asarray(discretization.alphas_cumprod, device=devices.device, dtype=dtype) + model.conditioner.wrapped = torch.nn.Module() -sgm.models.diffusion.DiffusionEngine.get_learned_conditioning = get_learned_conditioning -sgm.models.diffusion.DiffusionEngine.apply_model = apply_model -sgm.models.diffusion.DiffusionEngine.get_first_stage_encoding = get_first_stage_encoding - sgm.modules.attention.print = lambda *args: None sgm.modules.diffusionmodules.model.print = lambda *args: None sgm.modules.diffusionmodules.openaimodel.print = lambda *args: None diff --git a/modules/shared.py b/modules/shared.py index 71afd94f..234ede0d 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -428,8 +428,13 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "CLIP_stop_at_last_layers": OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}).link("wiki", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#clip-skip").info("ignore last layers of CLIP network; 1 ignores none, 2 ignores one layer"), "upcast_attn": OptionInfo(False, "Upcast cross attention layer to float32"), "randn_source": OptionInfo("GPU", "Random number generator source.", gr.Radio, {"choices": ["GPU", "CPU"]}).info("changes seeds drastically; use CPU to produce the same picture across different videocard vendors"), - "sdxl_crop_top": OptionInfo(0, "SDXL top coordinate of the crop"), - "sdxl_crop_left": OptionInfo(0, "SDXL left coordinate of the crop"), +})) + +options_templates.update(options_section(('sdxl', "Stable Diffusion XL"), { + "sdxl_crop_top": OptionInfo(0, "crop top coordinate"), + "sdxl_crop_left": OptionInfo(0, "crop left coordinate"), + "sdxl_refiner_low_aesthetic_score": OptionInfo(2.5, "SDXL low aesthetic score", gr.Number).info("used for refiner model negative prompt"), + "sdxl_refiner_high_aesthetic_score": OptionInfo(6.0, "SDXL high aesthetic score", gr.Number).info("used for refiner model prompt"), })) options_templates.update(options_section(('optimizations', "Optimizations"), { -- cgit v1.2.3 From abb948dab09841571dd24c6be9ff9d6b212778ea Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Fri, 14 Jul 2023 09:28:01 +0300 Subject: raise maximum Negative Guidance minimum sigma due to request in PR discussion --- modules/shared.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/shared.py') diff --git a/modules/shared.py b/modules/shared.py index 234ede0d..89b7132e 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -439,7 +439,7 @@ options_templates.update(options_section(('sdxl', "Stable Diffusion XL"), { options_templates.update(options_section(('optimizations', "Optimizations"), { "cross_attention_optimization": OptionInfo("Automatic", "Cross attention optimization", gr.Dropdown, lambda: {"choices": shared_items.cross_attention_optimizations()}), - "s_min_uncond": OptionInfo(0.0, "Negative Guidance minimum sigma", gr.Slider, {"minimum": 0.0, "maximum": 4.0, "step": 0.01}).link("PR", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/9177").info("skip negative prompt for some steps when the image is almost ready; 0=disable, higher=faster"), + "s_min_uncond": OptionInfo(0.0, "Negative Guidance minimum sigma", gr.Slider, {"minimum": 0.0, "maximum": 15.0, "step": 0.01}).link("PR", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/9177").info("skip negative prompt for some steps when the image is almost ready; 0=disable, higher=faster"), "token_merging_ratio": OptionInfo(0.0, "Token merging ratio", gr.Slider, {"minimum": 0.0, "maximum": 0.9, "step": 0.1}).link("PR", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/9256").info("0=disable, higher=faster"), "token_merging_ratio_img2img": OptionInfo(0.0, "Token merging ratio for img2img", gr.Slider, {"minimum": 0.0, "maximum": 0.9, "step": 0.1}).info("only applies if non-zero and overrides above"), "token_merging_ratio_hr": OptionInfo(0.0, "Token merging ratio for high-res pass", gr.Slider, {"minimum": 0.0, "maximum": 0.9, "step": 0.1}).info("only applies if non-zero and overrides above"), -- cgit v1.2.3 From d380f939b5ab6a28bed6d1de3cf283e194255963 Mon Sep 17 00:00:00 2001 From: Leon Feng <523684+leon0707@users.noreply.github.com> Date: Sat, 15 Jul 2023 23:31:59 -0400 Subject: Update shared.py --- modules/shared.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/shared.py') diff --git a/modules/shared.py b/modules/shared.py index a0862055..564799bc 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -394,7 +394,7 @@ options_templates.update(options_section(('training', "Training"), { })) options_templates.update(options_section(('sd', "Stable Diffusion"), { - "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": list_checkpoint_tiles()}, refresh=refresh_checkpoints), + "sd_model_checkpoint": OptionInfo("", "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"), -- cgit v1.2.3 From 66c5f1bb1556a2d86d9f11aeb92f83d4a09832cc Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Tue, 18 Jul 2023 17:41:37 +0300 Subject: return sd_model_checkpoint to None --- modules/shared.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/shared.py') diff --git a/modules/shared.py b/modules/shared.py index a256d090..6162938a 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -409,7 +409,7 @@ 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"), -- cgit v1.2.3 From 136c8859a49a35cbffe269aafc0bbdfca0b3561d Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Tue, 18 Jul 2023 20:11:30 +0300 Subject: add backwards compatibility --lyco-dir-backcompat option, use that for LyCORIS directory instead of hardcoded value prevent running preload.py for disabled extensions --- CHANGELOG.md | 4 +--- extensions-builtin/Lora/networks.py | 4 ++-- extensions-builtin/Lora/preload.py | 1 + extensions-builtin/Lora/ui_extra_networks_lora.py | 4 ++-- launch.py | 1 + modules/script_loading.py | 5 +++-- modules/shared.py | 3 ++- 7 files changed, 12 insertions(+), 10 deletions(-) (limited to 'modules/shared.py') diff --git a/CHANGELOG.md b/CHANGELOG.md index 007010da..792529ec 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -58,9 +58,7 @@ * fix: check fill size none zero when resize (fixes #11425) * use submit and blur for quick settings textbox * save img2img batch with images.save_image() - * - - + * prevent running preload.py for disabled extensions ## 1.4.1 diff --git a/extensions-builtin/Lora/networks.py b/extensions-builtin/Lora/networks.py index 7b4c0312..af8188e3 100644 --- a/extensions-builtin/Lora/networks.py +++ b/extensions-builtin/Lora/networks.py @@ -11,7 +11,7 @@ import network_full import torch from typing import Union -from modules import shared, devices, sd_models, errors, scripts, sd_hijack, paths +from modules import shared, devices, sd_models, errors, scripts, sd_hijack module_types = [ network_lora.ModuleTypeLora(), @@ -399,7 +399,7 @@ def list_available_networks(): os.makedirs(shared.cmd_opts.lora_dir, exist_ok=True) candidates = list(shared.walk_files(shared.cmd_opts.lora_dir, allowed_extensions=[".pt", ".ckpt", ".safetensors"])) - candidates += list(shared.walk_files(os.path.join(paths.models_path, "LyCORIS"), allowed_extensions=[".pt", ".ckpt", ".safetensors"])) + candidates += list(shared.walk_files(shared.cmd_opts.lyco_dir_backcompat, allowed_extensions=[".pt", ".ckpt", ".safetensors"])) for filename in candidates: if os.path.isdir(filename): continue diff --git a/extensions-builtin/Lora/preload.py b/extensions-builtin/Lora/preload.py index 863dc5c0..50961be3 100644 --- a/extensions-builtin/Lora/preload.py +++ b/extensions-builtin/Lora/preload.py @@ -4,3 +4,4 @@ from modules import paths def preload(parser): parser.add_argument("--lora-dir", type=str, help="Path to directory with Lora networks.", default=os.path.join(paths.models_path, 'Lora')) + parser.add_argument("--lyco-dir-backcompat", type=str, help="Path to directory with LyCORIS networks (for backawards compatibility; can also use --lyco-dir).", default=os.path.join(paths.models_path, 'LyCORIS')) diff --git a/extensions-builtin/Lora/ui_extra_networks_lora.py b/extensions-builtin/Lora/ui_extra_networks_lora.py index 4b32098b..3629e5c0 100644 --- a/extensions-builtin/Lora/ui_extra_networks_lora.py +++ b/extensions-builtin/Lora/ui_extra_networks_lora.py @@ -3,7 +3,7 @@ import os import network import networks -from modules import shared, ui_extra_networks, paths +from modules import shared, ui_extra_networks from modules.ui_extra_networks import quote_js from ui_edit_user_metadata import LoraUserMetadataEditor @@ -72,7 +72,7 @@ class ExtraNetworksPageLora(ui_extra_networks.ExtraNetworksPage): yield item def allowed_directories_for_previews(self): - return [shared.cmd_opts.lora_dir, os.path.join(paths.models_path, "LyCORIS")] + return [shared.cmd_opts.lora_dir, shared.cmd_opts.lyco_dir_backcompat] def create_user_metadata_editor(self, ui, tabname): return LoraUserMetadataEditor(ui, tabname, self) diff --git a/launch.py b/launch.py index b103c8f3..1dbc4c6e 100644 --- a/launch.py +++ b/launch.py @@ -18,6 +18,7 @@ run_pip = launch_utils.run_pip check_run_python = launch_utils.check_run_python git_clone = launch_utils.git_clone git_pull_recursive = launch_utils.git_pull_recursive +list_extensions = launch_utils.list_extensions run_extension_installer = launch_utils.run_extension_installer prepare_environment = launch_utils.prepare_environment configure_for_tests = launch_utils.configure_for_tests diff --git a/modules/script_loading.py b/modules/script_loading.py index 306a1f35..0d55f193 100644 --- a/modules/script_loading.py +++ b/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 diff --git a/modules/shared.py b/modules/shared.py index 6162938a..1ce7b49e 100644 --- a/modules/shared.py +++ b/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: -- cgit v1.2.3 From 23c947ab0374220c39ac54fc00afcb74e809dd95 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Wed, 19 Jul 2023 20:23:30 +0300 Subject: automatically switch to 32-bit float VAE if the generated picture has NaNs. --- CHANGELOG.md | 3 ++- modules/processing.py | 41 ++++++++++++++++++++++++++++++++++++----- modules/shared.py | 1 + 3 files changed, 39 insertions(+), 6 deletions(-) (limited to 'modules/shared.py') diff --git a/CHANGELOG.md b/CHANGELOG.md index a561252c..63a2c7d3 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -29,7 +29,8 @@ * speedup extra networks listing * added `[none]` filename token. * removed thumbs extra networks view mode (use settings tab to change