From 7afe7375e104d85542f7572ca0f8559bb4e3a7fe Mon Sep 17 00:00:00 2001 From: Jabasukuriputo Wang Date: Sat, 22 Jul 2023 17:46:50 +0800 Subject: [PATCH 01/43] display a progressbar for extension installer --- modules/launch_utils.py | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/modules/launch_utils.py b/modules/launch_utils.py index 18b444d42..b827debe2 100644 --- a/modules/launch_utils.py +++ b/modules/launch_utils.py @@ -7,6 +7,7 @@ import importlib.util import platform import json from functools import lru_cache +from tqdm.auto import tqdm from modules import cmd_args, errors from modules.paths_internal import script_path, extensions_dir @@ -224,7 +225,10 @@ def run_extensions_installers(settings_file): if not os.path.isdir(extensions_dir): return - for dirname_extension in list_extensions(settings_file): + pbar_extensions = tqdm(list_extensions(settings_file), + bar_format="{desc}: |{bar}|{percentage:3.0f}% [{n_fmt}/{total_fmt} {elapsed}<{remaining}]") + for dirname_extension in pbar_extensions: + pbar_extensions.set_description("Installing %s" % dirname_extension) run_extension_installer(os.path.join(extensions_dir, dirname_extension)) From b2f0040da7df65a5deac34f59263cf518d970dcd Mon Sep 17 00:00:00 2001 From: Jabasukuriputo Wang Date: Sat, 22 Jul 2023 17:51:15 +0800 Subject: [PATCH 02/43] fix tqdm not found on new instance --- modules/launch_utils.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/modules/launch_utils.py b/modules/launch_utils.py index b827debe2..432560725 100644 --- a/modules/launch_utils.py +++ b/modules/launch_utils.py @@ -7,7 +7,6 @@ import importlib.util import platform import json from functools import lru_cache -from tqdm.auto import tqdm from modules import cmd_args, errors from modules.paths_internal import script_path, extensions_dir @@ -225,6 +224,7 @@ def run_extensions_installers(settings_file): if not os.path.isdir(extensions_dir): return + from tqdm.auto import tqdm pbar_extensions = tqdm(list_extensions(settings_file), bar_format="{desc}: |{bar}|{percentage:3.0f}% [{n_fmt}/{total_fmt} {elapsed}<{remaining}]") for dirname_extension in pbar_extensions: From 3ca3c7f1c62f525539926fa883d8f5d54de85de6 Mon Sep 17 00:00:00 2001 From: catboxanon <122327233+catboxanon@users.noreply.github.com> Date: Fri, 4 Aug 2023 07:20:32 -0400 Subject: [PATCH 03/43] Add styling for script components --- style.css | 7 +++++++ 1 file changed, 7 insertions(+) diff --git a/style.css b/style.css index 86b4f61ef..d9699668b 100644 --- a/style.css +++ b/style.css @@ -190,6 +190,13 @@ button.custom-button{ text-align: center; } +.gradio-group[id$="_script_container"] > div .gradio-group > div > div:is(.gradio-accordion, .form) { + border: 1px solid var(--block-border-color) !important; + border-radius: 8px !important; + margin: 2px 0; + padding: 8px 8px; +} + /* txt2img/img2img specific */ From b0f7f4a99125b55fed8acabb458fac6299e98fb1 Mon Sep 17 00:00:00 2001 From: Olivier Lacan Date: Mon, 7 Aug 2023 12:42:46 -0700 Subject: [PATCH 04/43] Pin fastapi to > 0.90.1 to fix crash See https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/11642#issuecomment-1643298659 This resolves a crashing bug for me on Python 3.10 and it appears to do so as well for others. --- requirements.txt | 1 + 1 file changed, 1 insertion(+) diff --git a/requirements.txt b/requirements.txt index 9a47d6d0d..d83092f0a 100644 --- a/requirements.txt +++ b/requirements.txt @@ -6,6 +6,7 @@ basicsr blendmodes clean-fid einops +fastapi>=0.90.1 gfpgan gradio==3.39.0 inflection From 8c200c21564992b7af1d2d692524051158e533db Mon Sep 17 00:00:00 2001 From: Uminosachi <49424133+Uminosachi@users.noreply.github.com> Date: Tue, 8 Aug 2023 10:48:03 +0900 Subject: [PATCH 05/43] Fix mismatch between shared.sd_model & shared.opts --- modules/sd_models.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/modules/sd_models.py b/modules/sd_models.py index 53c1df54c..cded27d41 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -623,6 +623,8 @@ def reuse_model_from_already_loaded(sd_model, checkpoint_info, timer): timer.record("send model to device") model_data.set_sd_model(already_loaded) + shared.opts.data["sd_model_checkpoint"] = already_loaded.sd_checkpoint_info.title + shared.opts.data["sd_checkpoint_hash"] = already_loaded.sd_checkpoint_info.sha256 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: From 2a72d76d6f3d34b1ffccec7736b19e7d52033dad Mon Sep 17 00:00:00 2001 From: dhwz Date: Tue, 8 Aug 2023 19:08:37 +0200 Subject: [PATCH 06/43] fix typo --- modules/processing.py | 2 +- modules/shared.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/modules/processing.py b/modules/processing.py index 317450065..dc6e8ff1c 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -568,7 +568,7 @@ def decode_latent_batch(model, batch, target_device=None, check_for_nans=False): 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 disable this behavior, disable the 'Automatically revert VAE to 32-bit floats' setting.\n" "To always start with 32-bit VAE, use --no-half-vae commandline flag." ) diff --git a/modules/shared.py b/modules/shared.py index 97f1eab52..e34847cef 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -481,7 +481,7 @@ For img2img, VAE is used to process user's input image before the sampling, and "sd_vae_checkpoint_cache": OptionInfo(0, "VAE Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}), "sd_vae": OptionInfo("Automatic", "SD VAE", gr.Dropdown, lambda: {"choices": shared_items.sd_vae_items()}, refresh=shared_items.refresh_vae_list).info("choose VAE model: Automatic = use one with same filename as checkpoint; None = use VAE from checkpoint"), "sd_vae_overrides_per_model_preferences": OptionInfo(True, "Selected VAE overrides per-model preferences").info("you can set per-model VAE either by editing user metadata for checkpoints, or by making the VAE have same name as checkpoint"), - "auto_vae_precision": OptionInfo(True, "Automaticlly revert VAE to 32-bit floats").info("triggers when a tensor with NaNs is produced in VAE; disabling the option in this case will result in a black square image"), + "auto_vae_precision": OptionInfo(True, "Automatically revert VAE to 32-bit floats").info("triggers when a tensor with NaNs is produced in VAE; disabling the option in this case will result in a black square image"), "sd_vae_encode_method": OptionInfo("Full", "VAE type for encode", gr.Radio, {"choices": ["Full", "TAESD"]}).info("method to encode image to latent (use in img2img, hires-fix or inpaint mask)"), "sd_vae_decode_method": OptionInfo("Full", "VAE type for decode", gr.Radio, {"choices": ["Full", "TAESD"]}).info("method to decode latent to image"), })) From bc7906e6d62bb3ed158304c581e941862355f6de Mon Sep 17 00:00:00 2001 From: Danil Boldyrev Date: Tue, 8 Aug 2023 21:28:16 +0300 Subject: [PATCH 07/43] Ability to automatically expand a picture that does not fit in the screen --- .../canvas-zoom-and-pan/javascript/zoom.js | 29 ++++++++++++++++++- .../scripts/hotkey_config.py | 1 + 2 files changed, 29 insertions(+), 1 deletion(-) diff --git a/extensions-builtin/canvas-zoom-and-pan/javascript/zoom.js b/extensions-builtin/canvas-zoom-and-pan/javascript/zoom.js index 30199dcd6..7369e8977 100644 --- a/extensions-builtin/canvas-zoom-and-pan/javascript/zoom.js +++ b/extensions-builtin/canvas-zoom-and-pan/javascript/zoom.js @@ -201,7 +201,8 @@ onUiLoaded(async() => { canvas_hotkey_overlap: "KeyO", canvas_disabled_functions: [], canvas_show_tooltip: true, - canvas_blur_prompt: false + canvas_blur_prompt: false, + canvas_auto_expand: false }; const functionMap = { @@ -648,8 +649,34 @@ onUiLoaded(async() => { mouseY = e.offsetY; } + // Simulation of the function to put a long image into the screen. + // We define the size of the canvas, make a fullscreen to reveal the image, then reduce it to fit into the element. + // We hide the image and show it to the user when it is ready. + function autoExpand(e) { + const canvas = document.querySelector(`${elemId} canvas[key="interface"]`); + const isMainTab = activeElement === elementIDs.inpaint || activeElement === elementIDs.inpaintSketch || activeElement === elementIDs.sketch; + if (canvas && isMainTab) { + if (canvas && parseInt(targetElement.style.width) > 862 || parseInt(canvas.width) < 862) { + return; + } + if (canvas) { + targetElement.style.visibility = "hidden"; + setTimeout(() => { + fitToScreen(); + resetZoom(); + targetElement.style.visibility = "visible"; + }, 10); + } + } + } + targetElement.addEventListener("mousemove", getMousePosition); + // Apply auto expand if enabled + if (hotkeysConfig.canvas_auto_expand) { + targetElement.addEventListener("mousemove", autoExpand); + } + // Handle events only inside the targetElement let isKeyDownHandlerAttached = false; diff --git a/extensions-builtin/canvas-zoom-and-pan/scripts/hotkey_config.py b/extensions-builtin/canvas-zoom-and-pan/scripts/hotkey_config.py index 380176ce2..9a51ff2a7 100644 --- a/extensions-builtin/canvas-zoom-and-pan/scripts/hotkey_config.py +++ b/extensions-builtin/canvas-zoom-and-pan/scripts/hotkey_config.py @@ -9,6 +9,7 @@ shared.options_templates.update(shared.options_section(('canvas_hotkey', "Canvas "canvas_hotkey_reset": shared.OptionInfo("R", "Reset zoom and canvas positon"), "canvas_hotkey_overlap": shared.OptionInfo("O", "Toggle overlap").info("Technical button, neededs for testing"), "canvas_show_tooltip": shared.OptionInfo(True, "Enable tooltip on the canvas"), + "canvas_auto_expand": shared.OptionInfo(False, "Automatically expands an image that does not fit completely in the canvas area, similar to manually pressing the S and R buttons"), "canvas_blur_prompt": shared.OptionInfo(False, "Take the focus off the prompt when working with a canvas"), "canvas_disabled_functions": shared.OptionInfo(["Overlap"], "Disable function that you don't use", gr.CheckboxGroup, {"choices": ["Zoom","Adjust brush size", "Moving canvas","Fullscreen","Reset Zoom","Overlap"]}), })) From 0e83c675257f473e024511845e7940802333fd5f Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Tue, 8 Aug 2023 22:27:32 +0300 Subject: [PATCH 08/43] by request: fix tiled vae extension --- modules/sd_samplers_kdiffusion.py | 5 +++-- modules/sd_samplers_timesteps.py | 4 ++++ 2 files changed, 7 insertions(+), 2 deletions(-) diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index f47431af7..5613b8c18 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -1,7 +1,8 @@ import torch import inspect import k_diffusion.sampling -from modules import sd_samplers_common, sd_samplers_extra, sd_samplers_cfg_denoiser +from modules import sd_samplers_common, sd_samplers_extra +from modules.sd_samplers_cfg_denoiser import CFGDenoiser from modules.shared import opts import modules.shared as shared @@ -62,7 +63,7 @@ class KDiffusionSampler(sd_samplers_common.Sampler): denoiser = k_diffusion.external.CompVisVDenoiser if sd_model.parameterization == "v" else k_diffusion.external.CompVisDenoiser self.model_wrap = denoiser(sd_model, quantize=shared.opts.enable_quantization) - self.model_wrap_cfg = sd_samplers_cfg_denoiser.CFGDenoiser(self.model_wrap, self) + self.model_wrap_cfg = CFGDenoiser(self.model_wrap, self) def get_sigmas(self, p, steps): discard_next_to_last_sigma = self.config is not None and self.config.options.get('discard_next_to_last_sigma', False) diff --git a/modules/sd_samplers_timesteps.py b/modules/sd_samplers_timesteps.py index d89d0efb3..f61799a82 100644 --- a/modules/sd_samplers_timesteps.py +++ b/modules/sd_samplers_timesteps.py @@ -1,5 +1,6 @@ import torch import inspect +import sys from modules import devices, sd_samplers_common, sd_samplers_timesteps_impl from modules.sd_samplers_cfg_denoiser import CFGDenoiser @@ -145,3 +146,6 @@ class CompVisSampler(sd_samplers_common.Sampler): return samples + +sys.modules['modules.sd_samplers_compvis'] = sys.modules[__name__] +VanillaStableDiffusionSampler = CompVisSampler # temp. compatibility with older extensions From a74c014425d412c0588618abe0a3e19e4f8f5902 Mon Sep 17 00:00:00 2001 From: Danil Boldyrev Date: Wed, 9 Aug 2023 00:06:51 +0300 Subject: [PATCH 09/43] auto-expand enable by default --- extensions-builtin/canvas-zoom-and-pan/scripts/hotkey_config.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/extensions-builtin/canvas-zoom-and-pan/scripts/hotkey_config.py b/extensions-builtin/canvas-zoom-and-pan/scripts/hotkey_config.py index 9a51ff2a7..2d8d2d1c0 100644 --- a/extensions-builtin/canvas-zoom-and-pan/scripts/hotkey_config.py +++ b/extensions-builtin/canvas-zoom-and-pan/scripts/hotkey_config.py @@ -9,7 +9,7 @@ shared.options_templates.update(shared.options_section(('canvas_hotkey', "Canvas "canvas_hotkey_reset": shared.OptionInfo("R", "Reset zoom and canvas positon"), "canvas_hotkey_overlap": shared.OptionInfo("O", "Toggle overlap").info("Technical button, neededs for testing"), "canvas_show_tooltip": shared.OptionInfo(True, "Enable tooltip on the canvas"), - "canvas_auto_expand": shared.OptionInfo(False, "Automatically expands an image that does not fit completely in the canvas area, similar to manually pressing the S and R buttons"), + "canvas_auto_expand": shared.OptionInfo(True, "Automatically expands an image that does not fit completely in the canvas area, similar to manually pressing the S and R buttons"), "canvas_blur_prompt": shared.OptionInfo(False, "Take the focus off the prompt when working with a canvas"), "canvas_disabled_functions": shared.OptionInfo(["Overlap"], "Disable function that you don't use", gr.CheckboxGroup, {"choices": ["Zoom","Adjust brush size", "Moving canvas","Fullscreen","Reset Zoom","Overlap"]}), })) From e12a1be1ca23377a3d5774fe8d52664a9c2c0fb9 Mon Sep 17 00:00:00 2001 From: Danil Boldyrev Date: Wed, 9 Aug 2023 00:14:19 +0300 Subject: [PATCH 10/43] auto-expand enable by default for js --- extensions-builtin/canvas-zoom-and-pan/javascript/zoom.js | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/extensions-builtin/canvas-zoom-and-pan/javascript/zoom.js b/extensions-builtin/canvas-zoom-and-pan/javascript/zoom.js index 7369e8977..eb49a01d4 100644 --- a/extensions-builtin/canvas-zoom-and-pan/javascript/zoom.js +++ b/extensions-builtin/canvas-zoom-and-pan/javascript/zoom.js @@ -201,8 +201,8 @@ onUiLoaded(async() => { canvas_hotkey_overlap: "KeyO", canvas_disabled_functions: [], canvas_show_tooltip: true, + canvas_auto_expand: true, canvas_blur_prompt: false, - canvas_auto_expand: false }; const functionMap = { From bd4b4292ef6c2cb0a452b7105485ec06301b7531 Mon Sep 17 00:00:00 2001 From: catboxanon <122327233+catboxanon@users.noreply.github.com> Date: Tue, 8 Aug 2023 20:55:08 -0400 Subject: [PATCH 11/43] Fix hr use same sampler --- modules/txt2img.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/modules/txt2img.py b/modules/txt2img.py index 8fa389b56..edad89305 100644 --- a/modules/txt2img.py +++ b/modules/txt2img.py @@ -42,7 +42,7 @@ def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, step 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=hr_sampler_name, + hr_sampler_name=None if hr_sampler_name == 'Use same sampler' else hr_sampler_name, hr_prompt=hr_prompt, hr_negative_prompt=hr_negative_prompt, override_settings=override_settings, From c1027806936f4460cd01dcdcc93f11ea30390382 Mon Sep 17 00:00:00 2001 From: w-e-w <40751091+w-e-w@users.noreply.github.com> Date: Wed, 9 Aug 2023 13:38:53 +0900 Subject: [PATCH 12/43] extra network metadata inherit old description --- modules/ui_extra_networks_user_metadata.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/modules/ui_extra_networks_user_metadata.py b/modules/ui_extra_networks_user_metadata.py index 1cb9eb6fe..ea7e1ab20 100644 --- a/modules/ui_extra_networks_user_metadata.py +++ b/modules/ui_extra_networks_user_metadata.py @@ -40,6 +40,8 @@ class UserMetadataEditor: user_metadata = {} item['user_metadata'] = user_metadata + if len(user_metadata) == 0: + user_metadata = {'description': item.get('description', '')} return user_metadata def create_extra_default_items_in_left_column(self): From d81d3fa8cde83ce1421889ed481a69c950c0c6f6 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Wed, 9 Aug 2023 07:45:06 +0300 Subject: [PATCH 13/43] fix styles missing from the prompt in infotext when making a grid of batch of multiplie images --- modules/processing.py | 9 +++++++-- 1 file changed, 7 insertions(+), 2 deletions(-) diff --git a/modules/processing.py b/modules/processing.py index d72663072..aa72b1329 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -172,6 +172,8 @@ class StableDiffusionProcessing: self.iteration = 0 self.is_hr_pass = False self.sampler = None + self.main_prompt = None + self.main_negative_prompt = None self.prompts = None self.negative_prompts = None @@ -319,6 +321,9 @@ class StableDiffusionProcessing: self.all_prompts = [shared.prompt_styles.apply_styles_to_prompt(x, self.styles) for x in self.all_prompts] self.all_negative_prompts = [shared.prompt_styles.apply_negative_styles_to_prompt(x, self.styles) for x in self.all_negative_prompts] + self.main_prompt = self.all_prompts[0] + self.main_negative_prompt = self.all_negative_prompts[0] + def cached_params(self, required_prompts, steps, extra_network_data): """Returns parameters that invalidate the cond cache if changed""" @@ -653,8 +658,8 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter generation_params_text = ", ".join([k if k == v else f'{k}: {generation_parameters_copypaste.quote(v)}' for k, v in generation_params.items() if v is not None]) - prompt_text = p.prompt if use_main_prompt else all_prompts[index] - negative_prompt_text = f"\nNegative prompt: {all_negative_prompts[index]}" if all_negative_prompts[index] else "" + prompt_text = p.main_prompt if use_main_prompt else all_prompts[index] + negative_prompt_text = f"\nNegative prompt: {p.main_negative_prompt if use_main_prompt else all_negative_prompts[index]}" if all_negative_prompts[index] else "" return f"{prompt_text}{negative_prompt_text}\n{generation_params_text}".strip() From 0d5dc9a6e7f6362e423a06bf0e75dd5854025394 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Wed, 9 Aug 2023 08:43:31 +0300 Subject: [PATCH 14/43] rework RNG to use generators instead of generating noises beforehand --- modules/devices.py | 81 +--------------- modules/processing.py | 89 ++---------------- modules/rng.py | 171 ++++++++++++++++++++++++++++++++++ modules/sd_samplers_common.py | 24 ++--- modules/shared.py | 2 +- 5 files changed, 196 insertions(+), 171 deletions(-) create mode 100644 modules/rng.py diff --git a/modules/devices.py b/modules/devices.py index 00a00b18a..ce59dc534 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, rng_philox +from modules import errors if sys.platform == "darwin": from modules import mac_specific @@ -96,84 +96,6 @@ def cond_cast_float(input): nv_rng = None -def randn(seed, shape): - """Generate a tensor with random numbers from a normal distribution using seed. - - Uses the seed parameter to set the global torch seed; to generate more with that seed, use randn_like/randn_without_seed.""" - - from modules.shared import opts - - 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_local(seed, shape): - """Generate a tensor with random numbers from a normal distribution using seed. - - Does not change the global random number generator. You can only generate the seed's first tensor using this function.""" - - from modules.shared import opts - - if opts.randn_source == "NV": - rng = rng_philox.Generator(seed) - return torch.asarray(rng.randn(shape), device=device) - - local_device = cpu if opts.randn_source == "CPU" or device.type == 'mps' else device - local_generator = torch.Generator(local_device).manual_seed(int(seed)) - return torch.randn(shape, device=local_device, generator=local_generator).to(device) - - -def randn_like(x): - """Generate a tensor with random numbers from a normal distribution using the previously initialized genrator. - - Use either randn() or manual_seed() to initialize the generator.""" - - 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): - """Generate a tensor with random numbers from a normal distribution using the previously initialized genrator. - - Use either randn() or manual_seed() to initialize the generator.""" - - 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): - """Set up a global random number generator using the specified 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 @@ -236,3 +158,4 @@ def first_time_calculation(): x = torch.zeros((1, 1, 3, 3)).to(device, dtype) conv2d = torch.nn.Conv2d(1, 1, (3, 3)).to(device, dtype) conv2d(x) + diff --git a/modules/processing.py b/modules/processing.py index aa72b1329..2df5e8c75 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, errors +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, rng from modules.sd_hijack import model_hijack from modules.sd_samplers_common import images_tensor_to_samples, decode_first_stage, approximation_indexes from modules.shared import opts, cmd_opts, state @@ -186,6 +186,7 @@ class StableDiffusionProcessing: self.cached_c = StableDiffusionProcessing.cached_c self.uc = None self.c = None + self.rng: rng.ImageRNG = None self.user = None @@ -475,82 +476,9 @@ class Processed: return self.token_merging_ratio_hr if for_hr else self.token_merging_ratio -# from https://discuss.pytorch.org/t/help-regarding-slerp-function-for-generative-model-sampling/32475/3 -def slerp(val, low, high): - low_norm = low/torch.norm(low, dim=1, keepdim=True) - high_norm = high/torch.norm(high, dim=1, keepdim=True) - dot = (low_norm*high_norm).sum(1) - - if dot.mean() > 0.9995: - return low * val + high * (1 - val) - - omega = torch.acos(dot) - so = torch.sin(omega) - res = (torch.sin((1.0-val)*omega)/so).unsqueeze(1)*low + (torch.sin(val*omega)/so).unsqueeze(1) * high - return res - - def create_random_tensors(shape, seeds, subseeds=None, subseed_strength=0.0, seed_resize_from_h=0, seed_resize_from_w=0, p=None): - eta_noise_seed_delta = opts.eta_noise_seed_delta or 0 - xs = [] - - # if we have multiple seeds, this means we are working with batch size>1; this then - # enables the generation of additional tensors with noise that the sampler will use during its processing. - # Using those pre-generated tensors instead of simple torch.randn allows a batch with seeds [100, 101] to - # produce the same images as with two batches [100], [101]. - if p is not None and p.sampler is not None and (len(seeds) > 1 and opts.enable_batch_seeds or eta_noise_seed_delta > 0): - sampler_noises = [[] for _ in range(p.sampler.number_of_needed_noises(p))] - else: - sampler_noises = None - - for i, seed in enumerate(seeds): - 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 and subseed_strength != 0: - subseed = 0 if i >= len(subseeds) else subseeds[i] - - subnoise = devices.randn(subseed, noise_shape) - - # randn results depend on device; gpu and cpu get different results for same seed; - # the way I see it, it's better to do this on CPU, so that everyone gets same result; - # but the original script had it like this, so I do not dare change it for now because - # it will break everyone's seeds. - noise = devices.randn(seed, noise_shape) - - if subnoise is not None: - noise = slerp(subseed_strength, noise, subnoise) - - if noise_shape != shape: - x = devices.randn(seed, shape) - dx = (shape[2] - noise_shape[2]) // 2 - dy = (shape[1] - noise_shape[1]) // 2 - w = noise_shape[2] if dx >= 0 else noise_shape[2] + 2 * dx - h = noise_shape[1] if dy >= 0 else noise_shape[1] + 2 * dy - tx = 0 if dx < 0 else dx - ty = 0 if dy < 0 else dy - dx = max(-dx, 0) - dy = max(-dy, 0) - - x[:, ty:ty+h, tx:tx+w] = noise[:, dy:dy+h, dx:dx+w] - noise = x - - if sampler_noises is not None: - cnt = p.sampler.number_of_needed_noises(p) - - if eta_noise_seed_delta > 0: - devices.manual_seed(seed + eta_noise_seed_delta) - - for j in range(cnt): - sampler_noises[j].append(devices.randn_without_seed(tuple(noise_shape))) - - xs.append(noise) - - if sampler_noises is not None: - p.sampler.sampler_noises = [torch.stack(n).to(shared.device) for n in sampler_noises] - - x = torch.stack(xs).to(shared.device) - return x + g = rng.ImageRNG(shape, seeds, subseeds=subseeds, subseed_strength=subseed_strength, seed_resize_from_h=seed_resize_from_h, seed_resize_from_w=seed_resize_from_w) + return g.next() class DecodedSamples(list): @@ -769,6 +697,8 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: p.seeds = p.all_seeds[n * p.batch_size:(n + 1) * p.batch_size] p.subseeds = p.all_subseeds[n * p.batch_size:(n + 1) * p.batch_size] + p.rng = rng.ImageRNG((opt_C, p.height // opt_f, p.width // opt_f), p.seeds, subseeds=p.subseeds, subseed_strength=p.subseed_strength, seed_resize_from_h=p.seed_resize_from_h, seed_resize_from_w=p.seed_resize_from_w) + if p.scripts is not None: p.scripts.before_process_batch(p, batch_number=n, prompts=p.prompts, seeds=p.seeds, subseeds=p.subseeds) @@ -1072,7 +1002,7 @@ 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) - 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) + x = self.rng.next() samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x)) del x @@ -1160,7 +1090,8 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): samples = samples[:, :, self.truncate_y//2:samples.shape[2]-(self.truncate_y+1)//2, self.truncate_x//2:samples.shape[3]-(self.truncate_x+1)//2] - noise = create_random_tensors(samples.shape[1:], seeds=seeds, subseeds=subseeds, subseed_strength=subseed_strength, p=self) + self.rng = rng.ImageRNG(samples.shape[1:], self.seeds, subseeds=self.subseeds, subseed_strength=self.subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w) + noise = self.rng.next() # GC now before running the next img2img to prevent running out of memory devices.torch_gc() @@ -1418,7 +1349,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing): self.image_conditioning = self.img2img_image_conditioning(image, self.init_latent, image_mask) def sample(self, conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength, prompts): - 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) + x = self.rng.next() if self.initial_noise_multiplier != 1.0: self.extra_generation_params["Noise multiplier"] = self.initial_noise_multiplier diff --git a/modules/rng.py b/modules/rng.py new file mode 100644 index 000000000..2d7baea5b --- /dev/null +++ b/modules/rng.py @@ -0,0 +1,171 @@ +import torch + +from modules import devices, rng_philox, shared + + +def randn(seed, shape, generator=None): + """Generate a tensor with random numbers from a normal distribution using seed. + + Uses the seed parameter to set the global torch seed; to generate more with that seed, use randn_like/randn_without_seed.""" + + manual_seed(seed) + + if shared.opts.randn_source == "NV": + return torch.asarray((generator or nv_rng).randn(shape), device=devices.device) + + if shared.opts.randn_source == "CPU" or devices.device.type == 'mps': + return torch.randn(shape, device=devices.cpu, generator=generator).to(devices.device) + + return torch.randn(shape, device=devices.device, generator=generator) + + +def randn_local(seed, shape): + """Generate a tensor with random numbers from a normal distribution using seed. + + Does not change the global random number generator. You can only generate the seed's first tensor using this function.""" + + if shared.opts.randn_source == "NV": + rng = rng_philox.Generator(seed) + return torch.asarray(rng.randn(shape), device=devices.device) + + local_device = devices.cpu if shared.opts.randn_source == "CPU" or devices.device.type == 'mps' else devices.device + local_generator = torch.Generator(local_device).manual_seed(int(seed)) + return torch.randn(shape, device=local_device, generator=local_generator).to(devices.device) + + +def randn_like(x): + """Generate a tensor with random numbers from a normal distribution using the previously initialized genrator. + + Use either randn() or manual_seed() to initialize the generator.""" + + if shared.opts.randn_source == "NV": + return torch.asarray(nv_rng.randn(x.shape), device=x.device, dtype=x.dtype) + + if shared.opts.randn_source == "CPU" or x.device.type == 'mps': + return torch.randn_like(x, device=devices.cpu).to(x.device) + + return torch.randn_like(x) + + +def randn_without_seed(shape, generator=None): + """Generate a tensor with random numbers from a normal distribution using the previously initialized genrator. + + Use either randn() or manual_seed() to initialize the generator.""" + + if shared.opts.randn_source == "NV": + return torch.asarray((generator or nv_rng).randn(shape), device=devices.device) + + if shared.opts.randn_source == "CPU" or devices.device.type == 'mps': + return torch.randn(shape, device=devices.cpu, generator=generator).to(devices.device) + + return torch.randn(shape, device=devices.device, generator=generator) + + +def manual_seed(seed): + """Set up a global random number generator using the specified 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 create_generator(seed): + if shared.opts.randn_source == "NV": + return rng_philox.Generator(seed) + + device = devices.cpu if shared.opts.randn_source == "CPU" or devices.device.type == 'mps' else devices.device + generator = torch.Generator(device).manual_seed(int(seed)) + return generator + + +# from https://discuss.pytorch.org/t/help-regarding-slerp-function-for-generative-model-sampling/32475/3 +def slerp(val, low, high): + low_norm = low/torch.norm(low, dim=1, keepdim=True) + high_norm = high/torch.norm(high, dim=1, keepdim=True) + dot = (low_norm*high_norm).sum(1) + + if dot.mean() > 0.9995: + return low * val + high * (1 - val) + + omega = torch.acos(dot) + so = torch.sin(omega) + res = (torch.sin((1.0-val)*omega)/so).unsqueeze(1)*low + (torch.sin(val*omega)/so).unsqueeze(1) * high + return res + + +class ImageRNG: + def __init__(self, shape, seeds, subseeds=None, subseed_strength=0.0, seed_resize_from_h=0, seed_resize_from_w=0): + self.shape = shape + self.seeds = seeds + self.subseeds = subseeds + self.subseed_strength = subseed_strength + self.seed_resize_from_h = seed_resize_from_h + self.seed_resize_from_w = seed_resize_from_w + + self.generators = [create_generator(seed) for seed in seeds] + + self.is_first = True + + def first(self): + noise_shape = self.shape if self.seed_resize_from_h <= 0 or self.seed_resize_from_w <= 0 else (self.shape[0], self.seed_resize_from_h // 8, self.seed_resize_from_w // 8) + + xs = [] + + for i, (seed, generator) in enumerate(zip(self.seeds, self.generators)): + subnoise = None + if self.subseeds is not None and self.subseed_strength != 0: + subseed = 0 if i >= len(self.subseeds) else self.subseeds[i] + subnoise = randn(subseed, noise_shape) + + if noise_shape != self.shape: + noise = randn(seed, noise_shape) + else: + noise = randn(seed, self.shape, generator=generator) + + if subnoise is not None: + noise = slerp(self.subseed_strength, noise, subnoise) + + if noise_shape != self.shape: + x = randn(seed, self.shape, generator=generator) + dx = (self.shape[2] - noise_shape[2]) // 2 + dy = (self.shape[1] - noise_shape[1]) // 2 + w = noise_shape[2] if dx >= 0 else noise_shape[2] + 2 * dx + h = noise_shape[1] if dy >= 0 else noise_shape[1] + 2 * dy + tx = 0 if dx < 0 else dx + ty = 0 if dy < 0 else dy + dx = max(-dx, 0) + dy = max(-dy, 0) + + x[:, ty:ty + h, tx:tx + w] = noise[:, dy:dy + h, dx:dx + w] + noise = x + + xs.append(noise) + + eta_noise_seed_delta = shared.opts.eta_noise_seed_delta or 0 + if eta_noise_seed_delta: + self.generators = [create_generator(seed + eta_noise_seed_delta) for seed in self.seeds] + + return torch.stack(xs).to(shared.device) + + def next(self): + if self.is_first: + self.is_first = False + return self.first() + + xs = [] + for generator in self.generators: + x = randn_without_seed(self.shape, generator=generator) + xs.append(x) + + return torch.stack(xs).to(shared.device) + + +devices.randn = randn +devices.randn_local = randn_local +devices.randn_like = randn_like +devices.randn_without_seed = randn_without_seed +devices.manual_seed = manual_seed diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py index adda963bc..97bc08041 100644 --- a/modules/sd_samplers_common.py +++ b/modules/sd_samplers_common.py @@ -1,5 +1,5 @@ import inspect -from collections import namedtuple, deque +from collections import namedtuple import numpy as np import torch from PIL import Image @@ -132,10 +132,15 @@ replace_torchsde_browinan() class TorchHijack: - def __init__(self, sampler_noises): - # Using a deque to efficiently receive the sampler_noises in the same order as the previous index-based - # implementation. - self.sampler_noises = deque(sampler_noises) + """This is here to replace torch.randn_like of k-diffusion. + + k-diffusion has random_sampler argument for most samplers, but not for all, so + this is needed to properly replace every use of torch.randn_like. + + We need to replace to make images generated in batches to be same as images generated individually.""" + + def __init__(self, p): + self.rng = p.rng def __getattr__(self, item): if item == 'randn_like': @@ -147,12 +152,7 @@ class TorchHijack: raise AttributeError(f"'{type(self).__name__}' object has no attribute '{item}'") def randn_like(self, x): - if self.sampler_noises: - noise = self.sampler_noises.popleft() - if noise.shape == x.shape: - return noise - - return devices.randn_like(x) + return self.rng.next() class Sampler: @@ -215,7 +215,7 @@ class Sampler: self.eta = p.eta if p.eta is not None else getattr(opts, self.eta_option_field, 0.0) self.s_min_uncond = getattr(p, 's_min_uncond', 0.0) - k_diffusion.sampling.torch = TorchHijack(self.sampler_noises if self.sampler_noises is not None else []) + k_diffusion.sampling.torch = TorchHijack(p) extra_params_kwargs = {} for param_name in self.extra_params: diff --git a/modules/shared.py b/modules/shared.py index e34847cef..e9b980a43 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -16,7 +16,7 @@ import modules.interrogate import modules.memmon import modules.styles import modules.devices as devices -from modules import localization, script_loading, errors, ui_components, shared_items, cmd_args +from modules import localization, script_loading, errors, ui_components, shared_items, cmd_args, rng # noqa: F401 from modules.paths_internal import models_path, script_path, data_path, sd_configs_path, sd_default_config, sd_model_file, default_sd_model_file, extensions_dir, extensions_builtin_dir # noqa: F401 from ldm.models.diffusion.ddpm import LatentDiffusion from typing import Optional From a6f840b4dc09bb876060dc2487742fef6dd49feb Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Wed, 9 Aug 2023 08:47:52 +0300 Subject: [PATCH 15/43] Split history: mv modules/shared.py modules/shared_options.py --- modules/{shared.py => shared_options.py} | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename modules/{shared.py => shared_options.py} (100%) diff --git a/modules/shared.py b/modules/shared_options.py similarity index 100% rename from modules/shared.py rename to modules/shared_options.py From da0712ee7d6e9353e6d2d1828d6217bd122fbd51 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Wed, 9 Aug 2023 08:47:53 +0300 Subject: [PATCH 16/43] Split history: mv modules/shared.py temp --- modules/shared.py => temp | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename modules/shared.py => temp (100%) diff --git a/modules/shared.py b/temp similarity index 100% rename from modules/shared.py rename to temp From 7d81ecbea6b558addd356d49c56891d04bc91fd4 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Wed, 9 Aug 2023 08:47:53 +0300 Subject: [PATCH 17/43] Split history: mv temp modules/shared.py --- temp => modules/shared.py | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename temp => modules/shared.py (100%) diff --git a/temp b/modules/shared.py similarity index 100% rename from temp rename to modules/shared.py From 386245a26427a64f364f66f6fecd03b3bccfd7f3 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Wed, 9 Aug 2023 10:25:35 +0300 Subject: [PATCH 18/43] split shared.py into multiple files; should resolve all circular reference import errors related to shared.py --- modules/devices.py | 10 +- modules/extensions.py | 4 +- modules/generation_parameters_copypaste.py | 3 +- modules/images.py | 28 +- modules/localization.py | 3 +- modules/mac_specific.py | 4 +- modules/options.py | 236 +++++ modules/rng.py | 3 +- modules/sd_models.py | 9 +- modules/sd_models_config.py | 3 +- modules/sd_vae.py | 5 +- modules/shared.py | 967 +-------------------- modules/shared_cmd_options.py | 18 + modules/shared_gradio_themes.py | 66 ++ modules/shared_init.py | 51 ++ modules/shared_items.py | 49 ++ modules/shared_options.py | 690 +-------------- modules/shared_state.py | 159 ++++ modules/shared_total_tqdm.py | 37 + modules/sysinfo.py | 7 +- modules/ui.py | 6 +- modules/ui_common.py | 4 +- modules/util.py | 58 ++ webui.py | 11 +- 24 files changed, 764 insertions(+), 1667 deletions(-) create mode 100644 modules/options.py create mode 100644 modules/shared_cmd_options.py create mode 100644 modules/shared_gradio_themes.py create mode 100644 modules/shared_init.py create mode 100644 modules/shared_state.py create mode 100644 modules/shared_total_tqdm.py create mode 100644 modules/util.py diff --git a/modules/devices.py b/modules/devices.py index ce59dc534..c01f06024 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, shared if sys.platform == "darwin": from modules import mac_specific @@ -17,8 +17,6 @@ def has_mps() -> bool: def get_cuda_device_string(): - from modules import shared - if shared.cmd_opts.device_id is not None: return f"cuda:{shared.cmd_opts.device_id}" @@ -40,8 +38,6 @@ def get_optimal_device(): def get_device_for(task): - from modules import shared - if task in shared.cmd_opts.use_cpu: return cpu @@ -97,8 +93,6 @@ nv_rng = None def autocast(disable=False): - from modules import shared - if disable: return contextlib.nullcontext() @@ -117,8 +111,6 @@ class NansException(Exception): def test_for_nans(x, where): - from modules import shared - if shared.cmd_opts.disable_nan_check: return diff --git a/modules/extensions.py b/modules/extensions.py index e4633af40..bf9a1878f 100644 --- a/modules/extensions.py +++ b/modules/extensions.py @@ -1,7 +1,7 @@ import os import threading -from modules import shared, errors, cache +from modules import shared, errors, cache, scripts from modules.gitpython_hack import Repo from modules.paths_internal import extensions_dir, extensions_builtin_dir, script_path # noqa: F401 @@ -90,8 +90,6 @@ class Extension: self.have_info_from_repo = True def list_files(self, subdir, extension): - from modules import scripts - dirpath = os.path.join(self.path, subdir) if not os.path.isdir(dirpath): return [] diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 5758e6f30..d932c67d5 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -6,7 +6,7 @@ import re import gradio as gr from modules.paths import data_path -from modules import shared, ui_tempdir, script_callbacks +from modules import shared, ui_tempdir, script_callbacks, processing from PIL import Image re_param_code = r'\s*([\w ]+):\s*("(?:\\"[^,]|\\"|\\|[^\"])+"|[^,]*)(?:,|$)' @@ -198,7 +198,6 @@ def restore_old_hires_fix_params(res): height = int(res.get("Size-2", 512)) if firstpass_width == 0 or firstpass_height == 0: - from modules import processing firstpass_width, firstpass_height = processing.old_hires_fix_first_pass_dimensions(width, height) res['Size-1'] = firstpass_width diff --git a/modules/images.py b/modules/images.py index ba3c43a45..019c1d600 100644 --- a/modules/images.py +++ b/modules/images.py @@ -21,8 +21,6 @@ from modules import sd_samplers, shared, script_callbacks, errors from modules.paths_internal import roboto_ttf_file from modules.shared import opts -import modules.sd_vae as sd_vae - LANCZOS = (Image.Resampling.LANCZOS if hasattr(Image, 'Resampling') else Image.LANCZOS) @@ -342,16 +340,6 @@ def sanitize_filename_part(text, replace_spaces=True): class FilenameGenerator: - def get_vae_filename(self): #get the name of the VAE file. - if sd_vae.loaded_vae_file is None: - return "NoneType" - file_name = os.path.basename(sd_vae.loaded_vae_file) - split_file_name = file_name.split('.') - if len(split_file_name) > 1 and split_file_name[0] == '': - return split_file_name[1] # if the first character of the filename is "." then [1] is obtained. - else: - return split_file_name[0] - replacements = { 'seed': lambda self: self.seed if self.seed is not None else '', 'seed_first': lambda self: self.seed if self.p.batch_size == 1 else self.p.all_seeds[0], @@ -391,6 +379,22 @@ class FilenameGenerator: self.image = image self.zip = zip + def get_vae_filename(self): + """Get the name of the VAE file.""" + + import modules.sd_vae as sd_vae + + if sd_vae.loaded_vae_file is None: + return "NoneType" + + file_name = os.path.basename(sd_vae.loaded_vae_file) + split_file_name = file_name.split('.') + if len(split_file_name) > 1 and split_file_name[0] == '': + return split_file_name[1] # if the first character of the filename is "." then [1] is obtained. + else: + return split_file_name[0] + + def hasprompt(self, *args): lower = self.prompt.lower() if self.p is None or self.prompt is None: diff --git a/modules/localization.py b/modules/localization.py index e8f585dab..c13202885 100644 --- a/modules/localization.py +++ b/modules/localization.py @@ -1,7 +1,7 @@ import json import os -from modules import errors +from modules import errors, scripts localizations = {} @@ -16,7 +16,6 @@ def list_localizations(dirname): localizations[fn] = os.path.join(dirname, file) - from modules import scripts for file in scripts.list_scripts("localizations", ".json"): fn, ext = os.path.splitext(file.filename) localizations[fn] = file.path diff --git a/modules/mac_specific.py b/modules/mac_specific.py index 9ceb43bae..bce527ccc 100644 --- a/modules/mac_specific.py +++ b/modules/mac_specific.py @@ -4,6 +4,7 @@ import torch import platform from modules.sd_hijack_utils import CondFunc from packaging import version +from modules import shared log = logging.getLogger(__name__) @@ -30,8 +31,7 @@ has_mps = check_for_mps() def torch_mps_gc() -> None: try: - from modules.shared import state - if state.current_latent is not None: + if shared.state.current_latent is not None: log.debug("`current_latent` is set, skipping MPS garbage collection") return from torch.mps import empty_cache diff --git a/modules/options.py b/modules/options.py new file mode 100644 index 000000000..59cb75ecf --- /dev/null +++ b/modules/options.py @@ -0,0 +1,236 @@ +import json +import sys + +import gradio as gr + +from modules import errors +from modules.shared_cmd_options import cmd_opts + + +class OptionInfo: + def __init__(self, default=None, label="", component=None, component_args=None, onchange=None, section=None, refresh=None, comment_before='', comment_after=''): + self.default = default + self.label = label + self.component = component + self.component_args = component_args + self.onchange = onchange + self.section = section + self.refresh = refresh + self.do_not_save = False + + self.comment_before = comment_before + """HTML text that will be added after label in UI""" + + self.comment_after = comment_after + """HTML text that will be added before label in UI""" + + def link(self, label, url): + self.comment_before += f"[{label}]" + return self + + def js(self, label, js_func): + self.comment_before += f"[{label}]" + return self + + def info(self, info): + self.comment_after += f"({info})" + return self + + def html(self, html): + self.comment_after += html + return self + + def needs_restart(self): + self.comment_after += " (requires restart)" + return self + + def needs_reload_ui(self): + self.comment_after += " (requires Reload UI)" + return self + + +class OptionHTML(OptionInfo): + def __init__(self, text): + super().__init__(str(text).strip(), label='', component=lambda **kwargs: gr.HTML(elem_classes="settings-info", **kwargs)) + + self.do_not_save = True + + +def options_section(section_identifier, options_dict): + for v in options_dict.values(): + v.section = section_identifier + + return options_dict + + +options_builtin_fields = {"data_labels", "data", "restricted_opts", "typemap"} + + +class Options: + typemap = {int: float} + + def __init__(self, data_labels, restricted_opts): + self.data_labels = data_labels + self.data = {k: v.default for k, v in self.data_labels.items()} + self.restricted_opts = restricted_opts + + def __setattr__(self, key, value): + if key in options_builtin_fields: + return super(Options, self).__setattr__(key, value) + + if self.data is not None: + if key in self.data or key in self.data_labels: + assert not cmd_opts.freeze_settings, "changing settings is disabled" + + info = self.data_labels.get(key, None) + if info.do_not_save: + return + + comp_args = info.component_args if info else None + if isinstance(comp_args, dict) and comp_args.get('visible', True) is False: + raise RuntimeError(f"not possible to set {key} because it is restricted") + + if cmd_opts.hide_ui_dir_config and key in self.restricted_opts: + raise RuntimeError(f"not possible to set {key} because it is restricted") + + self.data[key] = value + return + + return super(Options, self).__setattr__(key, value) + + def __getattr__(self, item): + if item in options_builtin_fields: + return super(Options, self).__getattribute__(item) + + if self.data is not None: + if item in self.data: + return self.data[item] + + if item in self.data_labels: + return self.data_labels[item].default + + return super(Options, self).__getattribute__(item) + + def set(self, key, value): + """sets an option and calls its onchange callback, returning True if the option changed and False otherwise""" + + oldval = self.data.get(key, None) + if oldval == value: + return False + + if self.data_labels[key].do_not_save: + return False + + try: + setattr(self, key, value) + except RuntimeError: + return False + + if self.data_labels[key].onchange is not None: + try: + self.data_labels[key].onchange() + except Exception as e: + errors.display(e, f"changing setting {key} to {value}") + setattr(self, key, oldval) + return False + + return True + + def get_default(self, key): + """returns the default value for the key""" + + data_label = self.data_labels.get(key) + if data_label is None: + return None + + return data_label.default + + def save(self, filename): + assert not cmd_opts.freeze_settings, "saving settings is disabled" + + with open(filename, "w", encoding="utf8") as file: + json.dump(self.data, file, indent=4) + + def same_type(self, x, y): + if x is None or y is None: + return True + + type_x = self.typemap.get(type(x), type(x)) + type_y = self.typemap.get(type(y), type(y)) + + return type_x == type_y + + def load(self, filename): + with open(filename, "r", encoding="utf8") as file: + self.data = json.load(file) + + # 1.6.0 VAE defaults + if self.data.get('sd_vae_as_default') is not None and self.data.get('sd_vae_overrides_per_model_preferences') is None: + self.data['sd_vae_overrides_per_model_preferences'] = not self.data.get('sd_vae_as_default') + + # 1.1.1 quicksettings list migration + if self.data.get('quicksettings') is not None and self.data.get('quicksettings_list') is None: + self.data['quicksettings_list'] = [i.strip() for i in self.data.get('quicksettings').split(',')] + + # 1.4.0 ui_reorder + if isinstance(self.data.get('ui_reorder'), str) and self.data.get('ui_reorder') and "ui_reorder_list" not in self.data: + self.data['ui_reorder_list'] = [i.strip() for i in self.data.get('ui_reorder').split(',')] + + bad_settings = 0 + for k, v in self.data.items(): + info = self.data_labels.get(k, None) + if info is not None and not self.same_type(info.default, v): + print(f"Warning: bad setting value: {k}: {v} ({type(v).