width/height/scale to get thumbs) - * add always_discard_next_to_last_sigma option to XYZ plot + * add always_discard_next_to_last_sigma option to XYZ plot + * automatically switch to 32-bit float VAE if the generated picture has NaNs without the need for `--no-half-vae` commandline flag. ### Extensions and API: * api endpoints: /sdapi/v1/server-kill, /sdapi/v1/server-restart, /sdapi/v1/server-stop diff --git a/modules/processing.py b/modules/processing.py index e028bf9e..a74a5302 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -14,7 +14,7 @@ from skimage import exposure from typing import Any, Dict, List import modules.sd_hijack -from modules import devices, prompt_parser, masking, sd_samplers, lowvram, generation_parameters_copypaste, extra_networks, sd_vae_approx, scripts, sd_samplers_common, sd_unet +from modules import devices, prompt_parser, masking, sd_samplers, lowvram, generation_parameters_copypaste, extra_networks, sd_vae_approx, scripts, sd_samplers_common, sd_unet, errors from modules.sd_hijack import model_hijack from modules.shared import opts, cmd_opts, state import modules.shared as shared @@ -538,6 +538,40 @@ def create_random_tensors(shape, seeds, subseeds=None, subseed_strength=0.0, see return x +def decode_latent_batch(model, batch, target_device=None, check_for_nans=False): + samples = [] + + for i in range(batch.shape[0]): + sample = decode_first_stage(model, batch[i:i + 1])[0] + + if check_for_nans: + try: + devices.test_for_nans(sample, "vae") + except devices.NansException as e: + if devices.dtype_vae == torch.float32 or not shared.opts.auto_vae_precision: + raise e + + errors.print_error_explanation( + "A tensor with all NaNs was produced in VAE.\n" + "Web UI will now convert VAE into 32-bit float and retry.\n" + "To disable this behavior, disable the 'Automaticlly revert VAE to 32-bit floats' setting.\n" + "To always start with 32-bit VAE, use --no-half-vae commandline flag." + ) + + devices.dtype_vae = torch.float32 + model.first_stage_model.to(devices.dtype_vae) + batch = batch.to(devices.dtype_vae) + + sample = decode_first_stage(model, batch[i:i + 1])[0] + + if target_device is not None: + sample = sample.to(target_device) + + samples.append(sample) + + return samples + + def decode_first_stage(model, x): x = model.decode_first_stage(x.to(devices.dtype_vae)) @@ -758,10 +792,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: with devices.without_autocast() if devices.unet_needs_upcast else devices.autocast(): samples_ddim = p.sample(conditioning=p.c, unconditional_conditioning=p.uc, seeds=p.seeds, subseeds=p.subseeds, subseed_strength=p.subseed_strength, prompts=p.prompts) - x_samples_ddim = [decode_first_stage(p.sd_model, samples_ddim[i:i+1].to(dtype=devices.dtype_vae))[0].cpu() for i in range(samples_ddim.size(0))] - for x in x_samples_ddim: - devices.test_for_nans(x, "vae") - + x_samples_ddim = decode_latent_batch(p.sd_model, samples_ddim, target_device=devices.cpu, check_for_nans=True) x_samples_ddim = torch.stack(x_samples_ddim).float() x_samples_ddim = torch.clamp((x_samples_ddim + 1.0) / 2.0, min=0.0, max=1.0) diff --git a/modules/shared.py b/modules/shared.py index 1ce7b49e..aa72c9c8 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -427,6 +427,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "comma_padding_backtrack": OptionInfo(20, "Prompt word wrap length limit", gr.Slider, {"minimum": 0, "maximum": 74, "step": 1}).info("in tokens - for texts shorter than specified, if they don't fit into 75 token limit, move them to the next 75 token chunk"), "CLIP_stop_at_last_layers": OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}).link("wiki", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#clip-skip").info("ignore last layers of CLIP network; 1 ignores none, 2 ignores one layer"), "upcast_attn": OptionInfo(False, "Upcast cross attention layer to float32"), + "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"), "randn_source": OptionInfo("GPU", "Random number generator source.", gr.Radio, {"choices": ["GPU", "CPU"]}).info("changes seeds drastically; use CPU to produce the same picture across different videocard vendors"), })) -- cgit v1.2.3 From 3bca90b249d749ed5429f76e380d2ffa52fc0d41 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Sun, 30 Jul 2023 13:48:27 +0300 Subject: hires fix checkpoint selection --- modules/generation_parameters_copypaste.py | 3 ++ modules/processing.py | 47 +++++++++++++++++++----------- modules/sd_models.py | 22 ++++++++------ modules/shared.py | 19 ++++++++---- modules/txt2img.py | 3 +- modules/ui.py | 8 ++++- 6 files changed, 68 insertions(+), 34 deletions(-) (limited to 'modules/shared.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index a3448be9..4e286558 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -280,6 +280,9 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model if "Hires sampler" not in res: res["Hires sampler"] = "Use same sampler" + if "Hires checkpoint" not in res: + res["Hires checkpoint"] = "Use same checkpoint" + if "Hires prompt" not in res: res["Hires prompt"] = "" diff --git a/modules/processing.py b/modules/processing.py index b0992ee1..7026487a 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -935,7 +935,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): cached_hr_uc = [None, None] cached_hr_c = [None, None] - def __init__(self, enable_hr: bool = False, denoising_strength: float = 0.75, firstphase_width: int = 0, firstphase_height: int = 0, hr_scale: float = 2.0, hr_upscaler: str = None, hr_second_pass_steps: int = 0, hr_resize_x: int = 0, hr_resize_y: int = 0, hr_sampler_name: str = None, hr_prompt: str = '', hr_negative_prompt: str = '', **kwargs): + def __init__(self, enable_hr: bool = False, denoising_strength: float = 0.75, firstphase_width: int = 0, firstphase_height: int = 0, hr_scale: float = 2.0, hr_upscaler: str = None, hr_second_pass_steps: int = 0, hr_resize_x: int = 0, hr_resize_y: int = 0, hr_checkpoint_name: str = None, hr_sampler_name: str = None, hr_prompt: str = '', hr_negative_prompt: str = '', **kwargs): super().__init__(**kwargs) self.enable_hr = enable_hr self.denoising_strength = denoising_strength @@ -946,11 +946,14 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): self.hr_resize_y = hr_resize_y self.hr_upscale_to_x = hr_resize_x self.hr_upscale_to_y = hr_resize_y + self.hr_checkpoint_name = hr_checkpoint_name + self.hr_checkpoint_info = None self.hr_sampler_name = hr_sampler_name self.hr_prompt = hr_prompt self.hr_negative_prompt = hr_negative_prompt self.all_hr_prompts = None self.all_hr_negative_prompts = None + self.latent_scale_mode = None if firstphase_width != 0 or firstphase_height != 0: self.hr_upscale_to_x = self.width @@ -973,6 +976,14 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): def init(self, all_prompts, all_seeds, all_subseeds): if self.enable_hr: + if self.hr_checkpoint_name: + self.hr_checkpoint_info = sd_models.get_closet_checkpoint_match(self.hr_checkpoint_name) + + if self.hr_checkpoint_info is None: + raise Exception(f'Could not find checkpoint with name {self.hr_checkpoint_name}') + + self.extra_generation_params["Hires checkpoint"] = self.hr_checkpoint_info.short_title + if self.hr_sampler_name is not None and self.hr_sampler_name != self.sampler_name: self.extra_generation_params["Hires sampler"] = self.hr_sampler_name @@ -982,6 +993,11 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): if tuple(self.hr_negative_prompt) != tuple(self.negative_prompt): self.extra_generation_params["Hires negative prompt"] = self.hr_negative_prompt + self.latent_scale_mode = shared.latent_upscale_modes.get(self.hr_upscaler, None) if self.hr_upscaler is not None else shared.latent_upscale_modes.get(shared.latent_upscale_default_mode, "nearest") + if self.enable_hr and self.latent_scale_mode is None: + if not any(x.name == self.hr_upscaler for x in shared.sd_upscalers): + raise Exception(f"could not find upscaler named {self.hr_upscaler}") + if opts.use_old_hires_fix_width_height and self.applied_old_hires_behavior_to != (self.width, self.height): self.hr_resize_x = self.width self.hr_resize_y = self.height @@ -1020,14 +1036,6 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): self.truncate_x = (self.hr_upscale_to_x - target_w) // opt_f self.truncate_y = (self.hr_upscale_to_y - target_h) // opt_f - # special case: the user has chosen to do nothing - if self.hr_upscale_to_x == self.width and self.hr_upscale_to_y == self.height: - self.enable_hr = False - self.denoising_strength = None - self.extra_generation_params.pop("Hires upscale", None) - self.extra_generation_params.pop("Hires resize", None) - return - if not state.processing_has_refined_job_count: if state.job_count == -1: state.job_count = self.n_iter @@ -1045,17 +1053,22 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): def sample(self, conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength, prompts): self.sampler = sd_samplers.create_sampler(self.sampler_name, self.sd_model) - latent_scale_mode = shared.latent_upscale_modes.get(self.hr_upscaler, None) if self.hr_upscaler is not None else shared.latent_upscale_modes.get(shared.latent_upscale_default_mode, "nearest") - if self.enable_hr and latent_scale_mode is None: - if not any(x.name == self.hr_upscaler for x in shared.sd_upscalers): - raise Exception(f"could not find upscaler named {self.hr_upscaler}") - x = create_random_tensors([opt_C, self.height // opt_f, self.width // opt_f], seeds=seeds, subseeds=subseeds, subseed_strength=self.subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self) samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x)) if not self.enable_hr: return samples + current = shared.sd_model.sd_checkpoint_info + try: + if self.hr_checkpoint_info is not None: + sd_models.reload_model_weights(info=self.hr_checkpoint_info) + + return self.sample_hr_pass(samples, seeds, subseeds, subseed_strength, prompts) + finally: + sd_models.reload_model_weights(info=current) + + def sample_hr_pass(self, samples, seeds, subseeds, subseed_strength, prompts): self.is_hr_pass = True target_width = self.hr_upscale_to_x @@ -1073,11 +1086,11 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): info = create_infotext(self, self.all_prompts, self.all_seeds, self.all_subseeds, [], iteration=self.iteration, position_in_batch=index) images.save_image(image, self.outpath_samples, "", seeds[index], prompts[index], opts.samples_format, info=info, p=self, suffix="-before-highres-fix") - if