__name__}; expected {type(info.default).__name__})", file=sys.stderr) + bad_settings += 1 + + if bad_settings > 0: + print(f"The program is likely to not work with bad settings.\nSettings file: {filename}\nEither fix the file, or delete it and restart.", file=sys.stderr) + + def onchange(self, key, func, call=True): + item = self.data_labels.get(key) + item.onchange = func + + if call: + func() + + def dumpjson(self): + d = {k: self.data.get(k, v.default) for k, v in self.data_labels.items()} + d["_comments_before"] = {k: v.comment_before for k, v in self.data_labels.items() if v.comment_before is not None} + d["_comments_after"] = {k: v.comment_after for k, v in self.data_labels.items() if v.comment_after is not None} + return json.dumps(d) + + def add_option(self, key, info): + self.data_labels[key] = info + + def reorder(self): + """reorder settings so that all items related to section always go together""" + + section_ids = {} + settings_items = self.data_labels.items() + for _, item in settings_items: + if item.section not in section_ids: + section_ids[item.section] = len(section_ids) + + self.data_labels = dict(sorted(settings_items, key=lambda x: section_ids[x[1].section])) + + def cast_value(self, key, value): + """casts an arbitrary to the same type as this setting's value with key + Example: cast_value("eta_noise_seed_delta", "12") -> returns 12 (an int rather than str) + """ + + if value is None: + return None + + default_value = self.data_labels[key].default + if default_value is None: + default_value = getattr(self, key, None) + if default_value is None: + return None + + expected_type = type(default_value) + if expected_type == bool and value == "False": + value = False + else: + value = expected_type(value) + + return value diff --git a/modules/rng.py b/modules/rng.py index 2d7baea5b..f927a318c 100644 --- a/modules/rng.py +++ b/modules/rng.py @@ -63,9 +63,8 @@ def randn_without_seed(shape, generator=None): def manual_seed(seed): """Set up a global random number generator using the specified seed.""" - from modules.shared import opts - if opts.randn_source == "NV": + if shared.opts.randn_source == "NV": global nv_rng nv_rng = rng_philox.Generator(seed) return diff --git a/modules/sd_models.py b/modules/sd_models.py index 53c1df54c..88a098992 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -14,7 +14,7 @@ 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, cache +from modules import paths, shared, modelloader, devices, script_callbacks, sd_vae, sd_disable_initialization, errors, hashes, sd_models_config, sd_unet, sd_models_xl, cache, extra_networks, processing, lowvram, sd_hijack from modules.timer import Timer import tomesd @@ -473,7 +473,6 @@ model_data = SdModelData() def get_empty_cond(sd_model): - from modules import extra_networks, processing p = processing.StableDiffusionProcessingTxt2Img() extra_networks.activate(p, {}) @@ -486,8 +485,6 @@ def get_empty_cond(sd_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: @@ -497,8 +494,6 @@ def send_model_to_cpu(m): 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: @@ -642,7 +637,6 @@ def reuse_model_from_already_loaded(sd_model, checkpoint_info, timer): def reload_model_weights(sd_model=None, info=None): - from modules import devices, sd_hijack checkpoint_info = info or select_checkpoint() timer = Timer() @@ -705,7 +699,6 @@ def reload_model_weights(sd_model=None, info=None): def unload_model_weights(sd_model=None, info=None): - from modules import devices, sd_hijack timer = Timer() if model_data.sd_model: diff --git a/modules/sd_models_config.py b/modules/sd_models_config.py index 8266fa397..08dd03f19 100644 --- a/modules/sd_models_config.py +++ b/modules/sd_models_config.py @@ -2,7 +2,7 @@ import os import torch -from modules import shared, paths, sd_disable_initialization +from modules import shared, paths, sd_disable_initialization, devices sd_configs_path = shared.sd_configs_path sd_repo_configs_path = os.path.join(paths.paths['Stable Diffusion'], "configs", "stable-diffusion") @@ -29,7 +29,6 @@ def is_using_v_parameterization_for_sd2(state_dict): """ import ldm.modules.diffusionmodules.openaimodel - from modules import devices device = devices.cpu diff --git a/modules/sd_vae.py b/modules/sd_vae.py index 38bcb8402..5ac1ac31f 100644 --- a/modules/sd_vae.py +++ b/modules/sd_vae.py @@ -2,7 +2,8 @@ import os import collections from dataclasses import dataclass -from modules import paths, shared, devices, script_callbacks, sd_models, extra_networks +from modules import paths, shared, devices, script_callbacks, sd_models, extra_networks, lowvram, sd_hijack + import glob from copy import deepcopy @@ -231,8 +232,6 @@ unspecified = object() def reload_vae_weights(sd_model=None, vae_file=unspecified): - from modules import lowvram, devices, sd_hijack - if not sd_model: sd_model = shared.sd_model diff --git a/modules/shared.py b/modules/shared.py index e9b980a43..8ba72f495 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -1,843 +1,51 @@ -import datetime -import json -import os -import re import sys -import threading -import time -import logging import gradio as gr -import torch -import tqdm -import launch -import modules.interrogate -import modules.memmon -import modules.styles -import modules.devices as devices -from modules import localization, script_loading, errors, ui_components, shared_items, cmd_args, rng # noqa: F401 +from modules import shared_cmd_options, shared_gradio_themes, options, shared_items from modules.paths_internal import models_path, script_path, data_path, sd_configs_path, sd_default_config, sd_model_file, default_sd_model_file, extensions_dir, extensions_builtin_dir # noqa: F401 from ldm.models.diffusion.ddpm import LatentDiffusion -from typing import Optional +from modules import util -log = logging.getLogger(__name__) - -demo = None - -parser = cmd_args.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: - cmd_opts = parser.parse_args() -else: - cmd_opts, _ = parser.parse_known_args() - - -restricted_opts = { - "samples_filename_pattern", - "directories_filename_pattern", - "outdir_samples", - "outdir_txt2img_samples", - "outdir_img2img_samples", - "outdir_extras_samples", - "outdir_grids", - "outdir_txt2img_grids", - "outdir_save", - "outdir_init_images" -} - -# https://huggingface.co/datasets/freddyaboulton/gradio-theme-subdomains/resolve/main/subdomains.json -gradio_hf_hub_themes = [ - "gradio/base", - "gradio/glass", - "gradio/monochrome", - "gradio/seafoam", - "gradio/soft", - "gradio/dracula_test", - "abidlabs/dracula_test", - "abidlabs/Lime", - "abidlabs/pakistan", - "Ama434/neutral-barlow", - "dawood/microsoft_windows", - "finlaymacklon/smooth_slate", - "Franklisi/darkmode", - "freddyaboulton/dracula_revamped", - "freddyaboulton/test-blue", - "gstaff/xkcd", - "Insuz/Mocha", - "Insuz/SimpleIndigo", - "JohnSmith9982/small_and_pretty", - "nota-ai/theme", - "nuttea/Softblue", - "ParityError/Anime", - "reilnuud/polite", - "remilia/Ghostly", - "rottenlittlecreature/Moon_Goblin", - "step-3-profit/Midnight-Deep", - "Taithrah/Minimal", - "ysharma/huggingface", - "ysharma/steampunk" -] - - -cmd_opts.disable_extension_access = (cmd_opts.share or cmd_opts.listen or cmd_opts.server_name) and not cmd_opts.enable_insecure_extension_access - -devices.device, devices.device_interrogate, devices.device_gfpgan, devices.device_esrgan, devices.device_codeformer = \ - (devices.cpu if any(y in cmd_opts.use_cpu for y in [x, 'all']) else devices.get_optimal_device() for x in ['sd', 'interrogate', 'gfpgan', 'esrgan', 'codeformer']) - -devices.dtype = torch.float32 if cmd_opts.no_half else torch.float16 -devices.dtype_vae = torch.float32 if cmd_opts.no_half or cmd_opts.no_half_vae else torch.float16 - -device = devices.device -weight_load_location = None if cmd_opts.lowram else "cpu" +cmd_opts = shared_cmd_options.cmd_opts +parser = shared_cmd_options.parser batch_cond_uncond = cmd_opts.always_batch_cond_uncond or not (cmd_opts.lowvram or cmd_opts.medvram) parallel_processing_allowed = not cmd_opts.lowvram and not cmd_opts.medvram -xformers_available = False +styles_filename = cmd_opts.styles_file config_filename = cmd_opts.ui_settings_file +hide_dirs = {"visible": not cmd_opts.hide_ui_dir_config} + +demo = None + +device = None + +weight_load_location = None + +xformers_available = False -os.makedirs(cmd_opts.hypernetwork_dir, exist_ok=True) hypernetworks = {} + loaded_hypernetworks = [] +state = None -def reload_hypernetworks(): - from modules.hypernetworks import hypernetwork - global hypernetworks +prompt_styles = None - hypernetworks = hypernetwork.list_hypernetworks(cmd_opts.hypernetwork_dir) - - -class State: - skipped = False - interrupted = False - job = "" - job_no = 0 - job_count = 0 - processing_has_refined_job_count = False - job_timestamp = '0' - sampling_step = 0 - sampling_steps = 0 - current_latent = None - current_image = None - current_image_sampling_step = 0 - id_live_preview = 0 - textinfo = None - time_start = None - server_start = None - _server_command_signal = threading.Event() - _server_command: Optional[str] = None - - @property - def need_restart(self) -> bool: - # Compatibility getter for need_restart. - return self.server_command == "restart" - - @need_restart.setter - def need_restart(self, value: bool) -> None: - # Compatibility setter for need_restart. - if value: - self.server_command = "restart" - - @property - def server_command(self): - return self._server_command - - @server_command.setter - def server_command(self, value: Optional[str]) -> None: - """ - Set the server command to `value` and signal that it's been set. - """ - self._server_command = value - self._server_command_signal.set() - - def wait_for_server_command(self, timeout: Optional[float] = None) -> Optional[str]: - """ - Wait for server command to get set; return and clear the value and signal. - """ - if self._server_command_signal.wait(timeout): - self._server_command_signal.clear() - req = self._server_command - self._server_command = None - return req - return None - - def request_restart(self) -> None: - self.interrupt() - self.server_command = "restart" - log.info("Received restart request") - - def skip(self): - self.skipped = True - log.info("Received skip request") - - def interrupt(self): - self.interrupted = True - log.info("Received interrupt request") - - def nextjob(self): - if opts.live_previews_enable and opts.show_progress_every_n_steps == -1: - self.do_set_current_image() - - self.job_no += 1 - self.sampling_step = 0 - self.current_image_sampling_step = 0 - - def dict(self): - obj = { - "skipped": self.skipped, - "interrupted": self.interrupted, - "job": self.job, - "job_count": self.job_count, - "job_timestamp": self.job_timestamp, - "job_no": self.job_no, - "sampling_step": self.sampling_step, - "sampling_steps": self.sampling_steps, - } - - return obj - - def begin(self, job: str = "(unknown)"): - self.sampling_step = 0 - self.job_count = -1 - self.processing_has_refined_job_count = False - self.job_no = 0 - self.job_timestamp = datetime.datetime.now().strftime("%Y%m%d%H%M%S") - self.current_latent = None - self.current_image = None - self.current_image_sampling_step = 0 - self.id_live_preview = 0 - self.skipped = False - self.interrupted = False - self.textinfo = None - self.time_start = time.time() - self.job = job - devices.torch_gc() - log.info("Starting job %s", job) - - def end(self): - duration = time.time() - self.time_start - log.info("Ending job %s (%.2f seconds)", self.job, duration) - self.job = "" - self.job_count = 0 - - devices.torch_gc() - - def set_current_image(self): - """sets self.current_image from self.current_latent if enough sampling steps have been made after the last call to this""" - if not parallel_processing_allowed: - return - - if self.sampling_step - self.current_image_sampling_step >= opts.show_progress_every_n_steps and opts.live_previews_enable and opts.show_progress_every_n_steps != -1: - self.do_set_current_image() - - def do_set_current_image(self): - if self.current_latent is None: - return - - import modules.sd_samplers - - 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 - self.id_live_preview += 1 - - -state = State() -state.server_start = time.time() - -styles_filename = cmd_opts.styles_file -prompt_styles = modules.styles.StyleDatabase(styles_filename) - -interrogator = modules.interrogate.InterrogateModels("interrogate") +interrogator = None face_restorers = [] +options_templates = None +opts = None -class OptionInfo: - def __init__(self, default=None, label="", component=None, component_args=None, onchange=None, section=None, refresh=None, comment_before='', comment_after=''): - self.default = default - self.label = label - self.component = component - self.component_args = component_args - self.onchange = onchange - self.section = section - self.refresh = refresh - self.do_not_save = False - - self.comment_before = comment_before - """HTML text that will be added after label in UI""" - - self.comment_after = comment_after - """HTML text that will be added before label in UI""" - - def link(self, label, url): - self.comment_before += f"[{label}]" - return self - - def js(self, label, js_func): - self.comment_before += f"[{label}]" - return self - - def info(self, info): - self.comment_after += f"({info})" - return self - - def html(self, html): - self.comment_after += html - return self - - def needs_restart(self): - self.comment_after += " (requires restart)" - return self - - def needs_reload_ui(self): - self.comment_after += " (requires Reload UI)" - return self - - -class OptionHTML(OptionInfo): - def __init__(self, text): - super().__init__(str(text).strip(), label='', component=lambda **kwargs: gr.HTML(elem_classes="settings-info", **kwargs)) - - self.do_not_save = True - - -def options_section(section_identifier, options_dict): - for v in options_dict.values(): - v.section = section_identifier - - return options_dict - - -def list_checkpoint_tiles(): - import modules.sd_models - return modules.sd_models.checkpoint_tiles() - - -def refresh_checkpoints(): - import modules.sd_models - return modules.sd_models.list_models() - - -def list_samplers(): - import modules.sd_samplers - return modules.sd_samplers.all_samplers - - -hide_dirs = {"visible": not cmd_opts.hide_ui_dir_config} -tab_names = [] - -options_templates = {} - -options_templates.update(options_section(('saving-images', "Saving images/grids"), { - "samples_save": OptionInfo(True, "Always save all generated images"), - "samples_format": OptionInfo('png', 'File format for images'), - "samples_filename_pattern": OptionInfo("", "Images filename pattern", component_args=hide_dirs).link("wiki", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Custom-Images-Filename-Name-and-Subdirectory"), - "save_images_add_number": OptionInfo(True, "Add number to filename when saving", component_args=hide_dirs), - - "grid_save": OptionInfo(True, "Always save all generated image grids"), - "grid_format": OptionInfo('png', 'File format for grids'), - "grid_extended_filename": OptionInfo(False, "Add extended info (seed, prompt) to filename when saving grid"), - "grid_only_if_multiple": OptionInfo(True, "Do not save grids consisting of one picture"), - "grid_prevent_empty_spots": OptionInfo(False, "Prevent empty spots in grid (when set to autodetect)"), - "grid_zip_filename_pattern": OptionInfo("", "Archive filename pattern", component_args=hide_dirs).link("wiki", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Custom-Images-Filename-Name-and-Subdirectory"), - "n_rows": OptionInfo(-1, "Grid row count; use -1 for autodetect and 0 for it to be same as batch size", gr.Slider, {"minimum": -1, "maximum": 16, "step": 1}), - "font": OptionInfo("", "Font for image grids that have text"), - "grid_text_active_color": OptionInfo("#000000", "Text color for image grids", ui_components.FormColorPicker, {}), - "grid_text_inactive_color": OptionInfo("#999999", "Inactive text color for image grids", ui_components.FormColorPicker, {}), - "grid_background_color": OptionInfo("#ffffff", "Background color for image grids", ui_components.FormColorPicker, {}), - - "enable_pnginfo": OptionInfo(True, "Save text information about generation parameters as chunks to png files"), - "save_txt": OptionInfo(False, "Create a text file next to every image with generation parameters."), - "save_images_before_face_restoration": OptionInfo(False, "Save a copy of image before doing face restoration."), - "save_images_before_highres_fix": OptionInfo(False, "Save a copy of image before applying highres fix."), - "save_images_before_color_correction": OptionInfo(False, "Save a copy of image before applying color correction to img2img results"), - "save_mask": OptionInfo(False, "For inpainting, save a copy of the greyscale mask"), - "save_mask_composite": OptionInfo(False, "For inpainting, save a masked composite"), - "jpeg_quality": OptionInfo(80, "Quality for saved jpeg images", gr.Slider, {"minimum": 1, "maximum": 100, "step": 1}), - "webp_lossless": OptionInfo(False, "Use lossless compression for webp images"), - "export_for_4chan": OptionInfo(True, "Save copy of large images as JPG").info("if the file size is above the limit, or either width or height are above the limit"), - "img_downscale_threshold": OptionInfo(4.0, "File size limit for the above option, MB", gr.Number), - "target_side_length": OptionInfo(4000, "Width/height limit for the above option, in pixels", gr.Number), - "img_max_size_mp": OptionInfo(200, "Maximum image size", gr.Number).info("in megapixels"), - - "use_original_name_batch": OptionInfo(True, "Use original name for output filename during batch process in extras tab"), - "use_upscaler_name_as_suffix": OptionInfo(False, "Use upscaler name as filename suffix in the extras tab"), - "save_selected_only": OptionInfo(True, "When using 'Save' button, only save a single selected image"), - "save_init_img": OptionInfo(False, "Save init images when using img2img"), - - "temp_dir": OptionInfo("", "Directory for temporary images; leave empty for default"), - "clean_temp_dir_at_start": OptionInfo(False, "Cleanup non-default temporary directory when starting webui"), - - "save_incomplete_images": OptionInfo(False, "Save incomplete images").info("save images that has been interrupted in mid-generation; even if not saved, they will still show up in webui output."), -})) - -options_templates.update(options_section(('saving-paths', "Paths for saving"), { - "outdir_samples": OptionInfo("", "Output directory for images; if empty, defaults to three directories below", component_args=hide_dirs), - "outdir_txt2img_samples": OptionInfo("outputs/txt2img-images", 'Output directory for txt2img images', component_args=hide_dirs), - "outdir_img2img_samples": OptionInfo("outputs/img2img-images", 'Output directory for img2img images', component_args=hide_dirs), - "outdir_extras_samples": OptionInfo("outputs/extras-images", 'Output directory for images from extras tab', component_args=hide_dirs), - "outdir_grids": OptionInfo("", "Output directory for grids; if empty, defaults to two directories below", component_args=hide_dirs), - "outdir_txt2img_grids": OptionInfo("outputs/txt2img-grids", 'Output directory for txt2img grids', component_args=hide_dirs), - "outdir_img2img_grids": OptionInfo("outputs/img2img-grids", 'Output directory for img2img grids', component_args=hide_dirs), - "outdir_save": OptionInfo("log/images", "Directory for saving images using the Save button", component_args=hide_dirs), - "outdir_init_images": OptionInfo("outputs/init-images", "Directory for saving init images when using img2img", component_args=hide_dirs), -})) - -options_templates.update(options_section(('saving-to-dirs', "Saving to a directory"), { - "save_to_dirs": OptionInfo(True, "Save images to a subdirectory"), - "grid_save_to_dirs": OptionInfo(True, "Save grids to a subdirectory"), - "use_save_to_dirs_for_ui": OptionInfo(False, "When using \"Save\" button, save images to a subdirectory"), - "directories_filename_pattern": OptionInfo("[date]", "Directory name pattern", component_args=hide_dirs).link("wiki", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Custom-Images-Filename-Name-and-Subdirectory"), - "directories_max_prompt_words": OptionInfo(8, "Max prompt words for [prompt_words] pattern", gr.Slider, {"minimum": 1, "maximum": 20, "step": 1, **hide_dirs}), -})) - -options_templates.update(options_section(('upscaling', "Upscaling"), { - "ESRGAN_tile": OptionInfo(192, "Tile size for ESRGAN upscalers.", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}).info("0 = no tiling"), - "ESRGAN_tile_overlap": OptionInfo(8, "Tile overlap for ESRGAN upscalers.", gr.Slider, {"minimum": 0, "maximum": 48, "step": 1}).info("Low values = visible seam"), - "realesrgan_enabled_models": OptionInfo(["R-ESRGAN 4x+", "R-ESRGAN 4x+ Anime6B"], "Select which Real-ESRGAN models to show in the web UI.", gr.CheckboxGroup, lambda: {"choices": shared_items.realesrgan_models_names()}), - "upscaler_for_img2img": OptionInfo(None, "Upscaler for img2img", gr.Dropdown, lambda: {"choices": [x.name for x in sd_upscalers]}), -})) - -options_templates.update(options_section(('face-restoration', "Face restoration"), { - "face_restoration_model": OptionInfo("CodeFormer", "Face restoration model", gr.Radio, lambda: {"choices": [x.name() for x in face_restorers]}), - "code_former_weight": OptionInfo(0.5, "CodeFormer weight", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}).info("0 = maximum effect; 1 = minimum effect"), - "face_restoration_unload": OptionInfo(False, "Move face restoration model from VRAM into RAM after processing"), -})) - -options_templates.update(options_section(('system', "System"), { - "auto_launch_browser": OptionInfo("Local", "Automatically open webui in browser on startup", gr.Radio, lambda: {"choices": ["Disable", "Local", "Remote"]}), - "show_warnings": OptionInfo(False, "Show warnings in console.").needs_reload_ui(), - "show_gradio_deprecation_warnings": OptionInfo(True, "Show gradio deprecation warnings in console.").needs_reload_ui(), - "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."), - "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"), { - "unload_models_when_training": OptionInfo(False, "Move VAE and CLIP to RAM when training if possible. Saves VRAM."), - "pin_memory": OptionInfo(False, "Turn on pin_memory for DataLoader. Makes training slightly faster but can increase memory usage."), - "save_optimizer_state": OptionInfo(False, "Saves Optimizer state as separate *.optim file. Training of embedding or HN can be resumed with the matching optim file."), - "save_training_settings_to_txt": OptionInfo(True, "Save textual inversion and hypernet settings to a text file whenever training starts."), - "dataset_filename_word_regex": OptionInfo("", "Filename word regex"), - "dataset_filename_join_string": OptionInfo(" ", "Filename join string"), - "training_image_repeats_per_epoch": OptionInfo(1, "Number of repeats for a single input image per epoch; used only for displaying epoch number", gr.Number, {"precision": 0}), - "training_write_csv_every": OptionInfo(500, "Save an csv containing the loss to log directory every N steps, 0 to disable"), - "training_xattention_optimizations": OptionInfo(False, "Use cross attention optimizations