latent_scale_mode is not None: + if self.latent_scale_mode is not None: for i in range(samples.shape[0]): save_intermediate(samples, i) - samples = torch.nn.functional.interpolate(samples, size=(target_height // opt_f, target_width // opt_f), mode=latent_scale_mode["mode"], antialias=latent_scale_mode["antialias"]) + samples = torch.nn.functional.interpolate(samples, size=(target_height // opt_f, target_width // opt_f), mode=self.latent_scale_mode["mode"], antialias=self.latent_scale_mode["antialias"]) # Avoid making the inpainting conditioning unless necessary as # this does need some extra compute to decode / encode the image again. @@ -1193,7 +1206,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): self.hr_uc = None self.hr_c = None - if self.enable_hr: + if self.enable_hr and self.hr_checkpoint_info is None: if shared.opts.hires_fix_use_firstpass_conds: self.calculate_hr_conds() diff --git a/modules/sd_models.py b/modules/sd_models.py index acb1e817..cb67e425 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -52,6 +52,7 @@ class CheckpointInfo: self.shorthash = self.sha256[0:10] if self.sha256 else None self.title = name if self.shorthash is None else f'{name} [{self.shorthash}]' + self.short_title = self.name_for_extra if self.shorthash is None else f'{self.name_for_extra} [{self.shorthash}]' self.ids = [self.hash, self.model_name, self.title, name, f'{name} [{self.hash}]'] + ([self.shorthash, self.sha256, f'{self.name} [{self.shorthash}]'] if self.shorthash else []) @@ -81,6 +82,7 @@ class CheckpointInfo: checkpoints_list.pop(self.title) self.title = f'{self.name} [{self.shorthash}]' + self.short_title = f'{self.name_for_extra} [{self.shorthash}]' self.register() return self.shorthash @@ -101,14 +103,8 @@ def setup_model(): enable_midas_autodownload() -def checkpoint_tiles(): - def convert(name): - return int(name) if name.isdigit() else name.lower() - - def alphanumeric_key(key): - return [convert(c) for c in re.split('([0-9]+)', key)] - - return sorted([x.title for x in checkpoints_list.values()], key=alphanumeric_key) +def checkpoint_tiles(use_short=False): + return [x.short_title if use_short else x.title for x in checkpoints_list.values()] def list_models(): @@ -131,11 +127,14 @@ def list_models(): elif cmd_ckpt is not None and cmd_ckpt != shared.default_sd_model_file: print(f"Checkpoint in --ckpt argument not found (Possible it was moved to {model_path}: {cmd_ckpt}", file=sys.stderr) - for filename in sorted(model_list, key=str.lower): + for filename in model_list: checkpoint_info = CheckpointInfo(filename) checkpoint_info.register() +re_strip_checksum = re.compile(r"\s*\[[^]]+]\s*$") + + def get_closet_checkpoint_match(search_string): checkpoint_info = checkpoint_aliases.get(search_string, None) if checkpoint_info is not None: @@ -145,6 +144,11 @@ def get_closet_checkpoint_match(search_string): if found: return found[0] + search_string_without_checksum = re.sub(re_strip_checksum, '', search_string) + found = sorted([info for info in checkpoints_list.values() if search_string_without_checksum in info.title], key=lambda x: len(x.title)) + if found: + return found[0] + return None diff --git a/modules/shared.py b/modules/shared.py index aa72c9c8..807fb9e3 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -220,12 +220,19 @@ class State: return import modules.sd_samplers - if opts.show_progress_grid: - self.assign_current_image(modules.sd_samplers.samples_to_image_grid(self.current_latent)) - else: - self.assign_current_image(modules.sd_samplers.sample_to_image(self.current_latent)) - self.current_image_sampling_step = self.sampling_step + try: + if opts.show_progress_grid: + self.assign_current_image(modules.sd_samplers.samples_to_image_grid(self.current_latent)) + else: + self.assign_current_image(modules.sd_samplers.sample_to_image(self.current_latent)) + + self.current_image_sampling_step = self.sampling_step + + except Exception: + # when switching models during genration, VAE would be on CPU, so creating an image will fail. + # we silently ignore this error + errors.record_exception() def assign_current_image(self, image): self.current_image = image @@ -512,7 +519,7 @@ options_templates.update(options_section(('ui', "User interface"), { "ui_tab_order": OptionInfo([], "UI tab order", ui_components.DropdownMulti, lambda: {"choices": list(tab_names)}).needs_restart(), "hidden_tabs": OptionInfo([], "Hidden UI tabs", ui_components.DropdownMulti, lambda: {"choices": list(tab_names)}).needs_restart(), "ui_reorder_list": OptionInfo([], "txt2img/img2img UI item order", ui_components.DropdownMulti, lambda: {"choices": list(shared_items.ui_reorder_categories())}).info("selected items appear first").needs_restart(), - "hires_fix_show_sampler": OptionInfo(False, "Hires fix: show hires sampler selection").needs_restart(), + "hires_fix_show_sampler": OptionInfo(False, "Hires fix: show hires checkpoint and sampler selection").needs_restart(), "hires_fix_show_prompts": OptionInfo(False, "Hires fix: show hires prompt and negative prompt").needs_restart(), "disable_token_counters": OptionInfo(False, "Disable prompt token counters").needs_restart(), })) diff --git a/modules/txt2img.py b/modules/txt2img.py index 29d94e8c..935ed418 100644 --- a/modules/txt2img.py +++ b/modules/txt2img.py @@ -9,7 +9,7 @@ from modules.ui import plaintext_to_html import gradio as gr -def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, hr_sampler_index: int, hr_prompt: str, hr_negative_prompt, override_settings_texts, request: gr.Request, *args): +def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, hr_checkpoint_name: str, hr_sampler_index: int, hr_prompt: str, hr_negative_prompt, override_settings_texts, request: gr.Request, *args): override_settings = create_override_settings_dict(override_settings_texts) p = processing.StableDiffusionProcessingTxt2Img( @@ -41,6 +41,7 @@ def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, step hr_second_pass_steps=hr_second_pass_steps, hr_resize_x=hr_resize_x, hr_resize_y=hr_resize_y, + hr_checkpoint_name=None if hr_checkpoint_name == 'Use same checkpoint' else hr_checkpoint_name, hr_sampler_name=sd_samplers.samplers_for_img2img[hr_sampler_index - 1].name if hr_sampler_index != 0 else None, hr_prompt=hr_prompt, hr_negative_prompt=hr_negative_prompt, diff --git a/modules/ui.py b/modules/ui.py index 07ecee7b..6d8265f2 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -476,6 +476,10 @@ def create_ui(): hr_resize_y = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize height to", value=0, elem_id="txt2img_hr_resize_y") with FormRow(elem_id="txt2img_hires_fix_row3", variant="compact", visible=opts.hires_fix_show_sampler) as hr_sampler_container: + checkpoint_choices = lambda: ["Use same checkpoint"] + modules.sd_models.checkpoint_tiles(use_short=True) + hr_checkpoint_name = gr.Dropdown(label='Hires checkpoint', elem_id="hr_checkpoint", choices=checkpoint_choices(), value="Use same checkpoint") + create_refresh_button(hr_checkpoint_name, modules.sd_models.list_models, lambda: {"choices": checkpoint_choices()}, "hr_checkpoint_refresh") + hr_sampler_index = gr.Dropdown(label='Hires sampling method', elem_id="hr_sampler", choices=["Use same sampler"] + [x.name for x in samplers_for_img2img], value="Use same sampler", type="index") with FormRow(elem_id="txt2img_hires_fix_row4", variant="compact", visible=opts.hires_fix_show_prompts) as hr_prompts_container: @@ -553,6 +557,7 @@ def create_ui(): hr_second_pass_steps, hr_resize_x, hr_resize_y, + hr_checkpoint_name, hr_sampler_index, hr_prompt, hr_negative_prompt, @@ -630,8 +635,9 @@ def create_ui(): (hr_second_pass_steps, "Hires steps"), (hr_resize_x, "Hires resize-1"), (hr_resize_y, "Hires resize-2"), + (hr_checkpoint_name, "Hires checkpoint"), (hr_sampler_index, "Hires sampler"), - (hr_sampler_container, lambda d: gr.update(visible=True) if d.get("Hires sampler", "Use same sampler") != "Use same sampler" else gr.update()), + (hr_sampler_container, lambda d: gr.update(visible=True) if d.get("Hires sampler", "Use same sampler") != "Use same sampler" or d.get("Hires checkpoint", "Use same checkpoint") != "Use same checkpoint" else gr.update()), (hr_prompt, "Hires prompt"), (hr_negative_prompt, "Hires negative prompt"), (hr_prompts_container, lambda d: gr.update(visible=True) if d.get("Hires prompt", "") != "" or d.get("Hires negative prompt", "") != "" else gr.update()), -- cgit v1.2.3 From b235022c615a7384f73c05fe240d8f4a28d103d4 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Tue, 1 Aug 2023 00:24:48 +0300 Subject: option to keep multiple models in memory --- modules/lowvram.py | 3 + modules/sd_hijack.py | 6 +- modules/sd_hijack_inpainting.py | 5 +- modules/sd_models.py | 136 +++++++++++++++++++++++++++++++++------- modules/sd_models_xl.py | 8 +-- modules/shared.py | 12 +++- 6 files changed, 135 insertions(+), 35 deletions(-) (limited to 'modules/shared.py') diff --git a/modules/lowvram.py b/modules/lowvram.py index 3f830664..96f52b7b 100644 --- a/modules/lowvram.py +++ b/modules/lowvram.py @@ -15,6 +15,9 @@ def send_everything_to_cpu(): def setup_for_low_vram(sd_model, use_medvram): + if getattr(sd_model, 'lowvram', False): + return + sd_model.lowvram = True parents = {} diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py index cfa5f0eb..7d692e3c 100644 --- a/modules/sd_hijack.py +++ b/modules/sd_hijack.py @@ -30,8 +30,10 @@ ldm.modules.attention.MemoryEfficientCrossAttention = ldm.modules.attention.Cros ldm.modules.attention.BasicTransformerBlock.ATTENTION_MODES["softmax-xformers"] = ldm.modules.attention.CrossAttention # silence new console spam from SD2 -ldm.modules.attention.print = lambda *args: None -ldm.modules.diffusionmodules.model.print = lambda *args: None +ldm.modules.attention.print = shared.ldm_print +ldm.modules.diffusionmodules.model.print = shared.ldm_print +ldm.util.print = shared.ldm_print +ldm.models.diffusion.ddpm.print = shared.ldm_print optimizers = [] current_optimizer: sd_hijack_optimizations.SdOptimization = None diff --git a/modules/sd_hijack_inpainting.py b/modules/sd_hijack_inpainting.py index c1977b19..97350f4f 100644 --- a/modules/sd_hijack_inpainting.py +++ b/modules/sd_hijack_inpainting.py @@ -91,7 +91,4 @@ def p_sample_plms(self, x, c, t, index, repeat_noise=False, use_original_steps=F return