while training"), - "training_enable_tensorboard": OptionInfo(False, "Enable tensorboard logging."), - "training_tensorboard_save_images": OptionInfo(False, "Save generated images within tensorboard."), - "training_tensorboard_flush_every": OptionInfo(120, "How often, in seconds, to flush the pending tensorboard events and summaries to disk."), -})) - -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_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_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"), - "enable_quantization": OptionInfo(False, "Enable quantization in K samplers for sharper and cleaner results. This may change existing seeds").needs_reload_ui(), - "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"), - "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", "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"), { - "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(('vae', "VAE"), { - "sd_vae_explanation": OptionHTML(""" -VAE is a neural network that transforms a standard RGB -image into latent space representation and back. Latent space representation is what stable diffusion is working on during sampling -(i.e. when the progress bar is between empty and full). For txt2img, VAE is used to create a resulting image after the sampling is finished. -For img2img, VAE is used to process user's input image before the sampling, and to create an image after sampling. -"""), - "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_overrides_per_model_preferences": OptionInfo(True, "Selected VAE overrides per-model preferences").info("you can set per-model VAE either by editing user metadata for checkpoints, or by making the VAE have same name as checkpoint"), - "auto_vae_precision": OptionInfo(True, "Automatically revert VAE to 32-bit floats").info("triggers when a tensor with NaNs is produced in VAE; disabling the option in this case will result in a black square image"), - "sd_vae_encode_method": OptionInfo("Full", "VAE type for encode", gr.Radio, {"choices": ["Full", "TAESD"]}).info("method to encode image to latent (use in img2img, hires-fix or inpaint mask)"), - "sd_vae_decode_method": OptionInfo("Full", "VAE type for decode", gr.Radio, {"choices": ["Full", "TAESD"]}).info("method to decode latent to image"), -})) - -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_reload_ui(), - "img2img_sketch_default_brush_color": OptionInfo("#ffffff", "Sketch initial brush color", ui_components.FormColorPicker, {}).info("default brush color of img2img sketch").needs_reload_ui(), - "img2img_inpaint_mask_brush_color": OptionInfo("#ffffff", "Inpaint mask brush color", ui_components.FormColorPicker, {}).info("brush color of inpaint mask").needs_reload_ui(), - "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_reload_ui(), - "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"), - "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"), - "pad_cond_uncond": OptionInfo(False, "Pad prompt/negative prompt to be same length").info("improves performance when prompt and negative prompt have different lengths; changes seeds"), - "persistent_cond_cache": OptionInfo(True, "Persistent cond cache").info("Do not recalculate conds from prompts if prompts have not changed since previous calculation"), -})) - -options_templates.update(options_section(('compatibility', "Compatibility"), { - "use_old_emphasis_implementation": OptionInfo(False, "Use old emphasis implementation. Can be useful to reproduce old seeds."), - "use_old_karras_scheduler_sigmas": OptionInfo(False, "Use old karras scheduler sigmas (0.1 to 10)."), - "no_dpmpp_sde_batch_determinism": OptionInfo(False, "Do not make DPM++ SDE deterministic across different batch sizes."), - "use_old_hires_fix_width_height": OptionInfo(False, "For hires fix, use width/height sliders to set final resolution rather than first pass (disables Upscale by, Resize width/height to)."), - "dont_fix_second_order_samplers_schedule": OptionInfo(False, "Do not fix prompt schedule for second order samplers."), - "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"), { - "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}), - "interrogate_clip_min_length": OptionInfo(24, "BLIP: minimum description length", gr.Slider, {"minimum": 1, "maximum": 128, "step": 1}), - "interrogate_clip_max_length": OptionInfo(48, "BLIP: maximum description length", gr.Slider, {"minimum": 1, "maximum": 256, "step": 1}), - "interrogate_clip_dict_limit": OptionInfo(1500, "CLIP: maximum number of lines in text file").info("0 = No limit"), - "interrogate_clip_skip_categories": OptionInfo([], "CLIP: skip inquire categories", gr.CheckboxGroup, lambda: {"choices": modules.interrogate.category_types()}, refresh=modules.interrogate.category_types), - "interrogate_deepbooru_score_threshold": OptionInfo(0.5, "deepbooru: score threshold", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}), - "deepbooru_sort_alpha": OptionInfo(True, "deepbooru: sort tags alphabetically").info("if not: sort by score"), - "deepbooru_use_spaces": OptionInfo(True, "deepbooru: use spaces in tags").info("if not: use underscores"), - "deepbooru_escape": OptionInfo(True, "deepbooru: escape (\\) brackets").info("so they are used as literal brackets and not for emphasis"), - "deepbooru_filter_tags": OptionInfo("", "deepbooru: filter out those tags").info("separate by comma"), -})) - -options_templates.update(options_section(('extra_networks', "Extra Networks"), { - "extra_networks_show_hidden_directories": OptionInfo(True, "Show hidden directories").info("directory is hidden if its name starts with \".\"."), - "extra_networks_hidden_models": OptionInfo("When searched", "Show cards for models in hidden directories", gr.Radio, {"choices": ["Always", "When searched", "Never"]}).info('"When searched" option will only show the item when the search string has 4 characters or more'), - "extra_networks_default_multiplier": OptionInfo(1.0, "Default multiplier for extra networks", gr.Slider, {"minimum": 0.0, "maximum": 2.0, "step": 0.01}), - "extra_networks_card_width": OptionInfo(0, "Card width for Extra Networks").info("in pixels"), - "extra_networks_card_height": OptionInfo(0, "Card height for Extra Networks").info("in pixels"), - "extra_networks_card_text_scale": OptionInfo(1.0, "Card text scale", gr.Slider, {"minimum": 0.0, "maximum": 2.0, "step": 0.01}).info("1 = original size"), - "extra_networks_card_show_desc": OptionInfo(True, "Show description on card"), - "extra_networks_add_text_separator": OptionInfo(" ", "Extra networks separator").info("extra text to add before <...> when adding extra network to prompt"), - "ui_extra_networks_tab_reorder": OptionInfo("", "Extra networks tab order").needs_reload_ui(), - "textual_inversion_print_at_load": OptionInfo(False, "Print a list of Textual Inversion embeddings when loading model"), - "textual_inversion_add_hashes_to_infotext": OptionInfo(True, "Add Textual Inversion hashes to infotext"), - "sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": ["None", *hypernetworks]}, refresh=reload_hypernetworks), -})) - -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_reload_ui(), - "gradio_theme": OptionInfo("Default", "Gradio theme", ui_components.DropdownEditable, lambda: {"choices": ["Default"] + gradio_hf_hub_themes}).info("you can also manually enter any of themes from the gallery.").needs_reload_ui(), - "gradio_themes_cache": OptionInfo(True, "Cache gradio themes locally").info("disable to update the selected Gradio theme"), - "return_grid": OptionInfo(True, "Show grid 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"), - "js_modal_lightbox": OptionInfo(True, "Enable full page image viewer"), - "js_modal_lightbox_initially_zoomed": OptionInfo(True, "Show images zoomed in by default in full page image viewer"), - "js_modal_lightbox_gamepad": OptionInfo(False, "Navigate image viewer with gamepad"), - "js_modal_lightbox_gamepad_repeat": OptionInfo(250, "Gamepad repeat period, in milliseconds"), - "show_progress_in_title": OptionInfo(True, "Show generation progress in window title."), - "samplers_in_dropdown": OptionInfo(True, "Use dropdown for sampler selection instead of radio group").needs_reload_ui(), - "dimensions_and_batch_together": OptionInfo(True, "Show Width/Height and Batch sliders in same row").needs_reload_ui(), - "keyedit_precision_attention": OptionInfo(0.1, "Ctrl+up/down precision when editing (attention:1.1)", gr.Slider, {"minimum": 0.01, "maximum": 0.2, "step": 0.001}), - "keyedit_precision_extra": OptionInfo(0.05, "Ctrl+up/down precision when editing ", gr.Slider, {"minimum": 0.01, "maximum": 0.2, "step": 0.001}), - "keyedit_delimiters": OptionInfo(".,\\/!?%^*;:{}=`~()", "Ctrl+up/down word delimiters"), - "keyedit_move": OptionInfo(True, "Alt+left/right moves prompt elements"), - "quicksettings_list": OptionInfo(["sd_model_checkpoint"], "Quicksettings list", ui_components.DropdownMulti, lambda: {"choices": list(opts.data_labels.keys())}).js("info", "settingsHintsShowQuicksettings").info("setting entries that appear at the top of page rather than in settings tab").needs_reload_ui(), - "ui_tab_order": OptionInfo([], "UI tab order", ui_components.DropdownMulti, lambda: {"choices": list(tab_names)}).needs_reload_ui(), - "hidden_tabs": OptionInfo([], "Hidden UI tabs", ui_components.DropdownMulti, lambda: {"choices": list(tab_names)}).needs_reload_ui(), - "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_reload_ui(), - "hires_fix_show_sampler": OptionInfo(False, "Hires fix: show hires checkpoint and sampler selection").needs_reload_ui(), - "hires_fix_show_prompts": OptionInfo(False, "Hires fix: show hires prompt and negative prompt").needs_reload_ui(), - "disable_token_counters": OptionInfo(False, "Disable prompt token counters").needs_reload_ui(), -})) - - -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"), - "add_user_name_to_info": OptionInfo(False, "Add user name to generation information when authenticated"), - "add_version_to_infotext": OptionInfo(True, "Add program version to generation information"), - "disable_weights_auto_swap": OptionInfo(True, "Disregard checkpoint information from pasted infotext").info("when reading generation parameters from text into UI"), - "infotext_styles": OptionInfo("Apply if any", "Infer styles from prompts of pasted infotext", gr.Radio, {"choices": ["Ignore", "Apply", "Discard", "Apply if any"]}).info("when reading generation parameters from text into UI)").html("""
    -
  • Ignore: keep prompt and styles dropdown as it is.
    • -
  • Apply: remove style text from prompt, always replace styles dropdown value with found styles (even if none are found).
    • -
  • Discard: remove style text from prompt, keep styles dropdown as it is.
    • -
  • Apply if any: remove style text from prompt; if any styles are found in prompt, put them into styles dropdown, otherwise keep it as it is.
    • -
"""), - -})) - -options_templates.update(options_section(('ui', "Live previews"), { - "show_progressbar": OptionInfo(True, "Show progressbar"), - "live_previews_enable": OptionInfo(True, "Show live previews of the created image"), - "live_previews_image_format": OptionInfo("png", "Live preview file format", gr.Radio, {"choices": ["jpeg", "png", "webp"]}), - "show_progress_grid": OptionInfo(True, "Show previews of all images generated in a batch as a grid"), - "show_progress_every_n_steps": OptionInfo(10, "Live preview display period", gr.Slider, {"minimum": -1, "maximum": 32, "step": 1}).info("in sampling steps - show new live preview image every N sampling steps; -1 = only show after completion of batch"), - "show_progress_type": OptionInfo("Approx NN", "Live preview method", gr.Radio, {"choices": ["Full", "Approx NN", "Approx cheap", "TAESD"]}).info("Full = slow but pretty; Approx NN and TAESD = fast but low quality; Approx cheap = super fast but terrible otherwise"), - "live_preview_content": OptionInfo("Prompt", "Live preview subject", gr.Radio, {"choices": ["Combined", "Prompt", "Negative prompt"]}), - "live_preview_refresh_period": OptionInfo(1000, "Progressbar and preview update period").info("in milliseconds"), -})) - -options_templates.update(options_section(('sampler-params', "Sampler parameters"), { - "hide_samplers": OptionInfo([], "Hide samplers in user interface", gr.CheckboxGroup, lambda: {"choices": [x.name for x in list_samplers()]}).needs_reload_ui(), - "eta_ddim": OptionInfo(0.0, "Eta for DDIM", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}).info("noise multiplier; higher = more unperdictable results"), - "eta_ancestral": OptionInfo(1.0, "Eta for ancestral samplers", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}).info("noise multiplier; applies to Euler a and other samplers that have a in them"), - "ddim_discretize": OptionInfo('uniform', "img2img DDIM discretize", gr.Radio, {"choices": ['uniform', 'quad']}), - 's_churn': OptionInfo(0.0, "sigma churn", gr.Slider, {"minimum": 0.0, "maximum": 100.0, "step": 0.01}).info('amount of stochasticity; only applies to Euler, Heun, and DPM2'), - 's_tmin': OptionInfo(0.0, "sigma tmin", gr.Slider, {"minimum": 0.0, "maximum": 10.0, "step": 0.01}).info('enable stochasticity; start value of the sigma range; only applies to Euler, Heun, and DPM2'), - 's_tmax': OptionInfo(0.0, "sigma tmax", gr.Slider, {"minimum": 0.0, "maximum": 999.0, "step": 0.01}).info("0 = inf; end value of the sigma range; only applies to Euler, Heun, and DPM2"), - 's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.1, "step": 0.001}).info('amount of additional noise to counteract loss of detail during sampling; only applies to Euler, Heun, and DPM2'), - 'k_sched_type': OptionInfo("Automatic", "Scheduler type", gr.Dropdown, {"choices": ["Automatic", "karras", "exponential", "polyexponential"]}).info("lets you override the noise schedule for k-diffusion samplers; choosing Automatic disables the three parameters below"), - 'sigma_min': OptionInfo(0.0, "sigma min", gr.Number).info("0 = default (~0.03); minimum noise strength for k-diffusion noise scheduler"), - 'sigma_max': OptionInfo(0.0, "sigma max", gr.Number).info("0 = default (~14.6); maximum noise strength for k-diffusion noise scheduler"), - 'rho': OptionInfo(0.0, "rho", gr.Number).info("0 = default (7 for karras, 1 for polyexponential); higher values result in a steeper noise schedule (decreases faster)"), - 'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}).info("ENSD; does not improve anything, just produces different results for ancestral samplers - only useful for reproducing images"), - 'always_discard_next_to_last_sigma': OptionInfo(False, "Always discard next-to-last sigma").link("PR", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/6044"), - 'uni_pc_variant': OptionInfo("bh1", "UniPC variant", gr.Radio, {"choices": ["bh1", "bh2", "vary_coeff"]}), - 'uni_pc_skip_type': OptionInfo("time_uniform", "UniPC skip type", gr.Radio, {"choices": ["time_uniform", "time_quadratic", "logSNR"]}), - 'uni_pc_order': OptionInfo(3, "UniPC order", gr.Slider, {"minimum": 1, "maximum": 50, "step": 1}).info("must be < sampling steps"), - 'uni_pc_lower_order_final': OptionInfo(True, "UniPC lower order final"), -})) - -options_templates.update(options_section(('postprocessing', "Postprocessing"), { - 'postprocessing_enable_in_main_ui': OptionInfo([], "Enable postprocessing operations in txt2img and img2img tabs", ui_components.DropdownMulti, lambda: {"choices": [x.name for x in shared_items.postprocessing_scripts()]}), - 'postprocessing_operation_order': OptionInfo([], "Postprocessing operation order", ui_components.DropdownMulti, lambda: {"choices": [x.name for x in shared_items.postprocessing_scripts()]}), - 'upscaling_max_images_in_cache': OptionInfo(5, "Maximum number of images in upscaling cache", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}), -})) - -options_templates.update(options_section((None, "Hidden options"), { - "disabled_extensions": OptionInfo([], "Disable these extensions"), - "disable_all_extensions": OptionInfo("none", "Disable all extensions (preserves the list of disabled extensions)", gr.Radio, {"choices": ["none", "extra", "all"]}), - "restore_config_state_file": OptionInfo("", "Config state file to restore from, under 'config-states/' folder"), - "sd_checkpoint_hash": OptionInfo("", "SHA256 hash of the current checkpoint"), -})) - - -options_templates.update() - - -class Options: - data = None - data_labels = options_templates - typemap = {int: float} - - def __init__(self): - self.data = {k: v.default for k, v in self.data_labels.items()} - - def __setattr__(self, key, value): - if self.data is not None: - if key in self.data or key in self.data_labels: - assert not cmd_opts.freeze_settings, "changing settings is disabled" - - info = opts.data_labels.get(key, None) - if info.do_not_save: - return - - comp_args = info.component_args if info else None - if isinstance(comp_args, dict) and comp_args.get('visible', True) is False: - raise RuntimeError(f"not possible to set {key} because it is restricted") - - if cmd_opts.hide_ui_dir_config and key in restricted_opts: - raise RuntimeError(f"not possible to set {key} because it is restricted") - - self.data[key] = value - return - - return super(Options, self).__setattr__(key, value) - - def __getattr__(self, item): - if self.data is not None: - if item in self.data: - return self.data[item] - - if item in self.data_labels: - return self.data_labels[item].default - - return super(Options, self).__getattribute__(item) - - def set(self, key, value): - """sets an option and calls its onchange callback, returning True if the option changed and False otherwise""" - - oldval = self.data.get(key, None) - if oldval == value: - return False - - if self.data_labels[key].do_not_save: - return False - - try: - setattr(self, key, value) - except RuntimeError: - return False - - if self.data_labels[key].onchange is not None: - try: - self.data_labels[key].onchange() - except Exception as e: - errors.display(e, f"changing setting {key} to {value}") - setattr(self, key, oldval) - return False - - return True - - def get_default(self, key): - """returns the default value for the key""" - - data_label = self.data_labels.get(key) - if data_label is None: - return None - - return data_label.default - - def save(self, filename): - assert not cmd_opts.freeze_settings, "saving settings is disabled" - - with open(filename, "w", encoding="utf8") as file: - json.dump(self.data, file, indent=4) - - def same_type(self, x, y): - if x is None or y is None: - return True - - type_x = self.typemap.get(type(x), type(x)) - type_y = self.typemap.get(type(y), type(y)) - - return type_x == type_y - - def load(self, filename): - with open(filename, "r", encoding="utf8") as file: - self.data = json.load(file) - - # 1.6.0 VAE defaults - if self.data.get('sd_vae_as_default') is not None and self.data.get('sd_vae_overrides_per_model_preferences') is None: - self.data['sd_vae_overrides_per_model_preferences'] = not self.data.get('sd_vae_as_default') - - # 1.1.1 quicksettings list migration - if self.data.get('quicksettings') is not None and self.data.get('quicksettings_list') is None: - self.data['quicksettings_list'] = [i.strip() for i in self.data.get('quicksettings').split(',')] - - # 1.4.0 ui_reorder - if isinstance(self.data.get('ui_reorder'), str) and self.data.get('ui_reorder') and "ui_reorder_list" not in self.data: - self.data['ui_reorder_list'] = [i.strip() for i in self.data.get('ui_reorder').split(',')] - - bad_settings = 0 - for k, v in self.data.items(): - info = self.data_labels.get(k, None) - if info is not None and not self.same_type(info.default, v): - print(f"Warning: bad setting value: {k}: {v} ({type(v).__name__}; expected {type(info.default).__name__})", file=sys.stderr) - bad_settings += 1 - - if bad_settings > 0: - print(f"The program is likely to not work with bad settings.\nSettings file: {filename}\nEither fix the file, or delete it and restart.", file=sys.stderr) - - def onchange(self, key, func, call=True): - item = self.data_labels.get(key) - item.onchange = func - - if call: - func() - - def dumpjson(self): - d = {k: self.data.get(k, v.default) for k, v in self.data_labels.items()} - d["_comments_before"] = {k: v.comment_before for k, v in self.data_labels.items() if v.comment_before is not None} - d["_comments_after"] = {k: v.comment_after for k, v in self.data_labels.items() if v.comment_after is not None} - return json.dumps(d) - - def add_option(self, key, info): - self.data_labels[key] = info - - def reorder(self): - """reorder settings so that all items related to section always go together""" - - section_ids = {} - settings_items = self.data_labels.items() - for _, item in settings_items: - if item.section not in section_ids: - section_ids[item.section] = len(section_ids) - - self.data_labels = dict(sorted(settings_items, key=lambda x: section_ids[x[1].section])) - - def cast_value(self, key, value): - """casts an arbitrary to the same type as this setting's value with key - Example: cast_value("eta_noise_seed_delta", "12") -> returns 12 (an int rather than str) - """ - - if value is None: - return None - - default_value = self.data_labels[key].default - if default_value is None: - default_value = getattr(self, key, None) - if default_value is None: - return None - - expected_type = type(default_value) - if expected_type == bool and value == "False": - value = False - else: - value = expected_type(value) - - return value - - -opts = Options() -if os.path.exists(config_filename): - opts.load(config_filename) - - -class Shared(sys.modules[__name__].__class__): - """ - this class is here to provide sd_model field as a property, so that it can be created and loaded on demand rather than - at program startup. - """ - - sd_model_val = None - - @property - def sd_model(self): - import modules.sd_models - - return modules.sd_models.model_data.get_sd_model() - - @sd_model.setter - def sd_model(self, value): - import modules.sd_models - - modules.sd_models.model_data.set_sd_model(value) - - -sd_model: LatentDiffusion = None # this var is here just for IDE's type checking; it cannot be accessed because the class field above will be accessed instead -sys.modules[__name__].__class__ = Shared +sd_model: LatentDiffusion = None settings_components = None """assinged from ui.py, a mapping on setting names to gradio components repsponsible for those settings""" +tab_names = [] + latent_upscale_default_mode = "Latent" latent_upscale_modes = { "Latent": {"mode": "bilinear", "antialias": False}, @@ -856,121 +64,24 @@ progress_print_out = sys.stdout gradio_theme = gr.themes.Base() +total_tqdm = None -def reload_gradio_theme(theme_name=None): - global gradio_theme - if not theme_name: - theme_name = opts.gradio_theme +mem_mon = None - default_theme_args = dict( - font=["Source Sans Pro", 'ui-sans-serif', 'system-ui', 'sans-serif'], - font_mono=['IBM Plex Mono', 'ui-monospace', 'Consolas', 'monospace'], - ) +options_section = options.options_section +OptionInfo = options.OptionInfo +OptionHTML = options.OptionHTML - if theme_name == "Default": - gradio_theme = gr.themes.Default(**default_theme_args) - else: - try: - theme_cache_dir = os.path.join(script_path, 'tmp', 'gradio_themes') - theme_cache_path = os.path.join(theme_cache_dir, f'{theme_name.replace("/", "_")}.json') - if opts.gradio_themes_cache and os.path.exists(theme_cache_path): - gradio_theme = gr.themes.ThemeClass.load(theme_cache_path) - else: - os.makedirs(theme_cache_dir, exist_ok=True) - gradio_theme = gr.themes.ThemeClass.from_hub(theme_name) - gradio_theme.dump(theme_cache_path) - except Exception as e: - errors.display(e, "changing gradio theme") - gradio_theme = gr.themes.Default(**default_theme_args) +natural_sort_key = util.natural_sort_key +listfiles = util.listfiles +html_path = util.html_path +html = util.html +walk_files = util.walk_files +ldm_print = util.ldm_print +reload_gradio_theme = shared_gradio_themes.reload_gradio_theme -class TotalTQDM: - def __init__(self): - self._tqdm = None - - def reset(self): - self._tqdm = tqdm.tqdm( - desc="Total progress", - total=state.job_count * state.sampling_steps, - position=1, - file=progress_print_out - ) - - def update(self): - if not opts.multiple_tqdm or cmd_opts.disable_console_progressbars: - return - if self._tqdm is None: - self.reset() - self._tqdm.update() - - def updateTotal(self, new_total): - if not opts.multiple_tqdm or cmd_opts.disable_console_progressbars: - return - if self._tqdm is None: - self.reset() - self._tqdm.total = new_total - - def clear(self): - if self._tqdm is not None: - self._tqdm.refresh() - self._tqdm.close() - self._tqdm = None - - -total_tqdm = TotalTQDM() - -mem_mon = modules.memmon.MemUsageMonitor("MemMon", device, opts) -mem_mon.start() - - -def natural_sort_key(s, regex=re.compile('([0-9]+)')): - return [int(text) if text.isdigit() else text.lower() for text in regex.split(s)] - - -def listfiles(dirname): - filenames = [os.path.join(dirname, x) for x in sorted(os.listdir(dirname), key=natural_sort_key) if not x.startswith(".")] - return [file for file in filenames if os.path.isfile(file)] - - -def html_path(filename): - return os.path.join(script_path, "html", filename) - - -def html(filename): - path = html_path(filename) - - if os.path.exists(path): - with open(path, encoding="utf8") as file: - return file.read() - - return "" - - -def walk_files(path, allowed_extensions=None): - if not os.path.exists(path): - return - - if allowed_extensions is not None: - allowed_extensions = set(allowed_extensions) - - items = list(os.walk(path, followlinks=True)) - items = sorted(items, key=lambda x: natural_sort_key(x[0])) - - for root, _, files in items: - for filename in sorted(files, key=natural_sort_key): - if allowed_extensions is not None: - _, ext = os.path.splitext(filename) - if ext not in allowed_extensions: - continue - - if not opts.list_hidden_files and ("/." in root or "\\." in root): - continue - - yield os.path.join(root, filename) - - -def ldm_print(*args, **kwargs): - if opts.hide_ldm_prints: - return - - print(*args, **kwargs) +list_checkpoint_tiles = shared_items.list_checkpoint_tiles +refresh_checkpoints = shared_items.refresh_checkpoints +list_samplers = shared_items.list_samplers +reload_hypernetworks = shared_items.reload_hypernetworks diff --git a/modules/shared_cmd_options.py b/modules/shared_cmd_options.py new file mode 100644 index 000000000..af24938b0 --- /dev/null +++ b/modules/shared_cmd_options.py @@ -0,0 +1,18 @@ +import os + +import launch +from modules import cmd_args, script_loading +from modules.paths_internal import models_path, script_path, data_path, sd_configs_path, sd_default_config, sd_model_file, default_sd_model_file, extensions_dir, extensions_builtin_dir # noqa: F401 + +parser = cmd_args.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: + cmd_opts = parser.parse_args() +else: + cmd_opts, _ = parser.parse_known_args() + + +cmd_opts.disable_extension_access = (cmd_opts.share or cmd_opts.listen or cmd_opts.server_name) and not cmd_opts.enable_insecure_extension_access diff --git a/modules/shared_gradio_themes.py b/modules/shared_gradio_themes.py new file mode 100644 index 000000000..ad1f2212a --- /dev/null +++ b/modules/shared_gradio_themes.py @@ -0,0 +1,66 @@ +import os + +import gradio as gr + +from modules import errors, shared +from modules.paths_internal import script_path + + +# https://huggingface.co/datasets/freddyaboulton/gradio-theme-subdomains/resolve/main/subdomains.json +gradio_hf_hub_themes = [ + "gradio/base", + "gradio/glass", + "gradio/monochrome", + "gradio/seafoam", + "gradio/soft", + "gradio/dracula_test", + "abidlabs/dracula_test", + "abidlabs/Lime", + "abidlabs/pakistan", + "Ama434/neutral-barlow", + "dawood/microsoft_windows", + "finlaymacklon/smooth_slate", + "Franklisi/darkmode", + "freddyaboulton/dracula_revamped", + "freddyaboulton/test-blue", + "gstaff/xkcd", + "Insuz/Mocha", + "Insuz/SimpleIndigo", + "JohnSmith9982/small_and_pretty", + "nota-ai/theme", + "nuttea/Softblue", + "ParityError/Anime", + "reilnuud/polite", + "remilia/Ghostly", + "rottenlittlecreature/Moon_Goblin", + "step-3-profit/Midnight-Deep", + "Taithrah/Minimal", + "ysharma/huggingface", + "ysharma/steampunk" +] + + +def reload_gradio_theme(theme_name=None): + if not theme_name: + theme_name = shared.opts.gradio_theme + + default_theme_args = dict( + font=["Source Sans Pro", 'ui-sans-serif', 'system-ui', 'sans-serif'], + font_mono=['IBM Plex Mono', 'ui-monospace', 'Consolas', 'monospace'], + ) + + if theme_name == "Default": + shared.gradio_theme = gr.themes.Default(**default_theme_args) + else: + try: + theme_cache_dir = os.path.join(script_path, 'tmp', 'gradio_themes') + theme_cache_path = os.path.join(theme_cache_dir, f'{theme_name.replace("/", "_")}.json') + if shared.opts.gradio_themes_cache and os.path.exists(theme_cache_path): + shared.gradio_theme = gr.themes.ThemeClass.load(theme_cache_path) + else: + os.makedirs(theme_cache_dir, exist_ok=True) + gradio_theme = gr.themes.ThemeClass.from_hub(theme_name) + gradio_theme.dump(theme_cache_path) + except Exception as e: + errors.display(e, "changing gradio theme") + shared.gradio_theme = gr.themes.Default(**default_theme_args) diff --git a/modules/shared_init.py b/modules/shared_init.py new file mode 100644 index 000000000..e7fc18d2d --- /dev/null +++ b/modules/shared_init.py @@ -0,0 +1,51 @@ +import os + +import torch + +from modules import shared +from modules.shared import cmd_opts + +import sys +sys.setrecursionlimit(1000) + + +def initialize(): + """Initializes fields inside the shared module in a controlled manner. + + Should be called early because some other modules you can import mingt need these fields to be already set. + """ + + os.makedirs(cmd_opts.hypernetwork_dir, exist_ok=True) + + from modules import options, shared_options + shared.options_templates = shared_options.options_templates + shared.opts = options.Options(shared_options.options_templates, shared_options.restricted_opts) + if os.path.exists(shared.config_filename): + shared.opts.load(shared.config_filename) + + from modules import devices + devices.device, devices.device_interrogate, devices.device_gfpgan, devices.device_esrgan, devices.device_codeformer = \ + (devices.cpu if any(y in cmd_opts.use_cpu for y in [x, 'all']) else devices.get_optimal_device() for x in ['sd', 'interrogate', 'gfpgan', 'esrgan', 'codeformer']) + + devices.dtype = torch.float32 if cmd_opts.no_half else torch.float16 + devices.dtype_vae = torch.float32 if cmd_opts.no_half or cmd_opts.no_half_vae else torch.float16 + + shared.device = devices.device + shared.weight_load_location = None if cmd_opts.lowram else "cpu" + + from modules import shared_state + shared.state = shared_state.State() + + from modules import styles + shared.prompt_styles = styles.StyleDatabase(shared.styles_filename) + + from modules import interrogate + shared.interrogator = interrogate.InterrogateModels("interrogate") + + from modules import shared_total_tqdm + shared.total_tqdm = shared_total_tqdm.TotalTQDM() + + from modules import memmon, devices + shared.mem_mon = memmon.MemUsageMonitor("MemMon", devices.device, shared.opts) + shared.mem_mon.start() + diff --git a/modules/shared_items.py b/modules/shared_items.py index 89792e88a..e4ec40a8b 100644 --- a/modules/shared_items.py +++ b/modules/shared_items.py @@ -1,3 +1,6 @@ +import sys + +from modules.shared_cmd_options import cmd_opts def realesrgan_models_names(): @@ -41,6 +44,28 @@ def refresh_unet_list(): modules.sd_unet.list_unets() +def list_checkpoint_tiles(): + import modules.sd_models + return modules.sd_models.checkpoint_tiles() + + +def refresh_checkpoints(): + import modules.sd_models + return modules.sd_models.list_models() + + +def list_samplers(): + import modules.sd_samplers + return modules.sd_samplers.all_samplers + + +def reload_hypernetworks(): + from modules.hypernetworks import hypernetwork + from modules import shared + + shared.hypernetworks = hypernetwork.list_hypernetworks(cmd_opts.hypernetwork_dir) + + ui_reorder_categories_builtin_items = [ "inpaint", "sampler", @@ -67,3 +92,27 @@ def ui_reorder_categories(): yield from sections yield "scripts" + + +class Shared(sys.modules[__name__].__class__): + """ + this class is here to provide sd_model field as a property, so that it can be created and loaded on demand rather than + at program startup. + """ + + sd_model_val = None + + @property + def sd_model(self): + import modules.sd_models + + return modules.sd_models.model_data.get_sd_model() + + @sd_model.setter + def sd_model(self, value): + import modules.sd_models + + modules.sd_models.model_data.set_sd_model(value) + + +sys.modules['modules.shared'].__class__ = Shared diff --git a/modules/shared_options.py b/modules/shared_options.py index e9b980a43..7468bc81a 100644 --- a/modules/shared_options.py +++ b/modules/shared_options.py @@ -1,40 +1,12 @@ -import datetime -import json -import os -import re -import sys -import threading -import time -import logging - import gradio as gr -import torch -import tqdm -import launch -import modules.interrogate -import modules.memmon -import modules.styles -import modules.devices as devices -from modules import localization, script_loading, errors, ui_components, shared_items, cmd_args, rng # noqa: F401 +from modules import localization, ui_components, shared_items, shared, interrogate, shared_gradio_themes from modules.paths_internal import models_path, script_path, data_path, sd_configs_path, sd_default_config, sd_model_file, default_sd_model_file, extensions_dir, extensions_builtin_dir # noqa: F401 -from ldm.models.diffusion.ddpm import LatentDiffusion -from typing import Optional - -log = logging.getLogger(__name__) - -demo = None - -parser = cmd_args.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: - cmd_opts = parser.parse_args() -else: - cmd_opts, _ = parser.parse_known_args() +from modules.shared_cmd_options import cmd_opts +from modules.options import options_section, OptionInfo, OptionHTML +options_templates = {} +hide_dirs = shared.hide_dirs restricted_opts = { "samples_filename_pattern", @@ -49,302 +21,6 @@ restricted_opts = { "outdir_init_images" } -# https://huggingface.co/datasets/freddyaboulton/gradio-theme-subdomains/resolve/main/subdomains.json -gradio_hf_hub_themes = [ - "gradio/base", - "gradio/glass", - "gradio/monochrome", - "gradio/seafoam", - "gradio/soft", - "gradio/dracula_test", - "abidlabs/dracula_test", - "abidlabs/Lime", - "abidlabs/pakistan", - "Ama434/neutral-barlow", - "dawood/microsoft_windows", - "finlaymacklon/smooth_slate", - "Franklisi/darkmode", - "freddyaboulton/dracula_revamped", - "freddyaboulton/test-blue", - "gstaff/xkcd", - "Insuz/Mocha", - "Insuz/SimpleIndigo", - "JohnSmith9982/small_and_pretty", - "nota-ai/theme", - "nuttea/Softblue", - "ParityError/Anime", - "reilnuud/polite", - "remilia/Ghostly", - "rottenlittlecreature/Moon_Goblin", - "step-3-profit/Midnight-Deep", - "Taithrah/Minimal", - "ysharma/huggingface", - "ysharma/steampunk" -] - - -cmd_opts.disable_extension_access = (cmd_opts.share or cmd_opts.listen or cmd_opts.server_name) and not cmd_opts.enable_insecure_extension_access - -devices.device, devices.device_interrogate, devices.device_gfpgan, devices.device_esrgan, devices.device_codeformer = \ - (devices.cpu if any(y in cmd_opts.use_cpu for y in [x, 'all']) else devices.get_optimal_device() for x in ['sd', 'interrogate', 'gfpgan', 'esrgan', 'codeformer']) - -devices.dtype = torch.float32 if cmd_opts.no_half else torch.float16 -devices.dtype_vae = torch.float32 if cmd_opts.no_half or cmd_opts.no_half_vae else torch.float16 - -device = devices.device -weight_load_location = None if cmd_opts.lowram else "cpu" - -batch_cond_uncond = cmd_opts.always_batch_cond_uncond or not (cmd_opts.lowvram or cmd_opts.medvram) -parallel_processing_allowed = not cmd_opts.lowvram and not cmd_opts.medvram -xformers_available = False -config_filename = cmd_opts.ui_settings_file - -os.makedirs(cmd_opts.hypernetwork_dir, exist_ok=True) -hypernetworks = {} -loaded_hypernetworks = [] - - -def reload_hypernetworks(): - from modules.hypernetworks import hypernetwork - global hypernetworks - - hypernetworks = hypernetwork.list_hypernetworks(cmd_opts.hypernetwork_dir) - - -class State: - skipped = False - interrupted = False - job = "" - job_no = 0 - job_count = 0 - processing_has_refined_job_count = False - job_timestamp = '0' - sampling_step = 0 - sampling_steps = 0 - current_latent = None - current_image = None - current_image_sampling_step = 0 - id_live_preview = 0 - textinfo = None - time_start = None - server_start = None - _server_command_signal = threading.Event() - _server_command: Optional[str] = None - - @property - def need_restart(self) -> bool: - # Compatibility getter for need_restart. - return self.server_command == "restart" - - @need_restart.setter - def need_restart(self, value: bool) -> None: - # Compatibility setter for need_restart. - if value: - self.server_command = "restart" - - @property - def server_command(self): - return self._server_command - - @server_command.setter - def server_command(self, value: Optional[str]) -> None: - """ - Set the server command to `value` and signal that it's been set. - """ - self._server_command = value - self._server_command_signal.set() - - def wait_for_server_command(self, timeout: Optional[float] = None) -> Optional[str]: - """ - Wait for server command to get set; return and clear the value and signal. - """ - if self._server_command_signal.wait(timeout): - self._server_command_signal.clear() - req = self._server_command - self._server_command = None - return req - return None - - def request_restart(self) -> None: - self.interrupt() - self.server_command = "restart" - log.info("Received restart request") - - def skip(self): - self.skipped = True - log.info("Received skip request") - - def interrupt(self): - self.interrupted = True - log.info("Received interrupt request") - - def nextjob(self): - if opts.live_previews_enable and opts.show_progress_every_n_steps == -1: - self.do_set_current_image() - - self.job_no += 1 - self.sampling_step = 0 - self.current_image_sampling_step = 0 - - def dict(self): - obj = { - "skipped": self.skipped, - "interrupted": self.interrupted, - "job": self.job, - "job_count": self.job_count, - "job_timestamp": self.job_timestamp, - "job_no": self.job_no, - "sampling_step": self.sampling_step, - "sampling_steps": self.sampling_steps, - } - - return obj - - def begin(self, job: str = "(unknown)"): - self.sampling_step = 0 - self.job_count = -1 - self.processing_has_refined_job_count = False - self.job_no = 0 - self.job_timestamp = datetime.datetime.now().strftime("%Y%m%d%H%M%S") - self.current_latent = None - self.current_image = None - self.current_image_sampling_step = 0 - self.id_live_preview = 0 - self.skipped = False - self.interrupted = False - self.textinfo = None - self.time_start = time.time() - self.job = job - devices.torch_gc() - log.info("Starting job %s", job) - - def end(self): - duration = time.time() - self.time_start - log.info("Ending job %s (%.2f seconds)", self.job, duration) - self.job = "" - self.job_count = 0 - - devices.torch_gc() - - def set_current_image(self): - """sets self.current_image from self.current_latent if enough sampling steps have been made after the last call to this""" - if not parallel_processing_allowed: - return - - if self.sampling_step - self.current_image_sampling_step >= opts.show_progress_every_n_steps and opts.live_previews_enable and opts.show_progress_every_n_steps != -1: - self.do_set_current_image() - - def do_set_current_image(self): - if self.current_latent is None: - return - - import modules.sd_samplers - - 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 - self.id_live_preview += 1 - - -state = State() -state.server_start = time.time() - -styles_filename = cmd_opts.styles_file -prompt_styles = modules.styles.StyleDatabase(styles_filename) - -interrogator = modules.interrogate.InterrogateModels("interrogate") - -face_restorers = [] - - -class OptionInfo: - def __init__(self, default=None, label="", component=None, component_args=None, onchange=None, section=None, refresh=None, comment_before='', comment_after=''): - self.default = default - self.label = label - self.component = component - self.component_args = component_args - self.onchange = onchange - self.section = section - self.refresh = refresh - self.do_not_save = False - - self.comment_before = comment_before - """HTML text that will be added after label in UI""" - - self.comment_after = comment_after - """HTML text that will be added before label in UI""" - - def link(self, label, url): - self.comment_before += f"[{label}]" - return self - - def js(self, label, js_func): - self.comment_before += f"[{label}]" - return self - - def info(self, info): - self.comment_after += f"({info})" - return self - - def html(self, html): - self.comment_after += html - return self - - def needs_restart(self): - self.comment_after += " (requires restart)" - return self - - def needs_reload_ui(self): - self.comment_after += " (requires Reload UI)" - return self - - -class OptionHTML(OptionInfo): - def __init__(self, text): - super().__init__(str(text).strip(), label='', component=lambda **kwargs: gr.HTML(elem_classes="settings-info", **kwargs)) - - self.do_not_save = True - - -def options_section(section_identifier, options_dict): - for v in options_dict.values(): - v.section = section_identifier - - return options_dict - - -def list_checkpoint_tiles(): - import modules.sd_models - return modules.sd_models.checkpoint_tiles() - - -def refresh_checkpoints(): - import modules.sd_models - return modules.sd_models.list_models() - - -def list_samplers(): - import modules.sd_samplers - return modules.sd_samplers.all_samplers - - -hide_dirs = {"visible": not cmd_opts.hide_ui_dir_config} -tab_names = [] - -options_templates = {} - options_templates.update(options_section(('saving-images', "Saving images/grids"), { "samples_save": OptionInfo(True, "Always save all generated images"), "samples_format": OptionInfo('png', 'File format for images'), @@ -412,11 +88,11 @@ options_templates.update(options_section(('upscaling', "Upscaling"), { "ESRGAN_tile": OptionInfo(192, "Tile size for ESRGAN upscalers.", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}).info("0 = no tiling"), "ESRGAN_tile_overlap": OptionInfo(8, "Tile overlap for ESRGAN upscalers.", gr.Slider, {"minimum": 0, "maximum": 48, "step": 1}).info("Low values = visible seam"), "realesrgan_enabled_models": OptionInfo(["R-ESRGAN 4x+", "R-ESRGAN 4x+ Anime6B"], "Select which Real-ESRGAN models to show in the web UI.", gr.CheckboxGroup, lambda: {"choices": shared_items.realesrgan_models_names()}), - "upscaler_for_img2img": OptionInfo(None, "Upscaler for img2img", gr.Dropdown, lambda: {"choices": [x.name for x in sd_upscalers]}), + "upscaler_for_img2img": OptionInfo(None, "Upscaler for img2img", gr.Dropdown, lambda: {"choices": [x.name for x in shared.sd_upscalers]}), })) options_templates.update(options_section(('face-restoration', "Face restoration"), { - "face_restoration_model": OptionInfo("CodeFormer", "Face restoration model", gr.Radio, lambda: {"choices": [x.name() for x in face_restorers]}), + "face_restoration_model": OptionInfo("CodeFormer", "Face restoration model", gr.Radio, lambda: {"choices": [x.name() for x in shared.face_restorers]}), "code_former_weight": OptionInfo(0.5, "CodeFormer weight", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}).info("0 = maximum effect; 1 = minimum effect"), "face_restoration_unload": OptionInfo(False, "Move face restoration model from VRAM into RAM after processing"), })) @@ -450,7 +126,7 @@ 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(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": shared_items.list_checkpoint_tiles()}, refresh=shared_items.refresh_checkpoints), "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"), @@ -526,7 +202,7 @@ options_templates.update(options_section(('interrogate', "Interrogate"), { "interrogate_clip_min_length": OptionInfo(24, "BLIP: minimum description length", gr.Slider, {"minimum": 1, "maximum": 128, "step": 1}), "interrogate_clip_max_length": OptionInfo(48, "BLIP: maximum description length", gr.Slider, {"minimum": 1, "maximum": 256, "step": 1}), "interrogate_clip_dict_limit": OptionInfo(1500, "CLIP: maximum number of lines in text file").info("0 = No limit"), - "interrogate_clip_skip_categories": OptionInfo([], "CLIP: skip inquire categories", gr.CheckboxGroup, lambda: {"choices": modules.interrogate.category_types()}, refresh=modules.interrogate.category_types), + "interrogate_clip_skip_categories": OptionInfo([], "CLIP: skip inquire categories", gr.CheckboxGroup, lambda: {"choices": interrogate.category_types()}, refresh=interrogate.category_types), "interrogate_deepbooru_score_threshold": OptionInfo(0.5, "deepbooru: score threshold", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}), "deepbooru_sort_alpha": OptionInfo(True, "deepbooru: sort tags alphabetically").info("if not: sort by score"), "deepbooru_use_spaces": OptionInfo(True, "deepbooru: use spaces in tags").info("if not: use underscores"), @@ -546,12 +222,12 @@ options_templates.update(options_section(('extra_networks', "Extra Networks"), { "ui_extra_networks_tab_reorder": OptionInfo("", "Extra networks tab order").needs_reload_ui(), "textual_inversion_print_at_load": OptionInfo(False, "Print a list of Textual Inversion embeddings when loading model"), "textual_inversion_add_hashes_to_infotext": OptionInfo(True, "Add Textual Inversion hashes to infotext"), - "sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": ["None", *hypernetworks]}, refresh=reload_hypernetworks), + "sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": ["None", *shared.hypernetworks]}, refresh=shared_items.reload_hypernetworks), })) 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_reload_ui(), - "gradio_theme": OptionInfo("Default", "Gradio theme", ui_components.DropdownEditable, lambda: {"choices": ["Default"] + gradio_hf_hub_themes}).info("you can also manually enter any of themes from the gallery.").needs_reload_ui(), + "gradio_theme": OptionInfo("Default", "Gradio theme", ui_components.DropdownEditable, lambda: {"choices": ["Default"] + shared_gradio_themes.gradio_hf_hub_themes}).info("you can also manually enter any of themes from the gallery.").needs_reload_ui(), "gradio_themes_cache": OptionInfo(True, "Cache gradio themes locally").info("disable to update the selected Gradio theme"), "return_grid": OptionInfo(True, "Show grid in results for web"), "do_not_show_images": OptionInfo(False, "Do not show any images in results for web"), @@ -568,9 +244,9 @@ options_templates.update(options_section(('ui', "User interface"), { "keyedit_precision_extra": OptionInfo(0.05, "Ctrl+up/down precision when editing ", gr.Slider, {"minimum": 0.01, "maximum": 0.2, "step": 0.001}), "keyedit_delimiters": OptionInfo(".,\\/!?