x_prev, pred_x0, e_t -def do_inpainting_hijack(): - # p_sample_plms is needed because PLMS can't work with dicts as conditionings - - ldm.models.diffusion.plms.PLMSSampler.p_sample_plms = p_sample_plms +ldm.models.diffusion.plms.PLMSSampler.p_sample_plms = p_sample_plms diff --git a/modules/sd_models.py b/modules/sd_models.py index acb1e817..77195f2f 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -15,7 +15,6 @@ import ldm.modules.midas as midas from ldm.util import instantiate_from_config from modules import paths, shared, modelloader, devices, script_callbacks, sd_vae, sd_disable_initialization, errors, hashes, sd_models_config, sd_unet, sd_models_xl -from modules.sd_hijack_inpainting import do_inpainting_hijack from modules.timer import Timer import tomesd @@ -423,6 +422,7 @@ sdxl_refiner_clip_weight = 'conditioner.embedders.0.model.ln_final.weight' class SdModelData: def __init__(self): self.sd_model = None + self.loaded_sd_models = [] self.was_loaded_at_least_once = False self.lock = threading.Lock() @@ -437,6 +437,7 @@ class SdModelData: try: load_model() + except Exception as e: errors.display(e, "loading stable diffusion model", full_traceback=True) print("", file=sys.stderr) @@ -448,11 +449,24 @@ class SdModelData: def set_sd_model(self, v): self.sd_model = v + try: + self.loaded_sd_models.remove(v) + except ValueError: + pass + + if v is not None: + self.loaded_sd_models.insert(0, v) + model_data = SdModelData() def get_empty_cond(sd_model): + from modules import extra_networks, processing + + p = processing.StableDiffusionProcessingTxt2Img() + extra_networks.activate(p, {}) + if hasattr(sd_model, 'conditioner'): d = sd_model.get_learned_conditioning([""]) return d['crossattn'] @@ -460,19 +474,43 @@ def get_empty_cond(sd_model): return sd_model.cond_stage_model([""]) +def send_model_to_cpu(m): + from modules import lowvram + + if shared.cmd_opts.lowvram or shared.cmd_opts.medvram: + lowvram.send_everything_to_cpu() + else: + m.to(devices.cpu) + + devices.torch_gc() + + +def send_model_to_device(m): + from modules import lowvram + + if shared.cmd_opts.lowvram or shared.cmd_opts.medvram: + lowvram.setup_for_low_vram(m, shared.cmd_opts.medvram) + else: + m.to(shared.device) + + +def send_model_to_trash(m): + m.to(device="meta") + devices.torch_gc() + + def load_model(checkpoint_info=None, already_loaded_state_dict=None): - from modules import lowvram, sd_hijack + from modules import sd_hijack checkpoint_info = checkpoint_info or select_checkpoint() + timer = Timer() + if model_data.sd_model: - sd_hijack.model_hijack.undo_hijack(model_data.sd_model) + send_model_to_trash(model_data.sd_model) model_data.sd_model = None - gc.collect() devices.torch_gc() - do_inpainting_hijack() - - timer = Timer() + timer.record("unload existing model") if already_loaded_state_dict is not None: state_dict = already_loaded_state_dict @@ -512,12 +550,9 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None): with sd_disable_initialization.LoadStateDictOnMeta(state_dict, devices.cpu): load_model_weights(sd_model, checkpoint_info, state_dict, timer) + timer.record("load weights from state dict") - if shared.cmd_opts.lowvram or shared.cmd_opts.medvram: - lowvram.setup_for_low_vram(sd_model, shared.cmd_opts.medvram) - else: - sd_model.to(shared.device) - + send_model_to_device(sd_model) timer.record("move model to device") sd_hijack.model_hijack.hijack(sd_model) @@ -525,7 +560,7 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None): timer.record("hijack") sd_model.eval() - model_data.sd_model = sd_model + model_data.set_sd_model(sd_model) model_data.was_loaded_at_least_once = True sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings(force_reload=True) # Reload embeddings after model load as they may or may not fit the model @@ -546,10 +581,61 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None): return sd_model +def reuse_model_from_already_loaded(sd_model, checkpoint_info, timer): + """ + Checks if the desired checkpoint from checkpoint_info is not already loaded in model_data.loaded_sd_models. + If it is loaded, returns that (moving it to GPU if necessary, and moving the currently loadded model to CPU if necessary). + If not, returns the model that can be used to load weights from checkpoint_info's file. + If no such model exists, returns None. + Additionaly deletes loaded models that are over the limit set in settings (sd_checkpoints_limit). + """ + + already_loaded = None + for i in reversed(range(len(model_data.loaded_sd_models))): + loaded_model = model_data.loaded_sd_models[i] + if loaded_model.sd_checkpoint_info.filename == checkpoint_info.filename: + already_loaded = loaded_model + continue + + if len(model_data.loaded_sd_models) > shared.opts.sd_checkpoints_limit > 0: + print(f"Unloading model {len(model_data.loaded_sd_models)} over the limit of {shared.opts.sd_checkpoints_limit}: {loaded_model.sd_checkpoint_info.title}") + model_data.loaded_sd_models.pop() + send_model_to_trash(loaded_model) + timer.record("send model to trash") + + if shared.opts.sd_checkpoints_keep_in_cpu: + send_model_to_cpu(sd_model) + timer.record("send model to cpu") + + if already_loaded is not None: + send_model_to_device(already_loaded) + timer.record("send model to device") + + model_data.set_sd_model(already_loaded) + print(f"Using already loaded model {already_loaded.sd_checkpoint_info.title}: done in {timer.summary()}") + return model_data.sd_model + elif shared.opts.sd_checkpoints_limit > 1 and len(model_data.loaded_sd_models) < shared.opts.sd_checkpoints_limit: + print(f"Loading model {checkpoint_info.title} ({len(model_data.loaded_sd_models) + 1} out of {shared.opts.sd_checkpoints_limit})") + + model_data.sd_model = None + load_model(checkpoint_info) + return model_data.sd_model + elif len(model_data.loaded_sd_models) > 0: + sd_model = model_data.loaded_sd_models.pop() + model_data.sd_model = sd_model + + print(f"Reusing loaded model {sd_model.sd_checkpoint_info.title} to load {checkpoint_info.title}") + return sd_model + else: + return None + + def reload_model_weights(sd_model=None, info=None): - from modules import lowvram, devices, sd_hijack + from modules import devices, sd_hijack checkpoint_info = info or select_checkpoint() + timer = Timer() + if not sd_model: sd_model = model_data.sd_model @@ -558,19 +644,17 @@ def reload_model_weights(sd_model=None, info=None): else: current_checkpoint_info = sd_model.sd_checkpoint_info if sd_model.sd_model_checkpoint == checkpoint_info.filename: - return - - sd_unet.apply_unet("None") + return sd_model - if shared.cmd_opts.lowvram or shared.cmd_opts.medvram: - lowvram.send_everything_to_cpu() - else: - sd_model.to(devices.cpu) + sd_model = reuse_model_from_already_loaded(sd_model, checkpoint_info, timer) + if sd_model is not None and sd_model.sd_checkpoint_info.filename == checkpoint_info.filename: + return sd_model + if sd_model is not None: + sd_unet.apply_unet("None") + send_model_to_cpu(sd_model) sd_hijack.model_hijack.undo_hijack(sd_model) - timer = Timer() - state_dict = get_checkpoint_state_dict(checkpoint_info, timer) checkpoint_config = sd_models_config.find_checkpoint_config(state_dict, checkpoint_info) @@ -578,7 +662,9 @@ def reload_model_weights(sd_model=None, info=None): timer.record("find config") if sd_model is None or checkpoint_config != sd_model.used_config: - del sd_model + if sd_model is not None: + send_model_to_trash(sd_model) + load_model(checkpoint_info, already_loaded_state_dict=state_dict) return model_data.sd_model @@ -601,6 +687,8 @@ def reload_model_weights(sd_model=None, info=None): print(f"Weights loaded in {timer.summary()}.") + model_data.set_sd_model(sd_model) + return sd_model diff --git a/modules/sd_models_xl.py b/modules/sd_models_xl.py index bc219508..01123321 100644 --- a/modules/sd_models_xl.py +++ b/modules/sd_models_xl.py @@ -98,10 +98,10 @@ def extend_sdxl(model): model.conditioner.wrapped = torch.nn.Module() -sgm.modules.attention.print = lambda *args: None -sgm.modules.diffusionmodules.model.print = lambda *args: None -sgm.modules.diffusionmodules.openaimodel.print = lambda *args: None -sgm.modules.encoders.modules.print = lambda *args: None +sgm.modules.attention.print = shared.ldm_print +sgm.modules.diffusionmodules.model.print = shared.ldm_print +sgm.modules.diffusionmodules.openaimodel.print = shared.ldm_print +sgm.modules.encoders.modules.print = shared.ldm_print # this gets the code to load the vanilla attention that we override sgm.modules.attention.SDP_IS_AVAILABLE = True diff --git a/modules/shared.py b/modules/shared.py index aa72c9c8..0184fcd0 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -392,6 +392,7 @@ options_templates.update(options_section(('system', "System"), { "print_hypernet_extra": OptionInfo(False, "Print extra hypernetwork information to console."), "list_hidden_files": OptionInfo(True, "Load models/files in hidden directories").info("directory is hidden if its name starts with \".