%^*;:{}=`~()", "Ctrl+up/down word delimiters"), "keyedit_move": OptionInfo(True, "Alt+left/right moves prompt elements"), - "quicksettings_list": OptionInfo(["sd_model_checkpoint"], "Quicksettings list", ui_components.DropdownMulti, lambda: {"choices": list(opts.data_labels.keys())}).js("info", "settingsHintsShowQuicksettings").info("setting entries that appear at the top of page rather than in settings tab").needs_reload_ui(), - "ui_tab_order": OptionInfo([], "UI tab order", ui_components.DropdownMulti, lambda: {"choices": list(tab_names)}).needs_reload_ui(), - "hidden_tabs": OptionInfo([], "Hidden UI tabs", ui_components.DropdownMulti, lambda: {"choices": list(tab_names)}).needs_reload_ui(), + "quicksettings_list": OptionInfo(["sd_model_checkpoint"], "Quicksettings list", ui_components.DropdownMulti, lambda: {"choices": list(shared.opts.data_labels.keys())}).js("info", "settingsHintsShowQuicksettings").info("setting entries that appear at the top of page rather than in settings tab").needs_reload_ui(), + "ui_tab_order": OptionInfo([], "UI tab order", ui_components.DropdownMulti, lambda: {"choices": list(shared.tab_names)}).needs_reload_ui(), + "hidden_tabs": OptionInfo([], "Hidden UI tabs", ui_components.DropdownMulti, lambda: {"choices": list(shared.tab_names)}).needs_reload_ui(), "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_reload_ui(), "hires_fix_show_sampler": OptionInfo(False, "Hires fix: show hires checkpoint and sampler selection").needs_reload_ui(), "hires_fix_show_prompts": OptionInfo(False, "Hires fix: show hires prompt and negative prompt").needs_reload_ui(), @@ -605,7 +281,7 @@ options_templates.update(options_section(('ui', "Live previews"), { })) options_templates.update(options_section(('sampler-params', "Sampler parameters"), { - "hide_samplers": OptionInfo([], "Hide samplers in user interface", gr.CheckboxGroup, lambda: {"choices": [x.name for x in list_samplers()]}).needs_reload_ui(), + "hide_samplers": OptionInfo([], "Hide samplers in user interface", gr.CheckboxGroup, lambda: {"choices": [x.name for x in shared_items.list_samplers()]}).needs_reload_ui(), "eta_ddim": OptionInfo(0.0, "Eta for DDIM", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}).info("noise multiplier; higher = more unperdictable results"), "eta_ancestral": OptionInfo(1.0, "Eta for ancestral samplers", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}).info("noise multiplier; applies to Euler a and other samplers that have a in them"), "ddim_discretize": OptionInfo('uniform', "img2img DDIM discretize", gr.Radio, {"choices": ['uniform', 'quad']}), @@ -638,339 +314,3 @@ options_templates.update(options_section((None, "Hidden options"), { "sd_checkpoint_hash": OptionInfo("", "SHA256 hash of the current checkpoint"), })) - -options_templates.update() - - -class Options: - data = None - data_labels = options_templates - typemap = {int: float} - - def __init__(self): - self.data = {k: v.default for k, v in self.data_labels.items()} - - def __setattr__(self, key, value): - if self.data is not None: - if key in self.data or key in self.data_labels: - assert not cmd_opts.freeze_settings, "changing settings is disabled" - - info = opts.data_labels.get(key, None) - if info.do_not_save: - return - - comp_args = info.component_args if info else None - if isinstance(comp_args, dict) and comp_args.get('visible', True) is False: - raise RuntimeError(f"not possible to set {key} because it is restricted") - - if cmd_opts.hide_ui_dir_config and key in restricted_opts: - raise RuntimeError(f"not possible to set {key} because it is restricted") - - self.data[key] = value - return - - return super(Options, self).__setattr__(key, value) - - def __getattr__(self, item): - if self.data is not None: - if item in self.data: - return self.data[item] - - if item in self.data_labels: - return self.data_labels[item].default - - return super(Options, self).__getattribute__(item) - - def set(self, key, value): - """sets an option and calls its onchange callback, returning True if the option changed and False otherwise""" - - oldval = self.data.get(key, None) - if oldval == value: - return False - - if self.data_labels[key].do_not_save: - return False - - try: - setattr(self, key, value) - except RuntimeError: - return False - - if self.data_labels[key].onchange is not None: - try: - self.data_labels[key].onchange() - except Exception as e: - errors.display(e, f"changing setting {key} to {value}") - setattr(self, key, oldval) - return False - - return True - - def get_default(self, key): - """returns the default value for the key""" - - data_label = self.data_labels.get(key) - if data_label is None: - return None - - return data_label.default - - def save(self, filename): - assert not cmd_opts.freeze_settings, "saving settings is disabled" - - with open(filename, "w", encoding="utf8") as file: - json.dump(self.data, file, indent=4) - - def same_type(self, x, y): - if x is None or y is None: - return True - - type_x = self.typemap.get(type(x), type(x)) - type_y = self.typemap.get(type(y), type(y)) - - return type_x == type_y - - def load(self, filename): - with open(filename, "r", encoding="utf8") as file: - self.data = json.load(file) - - # 1.6.0 VAE defaults - if self.data.get('sd_vae_as_default') is not None and self.data.get('sd_vae_overrides_per_model_preferences') is None: - self.data['sd_vae_overrides_per_model_preferences'] = not self.data.get('sd_vae_as_default') - - # 1.1.1 quicksettings list migration - if self.data.get('quicksettings') is not None and self.data.get('quicksettings_list') is None: - self.data['quicksettings_list'] = [i.strip() for i in self.data.get('quicksettings').split(',')] - - # 1.4.0 ui_reorder - if isinstance(self.data.get('ui_reorder'), str) and self.data.get('ui_reorder') and "ui_reorder_list" not in self.data: - self.data['ui_reorder_list'] = [i.strip() for i in self.data.get('ui_reorder').split(',')] - - bad_settings = 0 - for k, v in self.data.items(): - info = self.data_labels.get(k, None) - if info is not None and not self.same_type(info.default, v): - print(f"Warning: bad setting value: {k}: {v} ({type(v).__name__}; expected {type(info.default).__name__})", file=sys.stderr) - bad_settings += 1 - - if bad_settings > 0: - print(f"The program is likely to not work with bad settings.\nSettings file: {filename}\nEither fix the file, or delete it and restart.", file=sys.stderr) - - def onchange(self, key, func, call=True): - item = self.data_labels.get(key) - item.onchange = func - - if call: - func() - - def dumpjson(self): - d = {k: self.data.get(k, v.default) for k, v in self.data_labels.items()} - d["_comments_before"] = {k: v.comment_before for k, v in self.data_labels.items() if v.comment_before is not None} - d["_comments_after"] = {k: v.comment_after for k, v in self.data_labels.items() if v.comment_after is not None} - return json.dumps(d) - - def add_option(self, key, info): - self.data_labels[key] = info - - def reorder(self): - """reorder settings so that all items related to section always go together""" - - section_ids = {} - settings_items = self.data_labels.items() - for _, item in settings_items: - if item.section not in section_ids: - section_ids[item.section] = len(section_ids) - - self.data_labels = dict(sorted(settings_items, key=lambda x: section_ids[x[1].section])) - - def cast_value(self, key, value): - """casts an arbitrary to the same type as this setting's value with key - Example: cast_value("eta_noise_seed_delta", "12") -> returns 12 (an int rather than str) - """ - - if value is None: - return None - - default_value = self.data_labels[key].default - if default_value is None: - default_value = getattr(self, key, None) - if default_value is None: - return None - - expected_type = type(default_value) - if expected_type == bool and value == "False": - value = False - else: - value = expected_type(value) - - return value - - -opts = Options() -if os.path.exists(config_filename): - opts.load(config_filename) - - -class Shared(sys.modules[__name__].__class__): - """ - this class is here to provide sd_model field as a property, so that it can be created and loaded on demand rather than - at program startup. - """ - - sd_model_val = None - - @property - def sd_model(self): - import modules.sd_models - - return modules.sd_models.model_data.get_sd_model() - - @sd_model.setter - def sd_model(self, value): - import modules.sd_models - - modules.sd_models.model_data.set_sd_model(value) - - -sd_model: LatentDiffusion = None # this var is here just for IDE's type checking; it cannot be accessed because the class field above will be accessed instead -sys.modules[__name__].__class__ = Shared - -settings_components = None -"""assinged from ui.py, a mapping on setting names to gradio components repsponsible for those settings""" - -latent_upscale_default_mode = "Latent" -latent_upscale_modes = { - "Latent": {"mode": "bilinear", "antialias": False}, - "Latent (antialiased)": {"mode": "bilinear", "antialias": True}, - "Latent (bicubic)": {"mode": "bicubic", "antialias": False}, - "Latent (bicubic antialiased)": {"mode": "bicubic", "antialias": True}, - "Latent (nearest)": {"mode": "nearest", "antialias": False}, - "Latent (nearest-exact)": {"mode": "nearest-exact", "antialias": False}, -} - -sd_upscalers = [] - -clip_model = None - -progress_print_out = sys.stdout - -gradio_theme = gr.themes.Base() - - -def reload_gradio_theme(theme_name=None): - global gradio_theme - if not theme_name: - theme_name = opts.gradio_theme - - default_theme_args = dict( - font=["Source Sans Pro", 'ui-sans-serif', 'system-ui', 'sans-serif'], - font_mono=['IBM Plex Mono', 'ui-monospace', 'Consolas', 'monospace'], - ) - - if theme_name == "Default": - gradio_theme = gr.themes.Default(**default_theme_args) - else: - try: - theme_cache_dir = os.path.join(script_path, 'tmp', 'gradio_themes') - theme_cache_path = os.path.join(theme_cache_dir, f'{theme_name.replace("/", "_")}.json') - if opts.gradio_themes_cache and os.path.exists(theme_cache_path): - gradio_theme = gr.themes.ThemeClass.load(theme_cache_path) - else: - os.makedirs(theme_cache_dir, exist_ok=True) - gradio_theme = gr.themes.ThemeClass.from_hub(theme_name) - gradio_theme.dump(theme_cache_path) - except Exception as e: - errors.display(e, "changing gradio theme") - gradio_theme = gr.themes.Default(**default_theme_args) - - -class TotalTQDM: - def __init__(self): - self._tqdm = None - - def reset(self): - self._tqdm = tqdm.tqdm( - desc="Total progress", - total=state.job_count * state.sampling_steps, - position=1, - file=progress_print_out - ) - - def update(self): - if not opts.multiple_tqdm or cmd_opts.disable_console_progressbars: - return - if self._tqdm is None: - self.reset() - self._tqdm.update() - - def updateTotal(self, new_total): - if not opts.multiple_tqdm or cmd_opts.disable_console_progressbars: - return - if self._tqdm is None: - self.reset() - self._tqdm.total = new_total - - def clear(self): - if self._tqdm is not None: - self._tqdm.refresh() - self._tqdm.close() - self._tqdm = None - - -total_tqdm = TotalTQDM() - -mem_mon = modules.memmon.MemUsageMonitor("MemMon", device, opts) -mem_mon.start() - - -def natural_sort_key(s, regex=re.compile('([0-9]+)')): - return [int(text) if text.isdigit() else text.lower() for text in regex.split(s)] - - -def listfiles(dirname): - filenames = [os.path.join(dirname, x) for x in sorted(os.listdir(dirname), key=natural_sort_key) if not x.startswith(".")] - return [file for file in filenames if os.path.isfile(file)] - - -def html_path(filename): - return os.path.join(script_path, "html", filename) - - -def html(filename): - path = html_path(filename) - - if os.path.exists(path): - with open(path, encoding="utf8") as file: - return file.read() - - return "" - - -def walk_files(path, allowed_extensions=None): - if not os.path.exists(path): - return - - if allowed_extensions is not None: - allowed_extensions = set(allowed_extensions) - - items = list(os.walk(path, followlinks=True)) - items = sorted(items, key=lambda x: natural_sort_key(x[0])) - - for root, _, files in items: - for filename in sorted(files, key=natural_sort_key): - if allowed_extensions is not None: - _, ext = os.path.splitext(filename) - if ext not in allowed_extensions: - continue - - if not opts.list_hidden_files and ("/." in root or "\\." in root): - continue - - yield os.path.join(root, filename) - - -def ldm_print(*args, **kwargs): - if opts.hide_ldm_prints: - return - - print(*args, **kwargs) diff --git a/modules/shared_state.py b/modules/shared_state.py new file mode 100644 index 000000000..3dc9c7880 --- /dev/null +++ b/modules/shared_state.py @@ -0,0 +1,159 @@ +import datetime +import logging +import threading +import time + +from modules import errors, shared, devices +from typing import Optional + +log = logging.getLogger(__name__) + + +class State: + skipped = False + interrupted = False + job = "" + job_no = 0 + job_count = 0 + processing_has_refined_job_count = False + job_timestamp = '0' + sampling_step = 0 + sampling_steps = 0 + current_latent = None + current_image = None + current_image_sampling_step = 0 + id_live_preview = 0 + textinfo = None + time_start = None + server_start = None + _server_command_signal = threading.Event() + _server_command: Optional[str] = None + + def __init__(self): + self.server_start = time.time() + + @property + def need_restart(self) -> bool: + # Compatibility getter for need_restart. + return self.server_command == "restart" + + @need_restart.setter + def need_restart(self, value: bool) -> None: + # Compatibility setter for need_restart. + if value: + self.server_command = "restart" + + @property + def server_command(self): + return self._server_command + + @server_command.setter + def server_command(self, value: Optional[str]) -> None: + """ + Set the server command to `value` and signal that it's been set. + """ + self._server_command = value + self._server_command_signal.set() + + def wait_for_server_command(self, timeout: Optional[float] = None) -> Optional[str]: + """ + Wait for server command to get set; return and clear the value and signal. + """ + if self._server_command_signal.wait(timeout): + self._server_command_signal.clear() + req = self._server_command + self._server_command = None + return req + return None + + def request_restart(self) -> None: + self.interrupt() + self.server_command = "restart" + log.info("Received restart request") + + def skip(self): + self.skipped = True + log.info("Received skip request") + + def interrupt(self): + self.interrupted = True + log.info("Received interrupt request") + + def nextjob(self): + if shared.opts.live_previews_enable and shared.opts.show_progress_every_n_steps == -1: + self.do_set_current_image() + + self.job_no += 1 + self.sampling_step = 0 + self.current_image_sampling_step = 0 + + def dict(self): + obj = { + "skipped": self.skipped, + "interrupted": self.interrupted, + "job": self.job, + "job_count": self.job_count, + "job_timestamp": self.job_timestamp, + "job_no": self.job_no, + "sampling_step": self.sampling_step, + "sampling_steps": self.sampling_steps, + } + + return obj + + def begin(self, job: str = "(unknown)"): + self.sampling_step = 0 + self.job_count = -1 + self.processing_has_refined_job_count = False + self.job_no = 0 + self.job_timestamp = datetime.datetime.now().strftime("%Y%m%d%H%M%S") + self.current_latent = None + self.current_image = None + self.current_image_sampling_step = 0 + self.id_live_preview = 0 + self.skipped = False + self.interrupted = False + self.textinfo = None + self.time_start = time.time() + self.job = job + devices.torch_gc() + log.info("Starting job %s", job) + + def end(self): + duration = time.time() - self.time_start + log.info("Ending job %s (%.2f seconds)", self.job, duration) + self.job = "" + self.job_count = 0 + + devices.torch_gc() + + def set_current_image(self): + """sets self.current_image from self.current_latent if enough sampling steps have been made after the last call to this""" + if not shared.parallel_processing_allowed: + return + + if self.sampling_step - self.current_image_sampling_step >= shared.opts.show_progress_every_n_steps and shared.opts.live_previews_enable and shared.opts.show_progress_every_n_steps != -1: + self.do_set_current_image() + + def do_set_current_image(self): + if self.current_latent is None: + return + + import modules.sd_samplers + + try: + if shared.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 + self.id_live_preview += 1 diff --git a/modules/shared_total_tqdm.py b/modules/shared_total_tqdm.py new file mode 100644 index 000000000..cf82e1047 --- /dev/null +++ b/modules/shared_total_tqdm.py @@ -0,0 +1,37 @@ +import tqdm + +from modules import shared + + +class TotalTQDM: + def __init__(self): + self._tqdm = None + + def reset(self): + self._tqdm = tqdm.tqdm( + desc="Total progress", + total=shared.state.job_count * shared.state.sampling_steps, + position=1, + file=shared.progress_print_out + ) + + def update(self): + if not shared.opts.multiple_tqdm or shared.cmd_opts.disable_console_progressbars: + return + if self._tqdm is None: + self.reset() + self._tqdm.update() + + def updateTotal(self, new_total): + if not shared.opts.multiple_tqdm or shared.cmd_opts.disable_console_progressbars: + return + if self._tqdm is None: + self.reset() + self._tqdm.total = new_total + + def clear(self): + if self._tqdm is not None: + self._tqdm.refresh() + self._tqdm.close() + self._tqdm = None + diff --git a/modules/sysinfo.py b/modules/sysinfo.py index cf24c6dd4..7d906e1fe 100644 --- a/modules/sysinfo.py +++ b/modules/sysinfo.py @@ -10,7 +10,7 @@ import psutil import re import launch -from modules import paths_internal, timer +from modules import paths_internal, timer, shared, extensions, errors checksum_token = "DontStealMyGamePlz__WINNERS_DONT_USE_DRUGS__DONT_COPY_THAT_FLOPPY" environment_whitelist = { @@ -115,8 +115,6 @@ def format_exception(e, tb): def get_exceptions(): try: - from modules import errors - return list(reversed(errors.exception_records)) except Exception as e: return str(e) @@ -142,8 +140,6 @@ def get_torch_sysinfo(): def get_extensions(*, enabled): try: - from modules import extensions - def to_json(x: extensions.Extension): return { "name": x.name, @@ -160,7 +156,6 @@ def get_extensions(*, enabled): def get_config(): try: - from modules import shared return shared.opts.data except Exception as e: return str(e) diff --git a/modules/ui.py b/modules/ui.py index e3753e970..30b80417e 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -13,7 +13,7 @@ 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, sd_samplers +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, sd_samplers, processing, devices, ui_extra_networks from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML from modules.paths import script_path from modules.ui_common import create_refresh_button @@ -91,8 +91,6 @@ def send_gradio_gallery_to_image(x): def calc_resolution_hires(enable, width, height, hr_scale, hr_resize_x, hr_resize_y): - from modules import processing, devices - if not enable: return "" @@ -630,7 +628,6 @@ def create_ui(): toprow.token_button.click(fn=wrap_queued_call(update_token_counter), inputs=[toprow.prompt, steps], outputs=[toprow.token_counter]) toprow.negative_token_button.click(fn=wrap_queued_call(update_token_counter), inputs=[toprow.negative_prompt, steps], outputs=[toprow.negative_token_counter]) - from modules import ui_extra_networks extra_networks_ui = ui_extra_networks.create_ui(txt2img_interface, [txt2img_generation_tab], 'txt2img') ui_extra_networks.setup_ui(extra_networks_ui, txt2img_gallery) @@ -995,7 +992,6 @@ def create_ui(): paste_button=toprow.paste, tabname="img2img", source_text_component=toprow.prompt, source_image_component=None, )) - from modules import ui_extra_networks extra_networks_ui_img2img = ui_extra_networks.create_ui(img2img_interface, [img2img_generation_tab], 'img2img') ui_extra_networks.setup_ui(extra_networks_ui_img2img, img2img_gallery) diff --git a/modules/ui_common.py b/modules/ui_common.py index 303af9cd7..99d19ff01 100644 --- a/modules/ui_common.py +++ b/modules/ui_common.py @@ -11,7 +11,7 @@ from modules import call_queue, shared from modules.generation_parameters_copypaste import image_from_url_text import modules.images from modules.ui_components import ToolButton - +import modules.generation_parameters_copypaste as parameters_copypaste folder_symbol = '\U0001f4c2' # 📂 refresh_symbol = '\U0001f504' # 🔄 @@ -105,8 +105,6 @@ def save_files(js_data, images, do_make_zip, index): def create_output_panel(tabname, outdir): - from modules import shared - import modules.generation_parameters_copypaste as parameters_copypaste def open_folder(f): if not os.path.exists(f): diff --git a/modules/util.py b/modules/util.py new file mode 100644 index 000000000..60afc0670 --- /dev/null +++ b/modules/util.py @@ -0,0 +1,58 @@ +import os +import re + +from modules import shared +from modules.paths_internal import script_path + + +def natural_sort_key(s, regex=re.compile('([0-9]+)')): + return [int(text) if text.isdigit() else text.lower() for text in regex.split(s)] + + +def listfiles(dirname): + filenames = [os.path.join(dirname, x) for x in sorted(os.listdir(dirname), key=natural_sort_key) if not x.startswith(".")] + return [file for file in filenames if os.path.isfile(file)] + + +def html_path(filename): + return os.path.join(script_path, "html", filename) + + +def html(filename): + path = html_path(filename) + + if os.path.exists(path): + with open(path, encoding="utf8") as file: + return file.read() + + return "" + + +def walk_files(path, allowed_extensions=None): + if not os.path.exists(path): + return + + if allowed_extensions is not None: + allowed_extensions = set(allowed_extensions) + + items = list(os.walk(path, followlinks=True)) + items = sorted(items, key=lambda x: natural_sort_key(x[0])) + + for root, _, files in items: + for filename in sorted(files, key=natural_sort_key): + if allowed_extensions is not None: + _, ext = os.path.splitext(filename) + if ext not in allowed_extensions: + continue + + if not shared.opts.list_hidden_files and ("/." in root or "\\." in root): + continue + + yield os.path.join(root, filename) + + +def ldm_print(*args, **kwargs): + if shared.opts.hide_ldm_prints: + return + + print(*args, **kwargs) diff --git a/webui.py b/webui.py index 6d36f8806..0f1ace97a 100644 --- a/webui.py +++ b/webui.py @@ -43,12 +43,15 @@ startup_timer.record("import torch") import gradio # noqa: F401 startup_timer.record("import gradio") -from modules import paths, timer, import_hook, errors, devices # noqa: F401 +from modules import paths, timer, import_hook, errors # noqa: F401 startup_timer.record("setup paths") import ldm.modules.encoders.modules # noqa: F401 startup_timer.record("import ldm") +from modules import shared_init, shared, shared_items +shared_init.initialize() +startup_timer.record("initialize shared") from modules import extra_networks from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, queue_lock # noqa: F401 @@ -58,8 +61,6 @@ if ".dev" in torch.__version__ or "+git" in torch.__version__: torch.__long_version__ = torch.__version__ torch.__version__ = re.search(r'[\d.]+[\d]', torch.__version__).group(0) -from modules import shared - if not shared.cmd_opts.skip_version_check: errors.check_versions() @@ -82,7 +83,7 @@ import modules.textual_inversion.textual_inversion import modules.progress import modules.ui -from modules import modelloader +from modules import modelloader, devices from modules.shared import cmd_opts import modules.hypernetworks.hypernetwork @@ -297,7 +298,7 @@ def initialize_rest(*, reload_script_modules=False): Thread(target=load_model).start() - shared.reload_hypernetworks() + shared_items.reload_hypernetworks() startup_timer.record("reload hypernetworks") ui_extra_networks.initialize() From 0cac6ab6153dc376b55c9b7f61c01024515ae73a Mon Sep 17 00:00:00 2001 From: w-e-w <40751091+w-e-w@users.noreply.github.com> Date: Wed, 9 Aug 2023 20:32:36 +0900 Subject: [PATCH 19/43] extra network metadata inherit old description --- modules/ui_extra_networks_user_metadata.py | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/modules/ui_extra_networks_user_metadata.py b/modules/ui_extra_networks_user_metadata.py index ea7e1ab20..a5423fd85 100644 --- a/modules/ui_extra_networks_user_metadata.py +++ b/modules/ui_extra_networks_user_metadata.py @@ -36,12 +36,10 @@ class UserMetadataEditor: item = self.page.items.get(name, {}) user_metadata = item.get('user_metadata', None) - if user_metadata is None: - user_metadata = {} + if not user_metadata: + user_metadata = {'description': item.get('description', '')} item['user_metadata'] = user_metadata - if len(user_metadata) == 0: - user_metadata = {'description': item.get('description', '')} return user_metadata def create_extra_default_items_in_left_column(self): From aa10faa591f1ca0bd93ae3d53a0a4c15a3fbaf82 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Wed, 9 Aug 2023 14:47:44 +0300 Subject: [PATCH 20/43] fix checkpoint name jumping around in the list of checkpoints for no good reason --- modules/sd_models.py | 12 +++++++++--- 1 file changed, 9 insertions(+), 3 deletions(-) diff --git a/modules/sd_models.py b/modules/sd_models.py index b490fa992..7a866a07d 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -68,7 +68,9 @@ class CheckpointInfo: 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, self.name_for_extra, f'{name} [{self.hash}]'] + ([self.shorthash, self.sha256, f'{self.name} [{self.shorthash}]'] if self.shorthash else []) + self.ids = [self.hash, self.model_name, self.title, name, self.name_for_extra, f'{name} [{self.hash}]'] + if self.shorthash: + self.ids += [self.shorthash, self.sha256, f'{self.name} [{self.shorthash}]', f'{self.name_for_extra} [{self.shorthash}]'] def register(self): checkpoints_list[self.title] = self @@ -80,10 +82,14 @@ class CheckpointInfo: if self.sha256 is None: return - self.shorthash = self.sha256[0:10] + shorthash = self.sha256[0:10] + if self.shorthash == self.sha256[0:10]: + return self.shorthash + + self.shorthash = shorthash if self.shorthash not in self.ids: - self.ids += [self.shorthash, self.sha256, f'{self.name} [{self.shorthash}]'] + self.ids += [self.shorthash, self.sha256, f'{self.name} [{self.shorthash}]', f'{self.name_for_extra} [{self.shorthash}]'] checkpoints_list.pop(self.title, None) self.title = f'{self.name} [{self.shorthash}]' From 7ba8f11688bee1a04b48d8108627fd25ada69721 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Wed, 9 Aug 2023 15:06:03 +0300 Subject: [PATCH 21/43] fix missing restricted_opts from shared --- modules/shared.py | 1 + modules/shared_init.py | 1 + 2 files changed, 2 insertions(+) diff --git a/modules/shared.py b/modules/shared.py index 8ba72f495..d9d014845 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -38,6 +38,7 @@ face_restorers = [] options_templates = None opts = None +restricted_opts = None sd_model: LatentDiffusion = None diff --git a/modules/shared_init.py b/modules/shared_init.py index e7fc18d2d..b88d1d8e7 100644 --- a/modules/shared_init.py +++ b/modules/shared_init.py @@ -20,6 +20,7 @@ def initialize(): from modules import options, shared_options shared.options_templates = shared_options.options_templates shared.opts = options.Options(shared_options.options_templates, shared_options.restricted_opts) + shared.restricted_opts = shared_options.restricted_opts if os.path.exists(shared.config_filename): shared.opts.load(shared.config_filename) From eed963e97261ee03bffe59e3d343dcf53d82dbfd Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Wed, 9 Aug 2023 16:54:49 +0300 Subject: [PATCH 22/43] Lora cache in memory --- extensions-builtin/Lora/networks.py | 22 ++++++++++++++++--- .../Lora/scripts/lora_script.py | 3 +++ 2 files changed, 22 insertions(+), 3 deletions(-) diff --git a/extensions-builtin/Lora/networks.py b/extensions-builtin/Lora/networks.py index 17cbe1bb7..bc722e90c 100644 --- a/extensions-builtin/Lora/networks.py +++ b/extensions-builtin/Lora/networks.py @@ -195,6 +195,15 @@ def load_network(name, network_on_disk): return net +def purge_networks_from_memory(): + while len(networks_in_memory) > shared.opts.lora_in_memory_limit and len(networks_in_memory) > 0: + name = next(iter(networks_in_memory)) + networks_in_memory.pop(name, None) + + devices.torch_gc() + + + def load_networks(names, te_multipliers=None, unet_multipliers=None, dyn_dims=None): already_loaded = {} @@ -212,15 +221,19 @@ def load_networks(names, te_multipliers=None, unet_multipliers=None, dyn_dims=No failed_to_load_networks = [] - for i, name in enumerate(names): + for i, (network_on_disk, name) in enumerate(zip(networks_on_disk, names)): net = already_loaded.get(name, None) - network_on_disk = networks_on_disk[i] - if network_on_disk is not None: + if net is None: + net = networks_in_memory.get(name) + if net is None or os.path.getmtime(network_on_disk.filename) > net.mtime: try: net = load_network(name, network_on_disk) + + networks_in_memory.pop(name, None) + networks_in_memory[name] = net except Exception as e: errors.display(e, f"loading network {network_on_disk.filename}") continue @@ -242,6 +255,8 @@ def load_networks(names, te_multipliers=None, unet_multipliers=None, dyn_dims=No if failed_to_load_networks: sd_hijack.model_hijack.comments.append("Failed to find networks: " + ", ".join(failed_to_load_networks)) + purge_networks_from_memory() + def network_restore_weights_from_backup(self: Union[torch.nn.Conv2d, torch.nn.Linear, torch.nn.MultiheadAttention]): weights_backup = getattr(self, "network_weights_backup", None) @@ -462,6 +477,7 @@ def infotext_pasted(infotext, params): available_networks = {} available_network_aliases = {} loaded_networks = [] +networks_in_memory = {} available_network_hash_lookup = {} forbidden_network_aliases = {} diff --git a/extensions-builtin/Lora/scripts/lora_script.py b/extensions-builtin/Lora/scripts/lora_script.py index cd28afc92..6ab8b6e7c 100644 --- a/extensions-builtin/Lora/scripts/lora_script.py +++ b/extensions-builtin/Lora/scripts/lora_script.py @@ -65,6 +65,7 @@ shared.options_templates.update(shared.options_section(('extra_networks', "Extra "lora_add_hashes_to_infotext": shared.OptionInfo(True, "Add Lora hashes to infotext"), "lora_show_all": shared.OptionInfo(False, "Always show all networks on the Lora page").info("otherwise, those detected as for incompatible version of Stable Diffusion will be hidden"), "lora_hide_unknown_for_versions": shared.OptionInfo([], "Hide networks of unknown versions for model versions", gr.CheckboxGroup, {"choices": ["SD1", "SD2", "SDXL"]}), + "lora_in_memory_limit": shared.OptionInfo(0, "Number of Lora networks to keep cached in memory", gr.Number, {"precision": 0}), })) @@ -121,3 +122,5 @@ def infotext_pasted(infotext, d): script_callbacks.on_infotext_pasted(infotext_pasted) + +shared.opts.onchange("lora_in_memory_limit", networks.purge_networks_from_memory) From a2a97e57f069d24c9616d1867a6df7f532f92a04 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Wed, 9 Aug 2023 17:08:36 +0300 Subject: [PATCH 23/43] simplify --- modules/launch_utils.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/modules/launch_utils.py b/modules/launch_utils.py index c0847e14e..98ac5bbdc 100644 --- a/modules/launch_utils.py +++ b/modules/launch_utils.py @@ -7,6 +7,7 @@ import importlib.util import platform import json from functools import lru_cache +import tqdm from modules import cmd_args, errors from modules.paths_internal import script_path, extensions_dir @@ -248,11 +249,10 @@ def run_extensions_installers(settings_file): return with startup_timer.subcategory("run extensions installers"): - from tqdm.auto import tqdm - pbar_extensions = tqdm(list_extensions(settings_file), - bar_format="{desc}: |{bar}|{percentage:3.0f}% [{n_fmt}/{total_fmt} {elapsed}<{remaining}]") - for dirname_extension in pbar_extensions: - pbar_extensions.set_description("Installing %s" % dirname_extension) + progress_bar = tqdm.tqdm(list_extensions(settings_file)) + for dirname_extension in progress_bar: + progress_bar.set_description(f"Installing {dirname_extension}") + path = os.path.join(extensions_dir, dirname_extension) if os.path.isdir(path): From 95821f0132f5437ef30b0dbcac7c51e55818c18f Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Wed, 9 Aug 2023 18:11:13 +0300 Subject: [PATCH 24/43] split webui.py's initialization and utility functions into separate files --- modules/gradio_extensons.py | 4 +- modules/initialize.py | 168 ++++++++++++++++ modules/initialize_util.py | 195 +++++++++++++++++++ modules/shared_init.py | 3 - modules/ui_extra_networks.py | 3 +- modules/ui_tempdir.py | 5 +- webui.py | 368 ++++------------------------------- 7 files changed, 405 insertions(+), 341 deletions(-) create mode 100644 modules/initialize.py create mode 100644 modules/initialize_util.py diff --git a/modules/gradio_extensons.py b/modules/gradio_extensons.py index 5af7fd8ec..77c34c8ba 100644 --- a/modules/gradio_extensons.py +++ b/modules/gradio_extensons.py @@ -1,6 +1,6 @@ import gradio as gr -from modules import scripts +from modules import scripts, ui_tempdir def add_classes_to_gradio_component(comp): """ @@ -58,3 +58,5 @@ 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 + +ui_tempdir.install_ui_tempdir_override() diff --git a/modules/initialize.py b/modules/initialize.py new file mode 100644 index 000000000..f24f76375 --- /dev/null +++ b/modules/initialize.py @@ -0,0 +1,168 @@ +import importlib +import logging +import sys +import warnings +from threading import Thread + +from modules.timer import startup_timer + + +def imports(): + logging.getLogger("torch.distributed.nn").setLevel(logging.ERROR) # sshh... + logging.getLogger("xformers").addFilter(lambda record: 'A matching Triton is not available' not in record.getMessage()) + + import torch # noqa: F401 + startup_timer.record("import torch") + import pytorch_lightning # noqa: F401 + startup_timer.record("import torch") + warnings.filterwarnings(action="ignore", category=DeprecationWarning, module="pytorch_lightning") + warnings.filterwarnings(action="ignore", category=UserWarning, module="torchvision") + + import gradio # noqa: F401 + startup_timer.record("import gradio") + + from modules import paths, timer, import_hook, errors # noqa: F401 + startup_timer.record("setup paths") + + import ldm.modules.encoders.modules # noqa: F401 + startup_timer.record("import ldm") + + import sgm.modules.encoders.modules # noqa: F401 + startup_timer.record("import sgm") + + from modules import shared_init + shared_init.initialize() + startup_timer.record("initialize shared") + + from modules import processing, gradio_extensons, ui # noqa: F401 + startup_timer.record("other imports") + + +def check_versions(): + from modules.shared_cmd_options import cmd_opts + + if not cmd_opts.skip_version_check: + from modules import errors + errors.check_versions() + + +def initialize(): + from modules import initialize_util + initialize_util.fix_torch_version() + initialize_util.fix_asyncio_event_loop_policy() + initialize_util.validate_tls_options() + initialize_util.configure_sigint_handler() + initialize_util.configure_opts_onchange() + + from modules import modelloader + modelloader.cleanup_models() + + from modules import sd_models + sd_models.setup_model() + startup_timer.record("setup SD model") + + from modules.shared_cmd_options import cmd_opts + + from modules import codeformer_model + warnings.filterwarnings(action="ignore", category=UserWarning, module="torchvision.transforms.functional_tensor") + codeformer_model.setup_model(cmd_opts.codeformer_models_path) + startup_timer.record("setup codeformer") + + from modules import gfpgan_model + gfpgan_model.setup_model(cmd_opts.gfpgan_models_path) + startup_timer.record("setup gfpgan") + + initialize_rest(reload_script_modules=False) + + +def initialize_rest(*, reload_script_modules=False): + """ + Called both from initialize() and when reloading the webui. + """ + from modules.shared_cmd_options import cmd_opts + + from modules import sd_samplers + sd_samplers.set_samplers() + startup_timer.record("set samplers") + + from modules import extensions + extensions.list_extensions() + startup_timer.record("list extensions") + + from modules import initialize_util + initialize_util.restore_config_state_file() + startup_timer.record("restore config state file") + + from modules import shared, upscaler, scripts + if cmd_opts.ui_debug_mode: + shared.sd_upscalers = upscaler.UpscalerLanczos().scalers + scripts.load_scripts() + return + + from modules import sd_models + sd_models.list_models() + startup_timer.record("list SD models") + + from modules import localization + localization.list_localizations(cmd_opts.localizations_dir) + startup_timer.record("list localizations") + + with startup_timer.subcategory("load scripts"): + scripts.load_scripts() + + if reload_script_modules: + for module in [module for name, module in sys.modules.items() if name.startswith("modules.ui")]: + importlib.reload(module) + startup_timer.record("reload script modules") + + from modules import modelloader + modelloader.load_upscalers() + startup_timer.record("load upscalers") + + from modules import sd_vae + sd_vae.refresh_vae_list() + startup_timer.record("refresh VAE") + + from modules import textual_inversion + textual_inversion.textual_inversion.list_textual_inversion_templates() + startup_timer.record("refresh textual inversion templates") + + from modules import script_callbacks, sd_hijack_optimizations, sd_hijack + script_callbacks.on_list_optimizers(sd_hijack_optimizations.list_optimizers) + sd_hijack.list_optimizers() + startup_timer.record("scripts list_optimizers") + + from modules import sd_unet + sd_unet.list_unets() + startup_timer.record("scripts list_unets") + + def load_model(): + """ + Accesses shared.sd_model property to load model. + After it's available, if it has been loaded before this access by some extension, + its optimization may be None because the list of optimizaers has neet been filled + by that time, so we apply optimization again. + """ + + shared.sd_model # noqa: B018 + + if sd_hijack.current_optimizer is None: + sd_hijack.apply_optimizations() + + from modules import devices + devices.first_time_calculation() + + Thread(target=load_model).start() + + from modules import shared_items + shared_items.reload_hypernetworks() + startup_timer.record("reload hypernetworks") + + from modules import ui_extra_networks + ui_extra_networks.initialize() + ui_extra_networks.register_default_pages() + + from modules import extra_networks + extra_networks.initialize() + extra_networks.register_default_extra_networks() + startup_timer.record("initialize extra networks") diff --git a/modules/initialize_util.py b/modules/initialize_util.py new file mode 100644 index 000000000..e59bd3c49 --- /dev/null +++ b/modules/initialize_util.py @@ -0,0 +1,195 @@ +import json +import logging +import os +import signal +import sys +import re + +from modules.timer import startup_timer + +def setup_logging(): + # We can't use cmd_opts for this because it will not have been initialized at this point. + log_level = os.environ.get("SD_WEBUI_LOG_LEVEL") + if log_level: + log_level = getattr(logging, log_level.upper(), None) or logging.INFO + logging.basicConfig( + level=log_level, + format='%(asctime)s %(levelname)s [%(name)s] %(message)s', + datefmt='%Y-%m-%d %H:%M:%S', + ) + + +def gradio_server_name(): + from modules.shared_cmd_options import cmd_opts + + if cmd_opts.server_name: + return cmd_opts.server_name + else: + return "0.0.0.0" if cmd_opts.listen else None + + +def fix_torch_version(): + import torch + + # Truncate version number of nightly/local build of PyTorch to not cause exceptions with CodeFormer or Safetensors + if ".dev" in torch.__version__ or "+git" in torch.__version__: + torch.__long_version__ = torch.__version__ + torch.__version__ = re.search(r'[\d.]+[\d]', torch.__version__).group(0) + + +def fix_asyncio_event_loop_policy(): + """ + The default `asyncio` event loop policy only automatically creates + event loops in the main threads. Other threads must create event + loops explicitly or `asyncio.get_event_loop` (and therefore + `.IOLoop.current`) will fail. Installing this policy allows event + loops to be created automatically on any thread, matching the + behavior of Tornado versions prior to 5.0 (or 5.0 on Python 2). + """ + + import asyncio + + if sys.platform == "win32" and hasattr(asyncio, "WindowsSelectorEventLoopPolicy"): + # "Any thread" and "selector" should be orthogonal, but there's not a clean + # interface for composing policies so pick the right base. + _BasePolicy = asyncio.WindowsSelectorEventLoopPolicy # type: ignore + else: + _BasePolicy = asyncio.DefaultEventLoopPolicy + + class AnyThreadEventLoopPolicy(_BasePolicy): # type: ignore + """Event loop policy that allows loop creation on any thread. + Usage:: + + asyncio.set_event_loop_policy(AnyThreadEventLoopPolicy()) + """ + + def get_event_loop(self) -> asyncio.AbstractEventLoop: + try: + return super().get_event_loop() + except (RuntimeError, AssertionError): + # This was an AssertionError in python 3.4.2 (which ships with debian jessie) + # and changed to a RuntimeError in 3.4.3. + # "There is no current event loop in thread %r" + loop = self.new_event_loop() + self.set_event_loop(loop) + return loop + + asyncio.set_event_loop_policy(AnyThreadEventLoopPolicy()) + + +def restore_config_state_file(): + from modules import shared, config_states + + config_state_file = shared.opts.restore_config_state_file + if config_state_file == "": + return + + shared.opts.restore_config_state_file = "" + shared.opts.save(shared.config_filename) + + if os.path.isfile(config_state_file): + print(f"*** About to restore extension state from file: {config_state_file}") + with open(config_state_file, "r", encoding="utf-8") as f: + config_state = json.load(f) + config_states.restore_extension_config(config_state) + startup_timer.record("restore extension config") + elif config_state_file: + print(f"!!! Config state backup not found: {config_state_file}") + + +def validate_tls_options(): + from modules.shared_cmd_options import cmd_opts + + if not (cmd_opts.tls_keyfile and cmd_opts.tls_certfile): + return + + try: + if not os.path.exists(cmd_opts.tls_keyfile): + print("Invalid path to TLS keyfile given") + if not os.path.exists(cmd_opts.tls_certfile): + print(f"Invalid path to TLS certfile: '{cmd_opts.tls_certfile}'") + except TypeError: + cmd_opts.tls_keyfile = cmd_opts.tls_certfile = None + print("TLS setup invalid, running webui without TLS") + else: + print("Running with TLS") + startup_timer.record("TLS") + + +def get_gradio_auth_creds(): + """ + Convert the gradio_auth and gradio_auth_path commandline arguments into + an iterable of (username, password) tuples. + """ + from modules.shared_cmd_options import cmd_opts + + def process_credential_line(s): + s = s.strip() + if not s: + return None + return tuple(s.split(':', 1)) + + if cmd_opts.gradio_auth: + for cred in cmd_opts.gradio_auth.split(','): + cred = process_credential_line(cred) + if cred: + yield cred + + if cmd_opts.gradio_auth_path: + with open(cmd_opts.gradio_auth_path, 'r', encoding="utf8") as file: + for line in file.readlines(): + for cred in line.strip().split(','): + cred = process_credential_line(cred) + if cred: + yield cred + + +def configure_sigint_handler(): + # make the program just exit at ctrl+c without waiting for anything + def sigint_handler(sig, frame): + print(f'Interrupted with signal {sig} in {frame}') + os._exit(0) + + if not os.environ.get("COVERAGE_RUN"): + # Don't install the immediate-quit handler when running under coverage, + # as then the coverage report won't be generated. + signal.signal(signal.SIGINT, sigint_handler) + + +def configure_opts_onchange(): + from modules import shared, sd_models, sd_vae, ui_tempdir, sd_hijack + from modules.call_queue import wrap_queued_call + + shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: sd_models.reload_model_weights()), call=False) + shared.opts.onchange("sd_vae", wrap_queued_call(lambda: sd_vae.reload_vae_weights()), call=False) + shared.opts.onchange("sd_vae_overrides_per_model_preferences", wrap_queued_call(lambda: sd_vae.reload_vae_weights()), call=False) + shared.opts.onchange("temp_dir", ui_tempdir.on_tmpdir_changed) + shared.opts.onchange("gradio_theme", shared.reload_gradio_theme) + shared.opts.onchange("cross_attention_optimization", wrap_queued_call(lambda: sd_hijack.model_hijack.redo_hijack(shared.sd_model)), call=False) + startup_timer.record("opts onchange") + + +def setup_middleware(app): + from starlette.middleware.gzip import GZipMiddleware + + app.middleware_stack = None # reset current middleware to allow modifying user provided list + app.add_middleware(GZipMiddleware, minimum_size=1000) + configure_cors_middleware(app) + app.build_middleware_stack() # rebuild middleware stack on-the-fly + + +def configure_cors_middleware(app): + from starlette.middleware.cors import CORSMiddleware + from modules.shared_cmd_options import cmd_opts + + cors_options = { + "allow_methods": ["*"], + "allow_headers": ["*"], + "allow_credentials": True, + } + if cmd_opts.cors_allow_origins: + cors_options["allow_origins"] = cmd_opts.cors_allow_origins.split(',') + if cmd_opts.cors_allow_origins_regex: + cors_options["allow_origin_regex"] = cmd_opts.cors_allow_origins_regex + app.add_middleware(CORSMiddleware, **cors_options) + diff --git a/modules/shared_init.py b/modules/shared_init.py index b88d1d8e7..d3fb687e0 100644 --- a/modules/shared_init.py +++ b/modules/shared_init.py @@ -5,9 +5,6 @@ import torch from modules import shared from modules.shared import cmd_opts -import sys -sys.setrecursionlimit(1000) - def initialize(): """Initializes fields inside the shared module in a controlled manner. diff --git a/modules/ui_extra_networks.py b/modules/ui_extra_networks.py index e0b932b94..16d76a452 100644 --- a/modules/ui_extra_networks.py +++ b/modules/ui_extra_networks.py @@ -4,7 +4,6 @@ from pathlib import Path from modules import shared, ui_extra_networks_user_metadata, errors, extra_networks from modules.images import read_info_from_image, save_image_with_geninfo -from modules.ui import up_down_symbol import gradio as gr import json import html @@ -348,6 +347,8 @@ def pages_in_preferred_order(pages): def create_ui(interface: gr.Blocks, unrelated_tabs, tabname): + from modules.ui import up_down_symbol + ui = ExtraNetworksUi() ui.pages = [] ui.pages_contents = [] diff --git a/modules/ui_tempdir.py b/modules/ui_tempdir.py index fb75137e6..506017e50 100644 --- a/modules/ui_tempdir.py +++ b/modules/ui_tempdir.py @@ -57,8 +57,9 @@ def save_pil_to_file(self, pil_image, dir=None, format="png"): return file_obj.name -# override save to file function so that it also writes PNG info -gradio.components.IOComponent.pil_to_temp_file = save_pil_to_file +def install_ui_tempdir_override(): + """override save to file function so that it also writes PNG info""" + gradio.components.IOComponent.pil_to_temp_file = save_pil_to_file def on_tmpdir_changed(): diff --git a/webui.py b/webui.py index 0f1ace97a..738b3bef2 100644 --- a/webui.py +++ b/webui.py @@ -1,349 +1,43 @@ from __future__ import annotations import os -import sys import time -import importlib -import signal -import re -import warnings -import json -from threading import Thread -from typing import Iterable - -from fastapi import FastAPI -from fastapi.middleware.cors import CORSMiddleware -from fastapi.middleware.gzip import GZipMiddleware - -import logging - -# We can't use cmd_opts for this because it will not have been initialized at this point. -log_level = os.environ.get("SD_WEBUI_LOG_LEVEL") -if log_level: - log_level = getattr(logging, log_level.upper(), None) or logging.INFO - logging.basicConfig( - level=log_level, - format='%(asctime)s %(levelname)s [%(name)s] %(message)s', - datefmt='%Y-%m-%d %H:%M:%S', - ) - -logging.getLogger("torch.distributed.nn").setLevel(logging.ERROR) # sshh... -logging.getLogger("xformers").addFilter(lambda record: 'A matching Triton is not available' not in record.getMessage()) from modules import timer +from modules import initialize_util +from modules import initialize + startup_timer = timer.startup_timer startup_timer.record("launcher") -import torch -import pytorch_lightning # noqa: F401 # pytorch_lightning should be imported after torch, but it re-enables warnings on import so import once to disable them -warnings.filterwarnings(action="ignore", category=DeprecationWarning, module="pytorch_lightning") -warnings.filterwarnings(action="ignore", category=UserWarning, module="torchvision") -startup_timer.record("import torch") +initialize_util.setup_logging() -import gradio # noqa: F401 -startup_timer.record("import gradio") +initialize.imports() -from modules import paths, timer, import_hook, errors # noqa: F401 -startup_timer.record("setup paths") - -import ldm.modules.encoders.modules # noqa: F401 -startup_timer.record("import ldm") - -from modules import shared_init, shared, shared_items -shared_init.initialize() -startup_timer.record("initialize shared") - -from modules import extra_networks -from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, queue_lock # noqa: F401 - -# Truncate version number of nightly/local build of PyTorch to not cause exceptions with CodeFormer or Safetensors -if ".dev" in torch.