\""), "disable_mmap_load_safetensors": OptionInfo(False, "Disable memmapping for loading .safetensors files.").info("fixes very slow loading speed in some cases"), + "hide_ldm_prints": OptionInfo(True, "Prevent Stability-AI's ldm/sgm modules from printing noise to console."), })) options_templates.update(options_section(('training', "Training"), { @@ -411,7 +412,9 @@ options_templates.update(options_section(('training', "Training"), { options_templates.update(options_section(('sd', "Stable Diffusion"), { "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_checkpoints_limit": OptionInfo(1, "Maximum number of checkpoints loaded at the same time", gr.Slider, {"minimum": 1, "maximum": 10, "step": 1}), + "sd_checkpoints_keep_in_cpu": OptionInfo(True, "Only keep one model on device").info("will keep models other than the currently used one in RAM rather than VRAM"), + "sd_checkpoint_cache": OptionInfo(0, "Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}).info("obsolete; set to 0 and use the two settings above instead"), "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"), @@ -889,3 +892,10 @@ def walk_files(path, allowed_extensions=None): continue yield os.path.join(root, filename) + + +def ldm_print(*args, **kwargs): + if opts.hide_ldm_prints: + return + + print(*args, **kwargs) -- cgit v1.2.3 From 84b6fcd02ca6d6ab48c4b6be4bb8724b1c2e7014 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Thu, 3 Aug 2023 00:00:23 +0300 Subject: add NV option for Random number generator source setting, which allows to generate same pictures on CPU/AMD/Mac as on NVidia videocards. --- modules/devices.py | 39 ++++++++++++++- modules/processing.py | 6 +-- modules/rng_philox.py | 100 ++++++++++++++++++++++++++++++++++++++ modules/sd_samplers_kdiffusion.py | 5 +- modules/shared.py | 2 +- 5 files changed, 142 insertions(+), 10 deletions(-) create mode 100644 modules/rng_philox.py (limited to 'modules/shared.py') diff --git a/modules/devices.py b/modules/devices.py index 57e51da3..b58776d8 100644 --- a/modules/devices.py +++ b/modules/devices.py @@ -3,7 +3,7 @@ import contextlib from functools import lru_cache import torch -from modules import errors +from modules import errors, rng_philox if sys.platform == "darwin": from modules import mac_specific @@ -90,23 +90,58 @@ def cond_cast_float(input): return input.float() if unet_needs_upcast else input +nv_rng = None + + def randn(seed, shape): from modules.shared import opts - torch.manual_seed(seed) + manual_seed(seed) + + if opts.randn_source == "NV": + return torch.asarray(nv_rng.randn(shape), device=device) + if opts.randn_source == "CPU" or device.type == 'mps': return torch.randn(shape, device=cpu).to(device) + return torch.randn(shape, device=device) +def randn_like(x): + from modules.shared import opts + + if opts.randn_source == "NV": + return torch.asarray(nv_rng.randn(x.shape), device=x.device, dtype=x.dtype) + + if opts.randn_source == "CPU" or x.device.type == 'mps': + return torch.randn_like(x, device=cpu).to(x.device) + + return torch.randn_like(x) + + def randn_without_seed(shape): from modules.shared import opts + if opts.randn_source == "NV": + return torch.asarray(nv_rng.randn(shape), device=device) + if opts.randn_source == "CPU" or device.type == 'mps': return torch.randn(shape, device=cpu).to(device) + return torch.randn(shape, device=device) +def manual_seed(seed): + from modules.shared import opts + + if opts.randn_source == "NV": + global nv_rng + nv_rng = rng_philox.Generator(seed) + return + + torch.manual_seed(seed) + + def autocast(disable=False): from modules import shared diff --git a/modules/processing.py b/modules/processing.py index 0b66cd2a..8f34c8b4 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -492,7 +492,7 @@ def create_random_tensors(shape, seeds, subseeds=None, subseed_strength=0.0, see noise_shape = shape if seed_resize_from_h <= 0 or seed_resize_from_w <= 0 else (shape[0], seed_resize_from_h//8, seed_resize_from_w//8) subnoise = None - if subseeds is not None: + if subseeds is not None and subseed_strength != 0: subseed = 0 if i >= len(subseeds) else subseeds[i] subnoise = devices.randn(subseed, noise_shape) @@ -524,7 +524,7 @@ def create_random_tensors(shape, seeds, subseeds=None, subseed_strength=0.0, see cnt = p.sampler.number_of_needed_noises(p) if eta_noise_seed_delta > 0: - torch.manual_seed(seed + eta_noise_seed_delta) + devices.manual_seed(seed + eta_noise_seed_delta) for j in range(cnt): sampler_noises[j].append(devices.randn_without_seed(tuple(noise_shape))) @@ -636,7 +636,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter "Token merging ratio": None if token_merging_ratio == 0 else token_merging_ratio, "Token merging ratio hr": None if not enable_hr or token_merging_ratio_hr == 0 else token_merging_ratio_hr, "Init image hash": getattr(p, 'init_img_hash', None), - "RNG": opts.randn_source if opts.randn_source != "GPU" else None, + "RNG": opts.randn_source if opts.randn_source != "GPU" and opts.randn_source != "NV" else None, "NGMS": None if p.s_min_uncond == 0 else p.s_min_uncond, **p.extra_generation_params, "Version": program_version() if opts.add_version_to_infotext else None, diff --git a/modules/rng_philox.py b/modules/rng_philox.py new file mode 100644 index 00000000..b5c02483 --- /dev/null +++ b/modules/rng_philox.py @@ -0,0 +1,100 @@ +"""RNG imitiating torch cuda randn on CPU. You are welcome. + +Usage: + +``` +g = Generator(seed=0) +print(g.randn(shape=(3, 4))) +``` + +Expected output: +``` +[[-0.92466259 -0.42534415 -2.6438457 0.14518388] + [-0.12086647 -0.57972564 -0.62285122 -0.32838709] + [-1.07454231 -0.36314407 -1.67105067 2.26550497]] +``` +""" + +import numpy as np + +philox_m = [0xD2511F53, 0xCD9E8D57] +philox_w = [0x9E3779B9, 0xBB67AE85] + +two_pow32_inv = np.array([2.3283064e-10], dtype=np.float32) +two_pow32_inv_2pi = np.array([2.3283064e-10 * 6.2831855], dtype=np.float32) + + +def uint32(x): + """Converts (N,) np.uint64 array into (2, N) np.unit32 array.""" + return np.moveaxis(x.view(np.uint32).reshape(-1, 2), 0, 1) + + +def philox4_round(counter, key): + """A single round of the Philox 4x32 random number generator.""" + + v1 = uint32(counter[0].astype(np.uint64) * philox_m[0]) + v2 = uint32(counter[2].astype(np.uint64) * philox_m[1]) + + counter[0] = v2[1] ^ counter[1] ^ key[0] + counter[1] = v2[0] + counter[2] = v1[1] ^ counter[3] ^ key[1] + counter[3] = v1[0] + + +def philox4_32(counter, key, rounds=10): + """Generates 32-bit random numbers using the Philox 4x32 random number generator. + + Parameters: + counter (numpy.ndarray): A 4xN array of 32-bit integers representing the counter values (offset into generation). + key (numpy.ndarray): A 2xN array of 32-bit integers representing the key values (seed). + rounds (int): The number of rounds to perform. + + Returns: + numpy.ndarray: A 4xN array of 32-bit integers containing the generated random numbers. + """ + + for _ in range(rounds - 1): + philox4_round(counter, key) + + key[0] = key[0] + philox_w[0] + key[1] = key[1] + philox_w[1] + + philox4_round(counter, key) + return counter + + +def box_muller(x, y): + """Returns just the first out of two numbers generated by Box–Muller transform algorithm.""" + u = x.astype(np.float32) * two_pow32_inv + two_pow32_inv / 2 + v = y.astype(np.float32) * two_pow32_inv_2pi + two_pow32_inv_2pi / 2 + + s = np.sqrt(-2.0 * np.log(u)) + + r1 = s * np.sin(v) + return r1.astype(np.float32) + + +class Generator: + """RNG that produces same outputs as torch.randn(..., device='cuda') on CPU""" + + def __init__(self, seed): + self.seed = seed + self.offset = 0 + + def randn(self, shape): + """Generate a sequence of n standard normal random variables using the Philox 4x32 random number generator and the Box-Muller transform.""" + + n = 1 + for x in shape: + n *= x + + counter = np.zeros((4, n), dtype=np.uint32) + counter[0] = self.offset + counter[2] = np.arange(n, dtype=np.uint32) # up to 2^32 numbers can be generated - if you want more you'd need to spill into counter[3] + self.offset += 1 + + key = uint32(np.array([[self.seed] * n], dtype=np.uint64)) + + g = philox4_32(counter, key) + + return box_muller(g[0], g[1]).reshape(shape) # discard g[2] and g[3] diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index e0da3425..d72c1b5f 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -260,10 +260,7 @@ class TorchHijack: if noise.shape == x.shape: return noise - if opts.randn_source == "CPU" or x.device.type == 'mps': - return torch.randn_like(x, device=devices.cpu).to(x.device) - else: - return torch.randn_like(x) + return devices.randn_like(x) class KDiffusionSampler: diff --git a/modules/shared.py b/modules/shared.py index aa72c9c8..7103b4ca 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -428,7 +428,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "CLIP_stop_at_last_layers": OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}).link("wiki", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#clip-skip").info("ignore last layers of CLIP network; 1 ignores none, 2 ignores one layer"), "upcast_attn": OptionInfo(False, "Upcast cross attention layer to float32"), "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"), - "randn_source": OptionInfo("GPU", "Random number generator source.", gr.Radio, {"choices": ["GPU", "CPU"]}).info("changes seeds drastically; use CPU to produce the same picture across different videocard vendors"), + "randn_source": OptionInfo("GPU", "Random number generator source.", gr.Radio, {"choices": ["GPU", "CPU", "NV"]}).info("changes seeds drastically; use CPU to produce the same picture across different videocard vendors; use NV to produce same picture as on NVidia videocards"), })) options_templates.update(options_section(('sdxl', "Stable Diffusion XL"), { -- cgit v1.2.3 From 362789a3793025c698fa42372fd66c3c4f2d6413 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Fri, 4 Aug 2023 07:50:17 +0300 Subject: gradio 3.39 --- extensions-builtin/Lora/ui_edit_user_metadata.py | 2 +- modules/gradio_extensons.py | 60 ++++++++++++++++++++++++ modules/scripts.py | 60 ------------------------ modules/shared.py | 3 +- modules/ui.py | 24 +++++----- modules/ui_checkpoint_merger.py | 2 +- modules/ui_common.py | 2 +- modules/ui_components.py | 2 +- modules/ui_extensions.py | 8 ++-- modules/ui_postprocessing.py | 2 +- requirements.txt | 2 +- requirements_versions.txt | 2 +- style.css | 12 ++++- 13 files changed, 95 insertions(+), 86 deletions(-) create mode 100644 modules/gradio_extensons.py (limited to 'modules/shared.py') diff --git a/extensions-builtin/Lora/ui_edit_user_metadata.py b/extensions-builtin/Lora/ui_edit_user_metadata.py index 2ca997f7..390d9dde 100644 --- a/extensions-builtin/Lora/ui_edit_user_metadata.py +++ b/extensions-builtin/Lora/ui_edit_user_metadata.py @@ -167,7 +167,7 @@ class LoraUserMetadataEditor(ui_extra_networks_user_metadata.UserMetadataEditor) random_prompt = gr.Textbox(label='Random prompt', lines=4, max_lines=4, interactive=False) with gr.Column(scale=1, min_width=120): - generate_random_prompt = gr.Button('Generate').style(full_width=True, size="lg") + generate_random_prompt = gr.Button('Generate', size="lg", scale=1) self.edit_notes = gr.TextArea(label='Notes', lines=4) diff --git a/modules/gradio_extensons.py b/modules/gradio_extensons.py new file mode 100644 index 00000000..5af7fd8e --- /dev/null +++ b/modules/gradio_extensons.py @@ -0,0 +1,60 @@ +import gradio as gr + +from modules import scripts + +def add_classes_to_gradio_component(comp): + """ + this adds gradio-* to the component for css styling (ie gradio-button to gr.Button), as well as some others + """ + + comp.elem_classes = [f"gradio-{comp.get_block_name()}", *(comp.elem_classes or [])] + + if getattr(comp, 'multiselect', False): + comp.elem_classes.append('multiselect') + + +def IOComponent_init(self, *args, **kwargs): + self.webui_tooltip = kwargs.pop('tooltip', None) + + if scripts.scripts_current is not None: + scripts.scripts_current.before_component(self, **kwargs) + + scripts.script_callbacks.before_component_callback(self, **kwargs) + + res = original_IOComponent_init(self, *args, **kwargs) + + add_classes_to_gradio_component(self) + + scripts.script_callbacks.after_component_callback(self, **kwargs) + + if scripts.scripts_current is not None: + scripts.scripts_current.after_component(self, **kwargs) + + return res + + +def Block_get_config(self): + config = original_Block_get_config(self) + + webui_tooltip = getattr(self, 'webui_tooltip', None) + if webui_tooltip: + config["webui_tooltip"] = webui_tooltip + + return config + + +def BlockContext_init(self, *args, **kwargs): + res = original_BlockContext_init(self, *args, **kwargs) + + add_classes_to_gradio_component(self) + + return res + + +original_IOComponent_init = gr.components.IOComponent.__init__ +original_Block_get_config = gr.blocks.Block.get_config +original_BlockContext_init = gr.blocks.BlockContext.__init__ + +gr.components.IOComponent.__init__ = IOComponent_init +gr.blocks.Block.get_config = Block_get_config +gr.blocks.BlockContext.__init__ = BlockContext_init diff --git a/modules/scripts.py b/modules/scripts.py index edf7347e..f7d060aa 100644 --- a/modules/scripts.py +++ b/modules/scripts.py @@ -631,63 +631,3 @@ def reload_script_body_only(): reload_scripts = load_scripts # compatibility alias - - -def add_classes_to_gradio_component(comp): - """ - this adds gradio-* to the component for css styling (ie gradio-button to gr.Button), as well as some others - """ - - comp.elem_classes = [f"gradio-{comp.get_block_name()}", *(comp.elem_classes or [])] - - if getattr(comp, 'multiselect', False): - comp.elem_classes.append('multiselect') - - - -def IOComponent_init(self, *args, **kwargs): - self.webui_tooltip = kwargs.pop('tooltip', None) - - if scripts_current is not None: - scripts_current.before_component(self, **kwargs) - - script_callbacks.before_component_callback(self, **kwargs) - - res = original_IOComponent_init(self, *args, **kwargs) - - add_classes_to_gradio_component(self) - - script_callbacks.after_component_callback(self, **kwargs) - - if scripts_current is not None: - scripts_current.after_component(self, **kwargs) - - return res - - -def Block_get_config(self): - config = original_Block_get_config(self) - - webui_tooltip = getattr(self, 'webui_tooltip', None) - if webui_tooltip: - config["webui_tooltip"] = webui_tooltip - - return config - - -original_IOComponent_init = gr.components.IOComponent.__init__ -original_Block_get_config = gr.components.Block.get_config -gr.components.IOComponent.__init__ = IOComponent_init -gr.components.Block.get_config = Block_get_config - - -def BlockContext_init(self, *args, **kwargs): - res = original_BlockContext_init(self, *args, **kwargs) - - add_classes_to_gradio_component(self) - - return res - - -original_BlockContext_init = gr.blocks.BlockContext.__init__ -gr.blocks.BlockContext.__init__ = BlockContext_init diff --git a/modules/shared.py b/modules/shared.py index 7103b4ca..cec030f7 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -385,7 +385,8 @@ options_templates.update(options_section(('face-restoration', "Face restoration" })) options_templates.update(options_section(('system', "System"), { - "show_warnings": OptionInfo(False, "Show warnings in console."), + "show_warnings": OptionInfo(False, "Show warnings in console.").needs_restart(), + "show_gradio_deprecation_warnings": OptionInfo(True, "Show gradio deprecation warnings in console.").needs_restart(), "memmon_poll_rate": OptionInfo(8, "VRAM usage polls per second during generation.", gr.Slider, {"minimum": 0, "maximum": 40, "step": 1}).info("0 = disable"), "samples_log_stdout": OptionInfo(False, "Always print all generation info to standard output"), "multiple_tqdm": OptionInfo(True, "Add a second progress bar to the console that shows progress for an entire job."), diff --git a/modules/ui.py b/modules/ui.py index 03306ba9..822a7660 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -12,6 +12,7 @@ import numpy as np from PIL import Image, PngImagePlugin # noqa: F401 from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call +from modules import gradio_extensons # noqa: F401 from modules import sd_hijack, sd_models, script_callbacks, ui_extensions, deepbooru, extra_networks, ui_common, ui_postprocessing, progress, ui_loadsave, errors, shared_items, ui_settings, timer, sysinfo, ui_checkpoint_merger, ui_prompt_styles, scripts from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML from modules.paths import script_path @@ -34,6 +35,7 @@ from modules.generation_parameters_copypaste import image_from_url_text create_setting_component = ui_settings.create_setting_component warnings.filterwarnings("default" if opts.show_warnings else "ignore", category=UserWarning) +warnings.filterwarnings("default" if opts.show_gradio_deprecation_warnings else "ignore", category=gr.deprecation.GradioDeprecationWarning) # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI mimetypes.init() @@ -146,7 +148,6 @@ def interrogate_deepbooru(image): def create_seed_inputs(target_interface): with FormRow(elem_id=f"{target_interface}_seed_row", variant="compact"): seed = (gr.Textbox if cmd_opts.use_textbox_seed else gr.Number)(label='Seed', value=-1, elem_id=f"{target_interface}_seed") - seed.style(container=False) random_seed = ToolButton(random_symbol, elem_id=f"{target_interface}_random_seed", label='Random seed') reuse_seed = ToolButton(reuse_symbol, elem_id=f"{target_interface}_reuse_seed", label='Reuse seed') @@ -158,7 +159,6 @@ def create_seed_inputs(target_interface): with FormRow(visible=False, elem_id=f"{target_interface}_subseed_row") as seed_extra_row_1: seed_extras.append(seed_extra_row_1) subseed = gr.Number(label='Variation seed', value=-1, elem_id=f"{target_interface}_subseed") - subseed.style(container=False) random_subseed = ToolButton(random_symbol, elem_id=f"{target_interface}_random_subseed") reuse_subseed = ToolButton(reuse_symbol, elem_id=f"{target_interface}_reuse_subseed") subseed_strength = gr.Slider(label='Variation strength', value=0.0, minimum=0, maximum=1, step=0.01, elem_id=f"{target_interface}_subseed_strength") @@ -408,7 +408,7 @@ def create_ui(): from modules import ui_extra_networks extra_networks_ui = ui_extra_networks.create_ui(extra_networks, toprow.extra_networks_button, 'txt2img') - with gr.Row().style(equal_height=False): + with gr.Row(equal_height=False): with gr.Column(variant='compact', elem_id="txt2img_settings"): scripts.scripts_txt2img.prepare_ui() @@ -636,7 +636,7 @@ def create_ui(): from modules import ui_extra_networks extra_networks_ui_img2img = ui_extra_networks.create_ui(extra_networks, toprow.extra_networks_button, 'img2img') - with FormRow().style(equal_height=False): + with FormRow(equal_height=False): with gr.Column(variant='compact', elem_id="img2img_settings"): copy_image_buttons = [] copy_image_destinations = {} @@ -658,19 +658,19 @@ def create_ui(): img2img_selected_tab = gr.State(0) with gr.TabItem('img2img', id='img2img', elem_id="img2img_img2img_tab") as tab_img2img: - init_img = gr.Image(label="Image for img2img", elem_id="img2img_image", show_label=False, source="upload", interactive=True, type="pil", tool="editor", image_mode="RGBA").style(height=opts.img2img_editor_height) + init_img = gr.Image(label="Image for img2img", elem_id="img2img_image", show_label=False, source="upload", interactive=True, type="pil", tool="editor", image_mode="RGBA", height=opts.img2img_editor_height) add_copy_image_controls('img2img', init_img) with gr.TabItem('Sketch', id='img2img_sketch', elem_id="img2img_img2img_sketch_tab") as tab_sketch: - sketch = gr.Image(label="Image for img2img", elem_id="img2img_sketch", show_label=False, source="upload", interactive=True, type="pil", tool="color-sketch", image_mode="RGBA").style(height=opts.img2img_editor_height) + sketch = gr.Image(label="Image for img2img", elem_id="img2img_sketch", show_label=False, source="upload", interactive=True, type="pil", tool="color-sketch", image_mode="RGBA", height=opts.img2img_editor_height) add_copy_image_controls('sketch', sketch) with gr.TabItem('Inpaint', id='inpaint', elem_id="img2img_inpaint_tab") as tab_inpaint: - init_img_with_mask = gr.Image(label="Image for inpainting with mask", show_label=False, elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool="sketch", image_mode="RGBA").style(height=opts.img2img_editor_height) + init_img_with_mask = gr.Image(label="Image for inpainting with mask", show_label=False, elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool="sketch", image_mode="RGBA", height=opts.img2img_editor_height) add_copy_image_controls('inpaint', init_img_with_mask) with gr.TabItem('Inpaint sketch', id='inpaint_sketch', elem_id="img2img_inpaint_sketch_tab") as tab_inpaint_color: - inpaint_color_sketch = gr.Image(label="Color sketch inpainting", show_label=False, elem_id="inpaint_sketch", source="upload", interactive=True, type="pil", tool="color-sketch", image_mode="RGBA").style(height=opts.img2img_editor_height) + inpaint_color_sketch = gr.Image(label="Color sketch inpainting", show_label=False, elem_id="inpaint_sketch", source="upload", interactive=True, type="pil", tool="color-sketch", image_mode="RGBA", height=opts.img2img_editor_height) inpaint_color_sketch_orig = gr.State(None) add_copy_image_controls('inpaint_sketch', inpaint_color_sketch) @@ -993,7 +993,7 @@ def create_ui(): ui_postprocessing.create_ui() with gr.Blocks(analytics_enabled=False) as pnginfo_interface: - with gr.Row().style(equal_height=False): + with gr.Row(equal_height=False): with gr.Column(variant='panel'): image = gr.Image(elem_id="pnginfo_image", label="Source", source="upload", interactive=True, type="pil") @@ -1018,10 +1018,10 @@ def create_ui(): modelmerger_ui = ui_checkpoint_merger.UiCheckpointMerger() with gr.Blocks(analytics_enabled=False) as train_interface: - with gr.Row().style(equal_height=False): + with gr.Row(equal_height=False): gr.HTML(value="
See wiki for detailed explanation.
") - with gr.Row(variant="compact").style(equal_height=False): + with gr.Row(variant="compact", equal_height=False): with gr.Tabs(elem_id="train_tabs"): with gr.Tab(label="Create embedding", id="create_embedding"): @@ -1181,7 +1181,7 @@ def create_ui(): with gr.Column(elem_id='ti_gallery_container'): ti_output = gr.Text(elem_id="ti_output", value="", show_label=False) - gr.Gallery(label='Output', show_label=False, elem_id='ti_gallery').style(columns=4) + gr.Gallery(label='Output', show_label=False, elem_id='ti_gallery', columns=4) gr.HTML(elem_id="ti_progress", value="") ti_outcome = gr.HTML(elem_id="ti_error", value="") diff --git a/modules/ui_checkpoint_merger.py b/modules/ui_checkpoint_merger.py index 4863d861..f9c5dd6b 100644 --- a/modules/ui_checkpoint_merger.py +++ b/modules/ui_checkpoint_merger.py @@ -29,7 +29,7 @@ def modelmerger(*args): class UiCheckpointMerger: def __init__(self): with gr.Blocks(analytics_enabled=False) as modelmerger_interface: - with gr.Row().style(equal_height=False): + with gr.Row(equal_height=False): with gr.Column(variant='compact'): self.interp_description = gr.HTML(value=update_interp_description("Weighted sum"), elem_id="modelmerger_interp_description") diff --git a/modules/ui_common.py b/modules/ui_common.py index ba75fa73..eefe0c0e 100644 --- a/modules/ui_common.py +++ b/modules/ui_common.py @@ -134,7 +134,7 @@ Requested path was: {f} with gr.Column(variant='panel', elem_id=f"{tabname}_results"): with gr.Group(elem_id=f"{tabname}_gallery_container"): - result_gallery = gr.Gallery(label='Output', show_label=False, elem_id=f"{tabname}_gallery").style(columns=4) + result_gallery = gr.Gallery(label='Output', show_label=False, elem_id=f"{tabname}_gallery", columns=4) generation_info = None with gr.Column(): diff --git a/modules/ui_components.py b/modules/ui_components.py index 64451df7..8f8a7088 100644 --- a/modules/ui_components.py +++ b/modules/ui_components.py @@ -35,7 +35,7 @@ class FormColumn(FormComponent, gr.Column): class FormGroup(FormComponent, gr.Group): - """Same as gr.Row but fits inside gradio forms""" + """Same as gr.Group but fits inside gradio forms""" def get_block_name(self): return "group" diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py index bd28bfcf..15a8b0bf 100644 --- a/modules/ui_extensions.py +++ b/modules/ui_extensions.py @@ -533,8 +533,8 @@ def create_ui(): apply = gr.Button(value=apply_label, variant="primary") check = gr.Button(value="Check for updates") extensions_disable_all = gr.Radio(label="Disable all extensions", choices=["none", "extra", "all"], value=shared.opts.disable_all_extensions, elem_id="extensions_disable_all") - extensions_disabled_list = gr.Text(elem_id="extensions_disabled_list", visible=False).style(container=False) - extensions_update_list = gr.Text(elem_id="extensions_update_list", visible=False).style(container=False) + extensions_disabled_list = gr.Text(elem_id="extensions_disabled_list", visible=False, container=False) + extensions_update_list = gr.Text(elem_id="extensions_update_list", visible=False, container=False) html = "" @@ -569,7 +569,7 @@ def create_ui(): with gr.Row(): refresh_available_extensions_button = gr.Button(value="Load from:", variant="primary") extensions_index_url = os.environ.get('WEBUI_EXTENSIONS_INDEX', "https://raw.githubusercontent.com/AUTOMATIC1111/stable-diffusion-webui-extensions/master/index.json") - available_extensions_index = gr.Text(value=extensions_index_url, label="Extension index URL").style(container=False) + available_extensions_index = gr.Text(value=extensions_index_url, label="Extension index URL", container=False) extension_to_install = gr.Text(elem_id="extension_to_install", visible=False) install_extension_button = gr.Button(elem_id="install_extension_button", visible=False) @@ -578,7 +578,7 @@ def create_ui(): sort_column = gr.Radio(value="newest first", label="Order", choices=["newest first", "oldest first", "a-z", "z-a", "internal order",'update time', 'create time', "stars"], type="index") with gr.Row(): - search_extensions_text = gr.Text(label="Search").style(container=False) + search_extensions_text = gr.Text(label="Search", container=False) install_result = gr.HTML() available_extensions_table = gr.HTML() diff --git a/modules/ui_postprocessing.py b/modules/ui_postprocessing.py index c7dc1154..802e1ce7 100644 --- a/modules/ui_postprocessing.py +++ b/modules/ui_postprocessing.py @@ -6,7 +6,7 @@ import modules.generation_parameters_copypaste as parameters_copypaste def create_ui(): tab_index = gr.State(value=0) - with gr.Row().style(equal_height=False, variant='compact'): + with gr.Row(equal_height=False, variant='compact'): with gr.Column(variant='compact'): with gr.Tabs(elem_id="mode_extras"): with gr.TabItem('Single Image', id="single_image", elem_id="extras_single_tab") as tab_single: diff --git a/requirements.txt b/requirements.txt index b3f8a7f4..afdc6ee2 100644 --- a/requirements.txt +++ b/requirements.txt @@ -7,7 +7,7 @@ blendmodes clean-fid einops gfpgan -gradio==3.32.0 +gradio==3.39.0 inflection jsonmerge kornia diff --git a/requirements_versions.txt b/requirements_versions.txt index d07ab456..82b8732d 100644 --- a/requirements_versions.txt +++ b/requirements_versions.txt @@ -7,7 +7,7 @@ clean-fid==0.1.35 einops==0.4.1 fastapi==0.94.0 gfpgan==1.3.8 -gradio==3.32.0 +gradio==3.39.0 httpcore==0.15 inflection==0.5.1 jsonmerge==1.8.0 diff --git a/style.css b/style.css index cf8470e4..86b4f61e 100644 --- a/style.css +++ b/style.css @@ -8,6 +8,7 @@ --checkbox-label-gap: 0.25em 0.1em; --section-header-text-size: 12pt; --block-background-fill: transparent; + } .block.padded:not(.gradio-accordion) { @@ -42,7 +43,8 @@ div.form{ .block.gradio-radio, .block.gradio-checkboxgroup, .block.gradio-number, -.block.gradio-colorpicker +.block.gradio-colorpicker, +div.gradio-group { border-width: 0 !important; box-shadow: none !important; @@ -133,6 +135,11 @@ a{ cursor: pointer; } +div.styler{ + border: none; + background: var(--background-fill-primary); +} + /* general styled components */ @@ -164,7 +171,7 @@ a{ .checkboxes-row > div{ flex: 0; white-space: nowrap; - min-width: auto; + min-width: auto !important; } button.custom-button{ @@ -388,6 +395,7 @@ div#extras_scale_to_tab div.form{ #quicksettings > div, #quicksettings > fieldset{ max-width: 24em; min-width: 24em; + width: 24em; padding: 0; border: none; box-shadow: none; -- cgit v1.2.3 From 1d60a609a9d7a7f79517dc0c87d4b834b89db252 Mon Sep 17 00:00:00 2001 From: w-e-w <40751091+w-e-w@users.noreply.github.com> Date: Sat, 5 Aug 2023 09:25:21 +0900 Subject: configurable masks color and default brush color --- modules/shared.py | 3 +++ modules/ui.py | 6 +++--- 2 files changed, 6 insertions(+), 3 deletions(-) (limited to 'modules/shared.py') diff --git a/modules/shared.py b/modules/shared.py index cec030f7..1eb00b8f 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -492,6 +492,9 @@ options_templates.update(options_section(('ui', "User interface"), { "localization": OptionInfo("None", "Localization", gr.Dropdown, lambda: {"choices": ["None"] + list(localization.localizations.keys())}, refresh=lambda: localization.list_localizations(cmd_opts.localizations_dir)).needs_restart(), "gradio_theme": OptionInfo("Default", "Gradio theme", ui_components.DropdownEditable, lambda: {"choices": ["Default"] + gradio_hf_hub_themes}).needs_restart(), "img2img_editor_height": OptionInfo(720, "img2img: height of image editor", gr.Slider, {"minimum": 80, "maximum": 1600, "step": 1}).info("in pixels").needs_restart(), + "img2img_sketch_default_brush_color": OptionInfo("#000000", "sketch brush color", ui_components.FormColorPicker, {}).info("default brush color of img2img sketch) (requires reload"), + "img2img_inpaint_mask_brush_color": OptionInfo("#000000", "inpaint mask brush color", ui_components.FormColorPicker, {}).info("brush color of inpaint mask) (requires reload"), + "img2img_inpaint_sketch_default_brush_color": OptionInfo("#000000", "inpaint sketch brush color", ui_components.FormColorPicker, {}).info("default brush color of img2img inpaint sketch) (requires reload"), "return_grid": OptionInfo(True, "Show grid in results for web"), "return_mask": OptionInfo(False, "For inpainting, include the greyscale mask in results for web"), "return_mask_composite": OptionInfo(False, "For inpainting, include masked composite in results for web"), diff --git a/modules/ui.py b/modules/ui.py index 6cf3dff8..843a75ef 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -663,15 +663,15 @@ def create_ui(): add_copy_image_controls('img2img', init_img) with gr.TabItem('Sketch', id='img2img_sketch', elem_id="img2img_img2img_sketch_tab") as tab_sketch: - sketch = gr.Image(label="Image for img2img", elem_id="img2img_sketch", show_label=False, source="upload", interactive=True, type="pil", tool="color-sketch", image_mode="RGBA", height=opts.img2img_editor_height) + sketch = gr.Image(label="Image for img2img", elem_id="img2img_sketch", show_label=False, source="upload", interactive=True, type="pil", tool="color-sketch", image_mode="RGBA", height=opts.img2img_editor_height, brush_color=opts.img2img_sketch_default_brush_color) add_copy_image_controls('sketch', sketch) with gr.TabItem('Inpaint', id='inpaint', elem_id="img2img_inpaint_tab") as tab_inpaint: - init_img_with_mask = gr.Image(label="Image for inpainting with mask", show_label=False, elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool="sketch", image_mode="RGBA", height=opts.img2img_editor_height, brush_color='#ffffff') + init_img_with_mask = gr.Image(label="Image for inpainting with mask", show_label=False, elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool="sketch", image_mode="RGBA", height=opts.img2img_editor_height, brush_color=opts.img2img_inpaint_mask_brush_color) add_copy_image_controls('inpaint', init_img_with_mask) with gr.TabItem('Inpaint sketch', id='inpaint_sketch', elem_id="img2img_inpaint_sketch_tab") as tab_inpaint_color: - inpaint_color_sketch = gr.Image(label="Color sketch inpainting", show_label=False, elem_id="inpaint_sketch", source="upload", interactive=True, type="pil", tool="color-sketch", image_mode="RGBA", height=opts.img2img_editor_height, brush_color='#ffffff') + inpaint_color_sketch = gr.Image(label="Color sketch inpainting", show_label=False, elem_id="inpaint_sketch", source="upload", interactive=True, type="pil", tool="color-sketch", image_mode="RGBA", height=opts.img2img_editor_height, brush_color=opts.img2img_inpaint_sketch_default_brush_color) inpaint_color_sketch_orig = gr.State(None) add_copy_image_controls('inpaint_sketch', inpaint_color_sketch) -- cgit v1.2.3 From e7140a36c07c7590334eaaea07a3c79d7e044db9 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Sat, 5 Aug 2023 07:36:25 +0300 Subject: change default color to white --- modules/shared.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) (limited to 'modules/shared.py') diff --git a/modules/shared.py b/modules/shared.py index 1eb00b8f..fca6ad63 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -492,9 +492,9 @@ options_templates.update(options_section(('ui', "User interface"), { "localization": OptionInfo("None", "Localization", gr.Dropdown, lambda: {"choices": ["None"] + list(localization.localizations.keys())}, refresh=lambda: localization.list_localizations(cmd_opts.localizations_dir)).needs_restart(), "gradio_theme": OptionInfo("Default", "Gradio theme", ui_components.DropdownEditable, lambda: {"choices": ["Default"] + gradio_hf_hub_themes}).needs_restart(), "img2img_editor_height": OptionInfo(720, "img2img: height of image editor", gr.Slider, {"minimum": 80, "maximum": 1600, "step": 1}).info("in pixels").needs_restart(), - "img2img_sketch_default_brush_color": OptionInfo("#000000", "sketch brush color", ui_components.FormColorPicker, {}).info("default brush color of img2img sketch) (requires reload"), - "img2img_inpaint_mask_brush_color": OptionInfo("#000000", "inpaint mask brush color", ui_components.FormColorPicker, {}).info("brush color of inpaint mask) (requires reload"), - "img2img_inpaint_sketch_default_brush_color": OptionInfo("#000000", "inpaint sketch brush color", ui_components.FormColorPicker, {}).info("default brush color of img2img inpaint sketch) (requires reload"), + "img2img_sketch_default_brush_color": OptionInfo("#ffffff", "sketch brush color", ui_components.FormColorPicker, {}).info("default brush color of img2img sketch").needs_restart(), + "img2img_inpaint_mask_brush_color": OptionInfo("#ffffff", "inpaint mask brush color", ui_components.FormColorPicker, {}).info("brush color of inpaint mask").needs_restart(), + "img2img_inpaint_sketch_default_brush_color": OptionInfo("#ffffff", "inpaint sketch brush color", ui_components.FormColorPicker, {}).info("default brush color of img2img inpaint sketch").needs_restart(), "return_grid": OptionInfo(True, "Show grid in results for web"), "return_mask": OptionInfo(False, "For inpainting, include the greyscale mask in results for web"), "return_mask_composite": OptionInfo(False, "For inpainting, include masked composite in results for web"), -- cgit v1.2.3 From d2b842ce079949f2eafa8a4a6e2374f0e5acac34 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Sat, 5 Aug 2023 07:46:22 +0300 Subject: move img2img settings to their own section --- modules/shared.py | 32 +++++++++++++++++++------------- 1 file changed, 19 insertions(+), 13 deletions(-) (limited to 'modules/shared.py') diff --git a/modules/shared.py b/modules/shared.py index fca6ad63..55199cb9 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -417,12 +417,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "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_unet": OptionInfo("Automatic", "SD Unet", gr.Dropdown, lambda: {"choices": shared_items.sd_unet_items()}, refresh=shared_items.refresh_unet_list).info("choose Unet model: Automatic = use one with same filename as checkpoint; None = use Unet from checkpoint"), - "inpainting_mask_weight": OptionInfo(1.0, "Inpainting conditioning mask strength", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), - "initial_noise_multiplier": OptionInfo(1.0, "Noise multiplier for img2img", gr.Slider, {"minimum": 0.5, "maximum": 1.5, "step": 0.01}), - "img2img_color_correction": OptionInfo(False, "Apply color correction to img2img results to match original colors."), - "img2img_fix_steps": OptionInfo(False, "With img2img, do exactly the amount of steps the slider specifies.").info("normally you'd do less with less denoising"), - "img2img_background_color": OptionInfo("#ffffff", "With img2img, fill image's transparent parts with this color.", ui_components.FormColorPicker, {}), - "enable_quantization": OptionInfo(False, "Enable quantization in K samplers for sharper and cleaner results. This may change existing seeds. Requires restart to apply."), + "enable_quantization": OptionInfo(False, "Enable quantization in K samplers for sharper and cleaner results. This may change existing seeds").needs_restart(), "enable_emphasis": OptionInfo(True, "Enable emphasis").info("use (text) to make model pay more attention to text and [text] to make it pay less attention"), "enable_batch_seeds": OptionInfo(True, "Make K-diffusion samplers produce same images in a batch as when making a single image"), "comma_padding_backtrack": OptionInfo(20, "Prompt word wrap length limit", gr.Slider, {"minimum": 0, "maximum": 74, "step": 1}).info("in tokens - for texts shorter than specified, if they don't fit into 75 token limit, move them to the next 75 token chunk"), @@ -439,6 +434,22 @@ options_templates.update(options_section(('sdxl', "Stable Diffusion XL"), { "sdxl_refiner_high_aesthetic_score": OptionInfo(6.0, "SDXL high aesthetic score", gr.Number).info("used for refiner model prompt"), })) + +options_templates.update(options_section(('img2img', "img2img"), { + "inpainting_mask_weight": OptionInfo(1.0, "Inpainting conditioning mask strength", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), + "initial_noise_multiplier": OptionInfo(1.0, "Noise multiplier for img2img", gr.Slider, {"minimum": 0.5, "maximum": 1.5, "step": 0.01}), + "img2img_color_correction": OptionInfo(False, "Apply color correction to img2img results to match original colors."), + "img2img_fix_steps": OptionInfo(False, "With img2img, do exactly the amount of steps the slider specifies.").info("normally you'd do less with less denoising"), + "img2img_background_color": OptionInfo("#ffffff", "With img2img, fill transparent parts of the input image with this color.", ui_components.FormColorPicker, {}), + "img2img_editor_height": OptionInfo(720, "Height of the image editor", gr.Slider, {"minimum": 80, "maximum": 1600, "step": 1}).info("in pixels").needs_restart(), + "img2img_sketch_default_brush_color": OptionInfo("#ffffff", "Sketch initial brush color", ui_components.FormColorPicker, {}).info("default brush color of img2img sketch").needs_restart(), + "img2img_inpaint_mask_brush_color": OptionInfo("#ffffff", "Inpaint mask brush color", ui_components.FormColorPicker, {}).info("brush color of inpaint mask").needs_restart(), + "img2img_inpaint_sketch_default_brush_color": OptionInfo("#ffffff", "Inpaint sketch initial brush color", ui_components.FormColorPicker, {}).info("default brush color of img2img inpaint sketch").needs_restart(), + "return_mask": OptionInfo(False, "For inpainting, include the greyscale mask in results for web"), + "return_mask_composite": OptionInfo(False, "For inpainting, include masked composite in results for web"), +})) + + options_templates.update(options_section(('optimizations', "Optimizations"), { "cross_attention_optimization": OptionInfo("Automatic", "Cross attention optimization", gr.Dropdown, lambda: {"choices": shared_items.cross_attention_optimizations()}), "s_min_uncond": OptionInfo(0.0, "Negative Guidance minimum sigma", gr.Slider, {"minimum": 0.0, "maximum": 15.0, "step": 0.01}).link("PR", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/9177").info("skip negative prompt for some steps when the image is almost ready; 0=disable, higher=faster"), @@ -458,7 +469,7 @@ options_templates.update(options_section(('compatibility', "Compatibility"), { "hires_fix_use_firstpass_conds": OptionInfo(False, "For hires fix, calculate conds of second pass using extra networks of first pass."), })) -options_templates.update(options_section(('interrogate', "Interrogate Options"), { +options_templates.update(options_section(('interrogate', "Interrogate"), { "interrogate_keep_models_in_memory": OptionInfo(False, "Keep models in VRAM"), "interrogate_return_ranks": OptionInfo(False, "Include ranks of model tags matches in results.").info("booru only"), "interrogate_clip_num_beams": OptionInfo(1, "BLIP: num_beams", gr.Slider, {"minimum": 1, "maximum": 16, "step": 1}), @@ -491,13 +502,7 @@ options_templates.update(options_section(('extra_networks', "Extra Networks"), { options_templates.update(options_section(('ui', "User interface"), { "localization": OptionInfo("None", "Localization", gr.Dropdown, lambda: {"choices": ["None"] + list(localization.localizations.keys())}, refresh=lambda: localization.list_localizations(cmd_opts.localizations_dir)).needs_restart(), "gradio_theme": OptionInfo("Default", "Gradio theme", ui_components.DropdownEditable, lambda: {"choices": ["Default"] + gradio_hf_hub_themes}).needs_restart(), - "img2img_editor_height": OptionInfo(720, "img2img: height of image editor", gr.Slider, {"minimum": 80, "maximum": 1600, "step": 1}).info("in pixels").needs_restart(), - "img2img_sketch_default_brush_color": OptionInfo("#ffffff", "sketch brush color", ui_components.FormColorPicker, {}).info("default brush color of img2img sketch").needs_restart(), - "img2img_inpaint_mask_brush_color": OptionInfo("#ffffff", "inpaint mask brush color", ui_components.FormColorPicker, {}).info("brush color of inpaint mask").needs_restart(), - "img2img_inpaint_sketch_default_brush_color": OptionInfo("#ffffff", "inpaint sketch brush color", ui_components.FormColorPicker, {}).info("default brush color of img2img inpaint sketch").needs_restart(), "return_grid": OptionInfo(True, "Show grid in results for web"), - "return_mask": OptionInfo(False, "For inpainting, include the greyscale mask in results for web"), - "return_mask_composite": OptionInfo(False, "For inpainting, include masked composite in results for web"), "do_not_show_images": OptionInfo(False, "Do not show any images in results for web"), "send_seed": OptionInfo(True, "Send seed when sending prompt or image to other interface"), "send_size": OptionInfo(True, "Send size when sending prompt or image to another interface"), @@ -521,6 +526,7 @@ options_templates.update(options_section(('ui', "User interface"), { "disable_token_counters": OptionInfo(False, "Disable prompt token counters").needs_restart(), })) + options_templates.update(options_section(('infotext', "Infotext"), { "add_model_hash_to_info": OptionInfo(True, "Add model hash to generation information"), "add_model_name_to_info": OptionInfo(True, "Add model name to generation information"), -- cgit v1.2.3