__version__ or "+git" in torch.__version__: - torch.__long_version__ = torch.__version__ - torch.__version__ = re.search(r'[\d.]+[\d]', torch.__version__).group(0) - -if not shared.cmd_opts.skip_version_check: - errors.check_versions() - -import modules.codeformer_model as codeformer -import modules.gfpgan_model as gfpgan -from modules import sd_samplers, upscaler, extensions, localization, ui_tempdir, ui_extra_networks, config_states -import modules.face_restoration -import modules.img2img - -import modules.lowvram -import modules.scripts -import modules.sd_hijack -import modules.sd_hijack_optimizations -import modules.sd_models -import modules.sd_vae -import modules.sd_unet -import modules.txt2img -import modules.script_callbacks -import modules.textual_inversion.textual_inversion -import modules.progress - -import modules.ui -from modules import modelloader, devices -from modules.shared import cmd_opts -import modules.hypernetworks.hypernetwork - -startup_timer.record("other imports") - - -if cmd_opts.server_name: - server_name = cmd_opts.server_name -else: - server_name = "0.0.0.0" if cmd_opts.listen else None - - -def fix_asyncio_event_loop_policy(): - """ - The default `asyncio` event loop policy only automatically creates - event loops in the main threads. Other threads must create event - loops explicitly or `asyncio.get_event_loop` (and therefore - `.IOLoop.current`) will fail. Installing this policy allows event - loops to be created automatically on any thread, matching the - behavior of Tornado versions prior to 5.0 (or 5.0 on Python 2). - """ - - import asyncio - - if sys.platform == "win32" and hasattr(asyncio, "WindowsSelectorEventLoopPolicy"): - # "Any thread" and "selector" should be orthogonal, but there's not a clean - # interface for composing policies so pick the right base. - _BasePolicy = asyncio.WindowsSelectorEventLoopPolicy # type: ignore - else: - _BasePolicy = asyncio.DefaultEventLoopPolicy - - class AnyThreadEventLoopPolicy(_BasePolicy): # type: ignore - """Event loop policy that allows loop creation on any thread. - Usage:: - - asyncio.set_event_loop_policy(AnyThreadEventLoopPolicy()) - """ - - def get_event_loop(self) -> asyncio.AbstractEventLoop: - try: - return super().get_event_loop() - except (RuntimeError, AssertionError): - # This was an AssertionError in python 3.4.2 (which ships with debian jessie) - # and changed to a RuntimeError in 3.4.3. - # "There is no current event loop in thread %r" - loop = self.new_event_loop() - self.set_event_loop(loop) - return loop - - asyncio.set_event_loop_policy(AnyThreadEventLoopPolicy()) - - -def restore_config_state_file(): - config_state_file = shared.opts.restore_config_state_file - if config_state_file == "": - return - - shared.opts.restore_config_state_file = "" - shared.opts.save(shared.config_filename) - - if os.path.isfile(config_state_file): - print(f"*** About to restore extension state from file: {config_state_file}") - with open(config_state_file, "r", encoding="utf-8") as f: - config_state = json.load(f) - config_states.restore_extension_config(config_state) - startup_timer.record("restore extension config") - elif config_state_file: - print(f"!!! Config state backup not found: {config_state_file}") - - -def validate_tls_options(): - if not (cmd_opts.tls_keyfile and cmd_opts.tls_certfile): - return - - try: - if not os.path.exists(cmd_opts.tls_keyfile): - print("Invalid path to TLS keyfile given") - if not os.path.exists(cmd_opts.tls_certfile): - print(f"Invalid path to TLS certfile: '{cmd_opts.tls_certfile}'") - except TypeError: - cmd_opts.tls_keyfile = cmd_opts.tls_certfile = None - print("TLS setup invalid, running webui without TLS") - else: - print("Running with TLS") - startup_timer.record("TLS") - - -def get_gradio_auth_creds() -> Iterable[tuple[str, ...]]: - """ - Convert the gradio_auth and gradio_auth_path commandline arguments into - an iterable of (username, password) tuples. - """ - def process_credential_line(s) -> tuple[str, ...] | None: - s = s.strip() - if not s: - return None - return tuple(s.split(':', 1)) - - if cmd_opts.gradio_auth: - for cred in cmd_opts.gradio_auth.split(','): - cred = process_credential_line(cred) - if cred: - yield cred - - if cmd_opts.gradio_auth_path: - with open(cmd_opts.gradio_auth_path, 'r', encoding="utf8") as file: - for line in file.readlines(): - for cred in line.strip().split(','): - cred = process_credential_line(cred) - if cred: - yield cred - - -def configure_sigint_handler(): - # make the program just exit at ctrl+c without waiting for anything - def sigint_handler(sig, frame): - print(f'Interrupted with signal {sig} in {frame}') - os._exit(0) - - if not os.environ.get("COVERAGE_RUN"): - # Don't install the immediate-quit handler when running under coverage, - # as then the coverage report won't be generated. - signal.signal(signal.SIGINT, sigint_handler) - - -def configure_opts_onchange(): - shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights()), call=False) - shared.opts.onchange("sd_vae", wrap_queued_call(lambda: modules.sd_vae.reload_vae_weights()), call=False) - shared.opts.onchange("sd_vae_overrides_per_model_preferences", wrap_queued_call(lambda: modules.sd_vae.reload_vae_weights()), call=False) - shared.opts.onchange("temp_dir", ui_tempdir.on_tmpdir_changed) - shared.opts.onchange("gradio_theme", shared.reload_gradio_theme) - shared.opts.onchange("cross_attention_optimization", wrap_queued_call(lambda: modules.sd_hijack.model_hijack.redo_hijack(shared.sd_model)), call=False) - startup_timer.record("opts onchange") - - -def initialize(): - fix_asyncio_event_loop_policy() - validate_tls_options() - configure_sigint_handler() - modelloader.cleanup_models() - configure_opts_onchange() - - modules.sd_models.setup_model() - startup_timer.record("setup SD model") - - codeformer.setup_model(cmd_opts.codeformer_models_path) - startup_timer.record("setup codeformer") - - gfpgan.setup_model(cmd_opts.gfpgan_models_path) - startup_timer.record("setup gfpgan") - - initialize_rest(reload_script_modules=False) - - -def initialize_rest(*, reload_script_modules=False): - """ - Called both from initialize() and when reloading the webui. - """ - sd_samplers.set_samplers() - extensions.list_extensions() - startup_timer.record("list extensions") - - restore_config_state_file() - - if cmd_opts.ui_debug_mode: - shared.sd_upscalers = upscaler.UpscalerLanczos().scalers - modules.scripts.load_scripts() - return - - modules.sd_models.list_models() - startup_timer.record("list SD models") - - localization.list_localizations(cmd_opts.localizations_dir) - - with startup_timer.subcategory("load scripts"): - modules.scripts.load_scripts() - - if reload_script_modules: - for module in [module for name, module in sys.modules.items() if name.startswith("modules.ui")]: - importlib.reload(module) - startup_timer.record("reload script modules") - - modelloader.load_upscalers() - startup_timer.record("load upscalers") - - modules.sd_vae.refresh_vae_list() - startup_timer.record("refresh VAE") - modules.textual_inversion.textual_inversion.list_textual_inversion_templates() - startup_timer.record("refresh textual inversion templates") - - modules.script_callbacks.on_list_optimizers(modules.sd_hijack_optimizations.list_optimizers) - modules.sd_hijack.list_optimizers() - startup_timer.record("scripts list_optimizers") - - modules.sd_unet.list_unets() - startup_timer.record("scripts list_unets") - - def load_model(): - """ - Accesses shared.sd_model property to load model. - After it's available, if it has been loaded before this access by some extension, - its optimization may be None because the list of optimizaers has neet been filled - by that time, so we apply optimization again. - """ - - shared.sd_model # noqa: B018 - - if modules.sd_hijack.current_optimizer is None: - modules.sd_hijack.apply_optimizations() - - devices.first_time_calculation() - - Thread(target=load_model).start() - - shared_items.reload_hypernetworks() - startup_timer.record("reload hypernetworks") - - ui_extra_networks.initialize() - ui_extra_networks.register_default_pages() - - extra_networks.initialize() - extra_networks.register_default_extra_networks() - startup_timer.record("initialize extra networks") - - -def setup_middleware(app): - app.middleware_stack = None # reset current middleware to allow modifying user provided list - app.add_middleware(GZipMiddleware, minimum_size=1000) - configure_cors_middleware(app) - app.build_middleware_stack() # rebuild middleware stack on-the-fly - - -def configure_cors_middleware(app): - cors_options = { - "allow_methods": ["*"], - "allow_headers": ["*"], - "allow_credentials": True, - } - if cmd_opts.cors_allow_origins: - cors_options["allow_origins"] = cmd_opts.cors_allow_origins.split(',') - if cmd_opts.cors_allow_origins_regex: - cors_options["allow_origin_regex"] = cmd_opts.cors_allow_origins_regex - app.add_middleware(CORSMiddleware, **cors_options) +initialize.check_versions() def create_api(app): from modules.api.api import Api + from modules.call_queue import queue_lock + api = Api(app, queue_lock) return api def api_only(): - initialize() + from fastapi import FastAPI + from modules.shared_cmd_options import cmd_opts + + initialize.initialize() app = FastAPI() - setup_middleware(app) + initialize_util.setup_middleware(app) api = create_api(app) - modules.script_callbacks.before_ui_callback() - modules.script_callbacks.app_started_callback(None, app) + from modules import script_callbacks + script_callbacks.before_ui_callback() + script_callbacks.app_started_callback(None, app) print(f"Startup time: {startup_timer.summary()}.") api.launch( @@ -354,24 +48,28 @@ def api_only(): def webui(): + from modules.shared_cmd_options import cmd_opts + launch_api = cmd_opts.api - initialize() + initialize.initialize() + + from modules import shared, ui_tempdir, script_callbacks, ui, progress, ui_extra_networks while 1: if shared.opts.clean_temp_dir_at_start: ui_tempdir.cleanup_tmpdr() startup_timer.record("cleanup temp dir") - modules.script_callbacks.before_ui_callback() + script_callbacks.before_ui_callback() startup_timer.record("scripts before_ui_callback") - shared.demo = modules.ui.create_ui() + shared.demo = ui.create_ui() startup_timer.record("create ui") if not cmd_opts.no_gradio_queue: shared.demo.queue(64) - gradio_auth_creds = list(get_gradio_auth_creds()) or None + gradio_auth_creds = list(initialize_util.get_gradio_auth_creds()) or None auto_launch_browser = False if os.getenv('SD_WEBUI_RESTARTING') != '1': @@ -382,7 +80,7 @@ def webui(): app, local_url, share_url = shared.demo.launch( share=cmd_opts.share, - server_name=server_name, + server_name=initialize_util.gradio_server_name(), server_port=cmd_opts.port, ssl_keyfile=cmd_opts.tls_keyfile, ssl_certfile=cmd_opts.tls_certfile, @@ -407,10 +105,10 @@ def webui(): # running its code. We disable this here. Suggested by RyotaK. app.user_middleware = [x for x in app.user_middleware if x.cls.__name__ != 'CORSMiddleware'] - setup_middleware(app) + initialize_util.setup_middleware(app) - modules.progress.setup_progress_api(app) - modules.ui.setup_ui_api(app) + progress.setup_progress_api(app) + ui.setup_ui_api(app) if launch_api: create_api(app) @@ -420,7 +118,7 @@ def webui(): startup_timer.record("add APIs") with startup_timer.subcategory("app_started_callback"): - modules.script_callbacks.app_started_callback(shared.demo, app) + script_callbacks.app_started_callback(shared.demo, app) timer.startup_record = startup_timer.dump() print(f"Startup time: {startup_timer.summary()}.") @@ -450,14 +148,16 @@ def webui(): shared.demo.close() time.sleep(0.5) startup_timer.reset() - modules.script_callbacks.app_reload_callback() + script_callbacks.app_reload_callback() startup_timer.record("app reload callback") - modules.script_callbacks.script_unloaded_callback() + script_callbacks.script_unloaded_callback() startup_timer.record("scripts unloaded callback") - initialize_rest(reload_script_modules=True) + initialize.initialize_rest(reload_script_modules=True) if __name__ == "__main__": + from modules.shared_cmd_options import cmd_opts + if cmd_opts.nowebui: api_only() else: From 4a64d340010a907a6f5a0f53da023c46f794a590 Mon Sep 17 00:00:00 2001 From: Danil Boldyrev Date: Wed, 9 Aug 2023 18:40:45 +0300 Subject: [PATCH 25/43] fix auto-expand --- .../canvas-zoom-and-pan/javascript/zoom.js | 13 ++++++++----- 1 file changed, 8 insertions(+), 5 deletions(-) diff --git a/extensions-builtin/canvas-zoom-and-pan/javascript/zoom.js b/extensions-builtin/canvas-zoom-and-pan/javascript/zoom.js index eb49a01d4..e7616b981 100644 --- a/extensions-builtin/canvas-zoom-and-pan/javascript/zoom.js +++ b/extensions-builtin/canvas-zoom-and-pan/javascript/zoom.js @@ -42,6 +42,11 @@ onUiLoaded(async() => { } } + // Detect whether the element has a horizontal scroll bar + function hasHorizontalScrollbar(element) { + return element.scrollWidth > element.clientWidth; + } + // Function for defining the "Ctrl", "Shift" and "Alt" keys function isModifierKey(event, key) { switch (key) { @@ -650,16 +655,14 @@ onUiLoaded(async() => { } // Simulation of the function to put a long image into the screen. - // We define the size of the canvas, make a fullscreen to reveal the image, then reduce it to fit into the element. + // We detect if an image has a scroll bar or not, make a fullscreen to reveal the image, then reduce it to fit into the element. // We hide the image and show it to the user when it is ready. function autoExpand(e) { const canvas = document.querySelector(`${elemId} canvas[key="interface"]`); const isMainTab = activeElement === elementIDs.inpaint || activeElement === elementIDs.inpaintSketch || activeElement === elementIDs.sketch; + if (canvas && isMainTab) { - if (canvas && parseInt(targetElement.style.width) > 862 || parseInt(canvas.width) < 862) { - return; - } - if (canvas) { + if (hasHorizontalScrollbar(targetElement)) { targetElement.style.visibility = "hidden"; setTimeout(() => { fitToScreen(); From 8b7b99f8d582edf6422e52f41b82f08cdb80568d Mon Sep 17 00:00:00 2001 From: catboxanon <122327233+catboxanon@users.noreply.github.com> Date: Wed, 9 Aug 2023 12:18:03 -0400 Subject: [PATCH 26/43] fix: Only import tqdm when needed --- modules/launch_utils.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/modules/launch_utils.py b/modules/launch_utils.py index 98ac5bbdc..7143f1443 100644 --- a/modules/launch_utils.py +++ b/modules/launch_utils.py @@ -7,7 +7,6 @@ import importlib.util import platform import json from functools import lru_cache -import tqdm from modules import cmd_args, errors from modules.paths_internal import script_path, extensions_dir @@ -249,6 +248,7 @@ def run_extensions_installers(settings_file): return with startup_timer.subcategory("run extensions installers"): + import tqdm progress_bar = tqdm.tqdm(list_extensions(settings_file)) for dirname_extension in progress_bar: progress_bar.set_description(f"Installing {dirname_extension}") From edfae9e78af23bdd6161c55c7ec88533de8925f8 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Wed, 9 Aug 2023 20:49:33 +0300 Subject: [PATCH 27/43] add --loglevel commandline argument for logging remove the progressbar for extension installation in favor of logging output --- modules/cmd_args.py | 1 + modules/initialize_util.py | 12 ------------ modules/launch_utils.py | 9 +++++---- modules/logging_config.py | 16 ++++++++++++++++ webui.py | 2 -- 5 files changed, 22 insertions(+), 18 deletions(-) create mode 100644 modules/logging_config.py diff --git a/modules/cmd_args.py b/modules/cmd_args.py index 64f21e011..b0a11538b 100644 --- a/modules/cmd_args.py +++ b/modules/cmd_args.py @@ -16,6 +16,7 @@ parser.add_argument("--test-server", action='store_true', help="launch.py argume parser.add_argument("--log-startup", action='store_true', help="launch.py argument: print a detailed log of what's happening at startup") parser.add_argument("--skip-prepare-environment", action='store_true', help="launch.py argument: skip all environment preparation") parser.add_argument("--skip-install", action='store_true', help="launch.py argument: skip installation of packages") +parser.add_argument("--loglevel", type=str, help="log level; one of: CRITICAL, ERROR, WARNING, INFO, DEBUG", default=None) parser.add_argument("--do-not-download-clip", action='store_true', help="do not download CLIP model even if it's not included in the checkpoint") parser.add_argument("--data-dir", type=str, default=os.path.dirname(os.path.dirname(os.path.realpath(__file__))), help="base path where all user data is stored") parser.add_argument("--config", type=str, default=sd_default_config, help="path to config which constructs model",) diff --git a/modules/initialize_util.py b/modules/initialize_util.py index e59bd3c49..d83705768 100644 --- a/modules/initialize_util.py +++ b/modules/initialize_util.py @@ -1,5 +1,4 @@ import json -import logging import os import signal import sys @@ -7,17 +6,6 @@ import re from modules.timer import startup_timer -def setup_logging(): - # We can't use cmd_opts for this because it will not have been initialized at this point. - log_level = os.environ.get("SD_WEBUI_LOG_LEVEL") - if log_level: - log_level = getattr(logging, log_level.upper(), None) or logging.INFO - logging.basicConfig( - level=log_level, - format='%(asctime)s %(levelname)s [%(name)s] %(message)s', - datefmt='%Y-%m-%d %H:%M:%S', - ) - def gradio_server_name(): from modules.shared_cmd_options import cmd_opts diff --git a/modules/launch_utils.py b/modules/launch_utils.py index 7143f1443..90c00dd2d 100644 --- a/modules/launch_utils.py +++ b/modules/launch_utils.py @@ -1,4 +1,5 @@ # this scripts installs necessary requirements and launches main program in webui.py +import logging import re import subprocess import os @@ -11,8 +12,10 @@ from functools import lru_cache from modules import cmd_args, errors from modules.paths_internal import script_path, extensions_dir from modules.timer import startup_timer +from modules import logging_config args, _ = cmd_args.parser.parse_known_args() +logging_config.setup_logging(args.loglevel) python = sys.executable git = os.environ.get('GIT', "git") @@ -248,10 +251,8 @@ def run_extensions_installers(settings_file): return with startup_timer.subcategory("run extensions installers"): - import tqdm - progress_bar = tqdm.tqdm(list_extensions(settings_file)) - for dirname_extension in progress_bar: - progress_bar.set_description(f"Installing {dirname_extension}") + for dirname_extension in list_extensions(settings_file): + logging.debug(f"Installing {dirname_extension}") path = os.path.join(extensions_dir, dirname_extension) diff --git a/modules/logging_config.py b/modules/logging_config.py new file mode 100644 index 000000000..7db23d4b6 --- /dev/null +++ b/modules/logging_config.py @@ -0,0 +1,16 @@ +import os +import logging + + +def setup_logging(loglevel): + if loglevel is None: + loglevel = os.environ.get("SD_WEBUI_LOG_LEVEL") + + if loglevel: + log_level = getattr(logging, loglevel.upper(), None) or logging.INFO + logging.basicConfig( + level=log_level, + format='%(asctime)s %(levelname)s [%(name)s] %(message)s', + datefmt='%Y-%m-%d %H:%M:%S', + ) + diff --git a/webui.py b/webui.py index 738b3bef2..5c827dae8 100644 --- a/webui.py +++ b/webui.py @@ -10,8 +10,6 @@ from modules import initialize startup_timer = timer.startup_timer startup_timer.record("launcher") -initialize_util.setup_logging() - initialize.imports() initialize.check_versions() From 66c32e40e8c059d958292d665a0eeb7377b18988 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Wed, 9 Aug 2023 21:19:33 +0300 Subject: [PATCH 28/43] fix gradio themes not applying --- modules/shared_gradio_themes.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/modules/shared_gradio_themes.py b/modules/shared_gradio_themes.py index ad1f2212a..485e89d5e 100644 --- a/modules/shared_gradio_themes.py +++ b/modules/shared_gradio_themes.py @@ -59,8 +59,8 @@ def reload_gradio_theme(theme_name=None): shared.gradio_theme = gr.themes.ThemeClass.load(theme_cache_path) else: os.makedirs(theme_cache_dir, exist_ok=True) - gradio_theme = gr.themes.ThemeClass.from_hub(theme_name) - gradio_theme.dump(theme_cache_path) + shared.gradio_theme = gr.themes.ThemeClass.from_hub(theme_name) + shared.gradio_theme.dump(theme_cache_path) except Exception as e: errors.display(e, "changing gradio theme") shared.gradio_theme = gr.themes.Default(**default_theme_args) From 259805947e4e567abcf6a4be20fe520d456c251f Mon Sep 17 00:00:00 2001 From: catboxanon <122327233+catboxanon@users.noreply.github.com> Date: Wed, 9 Aug 2023 14:24:16 -0400 Subject: [PATCH 29/43] Add slerp import for extension backwards compat --- modules/processing.py | 1 + 1 file changed, 1 insertion(+) diff --git a/modules/processing.py b/modules/processing.py index 2df5e8c75..6961b7b14 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -15,6 +15,7 @@ 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, errors, rng +from modules.rng import slerp # noqa: F401 from modules.sd_hijack import model_hijack from modules.sd_samplers_common import images_tensor_to_samples, decode_first_stage, approximation_indexes from modules.shared import opts, cmd_opts, state From 2ceb4f81e2f291ba651dd24c7eb158ea3b446b42 Mon Sep 17 00:00:00 2001 From: catboxanon <122327233+catboxanon@users.noreply.github.com> Date: Wed, 9 Aug 2023 14:40:18 -0400 Subject: [PATCH 30/43] Use better symbol for extra networks sort --- modules/ui_extra_networks.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/modules/ui_extra_networks.py b/modules/ui_extra_networks.py index 16d76a452..063bd7b80 100644 --- a/modules/ui_extra_networks.py +++ b/modules/ui_extra_networks.py @@ -347,7 +347,7 @@ def pages_in_preferred_order(pages): def create_ui(interface: gr.Blocks, unrelated_tabs, tabname): - from modules.ui import up_down_symbol + from modules.ui import switch_values_symbol ui = ExtraNetworksUi() ui.pages = [] @@ -374,7 +374,7 @@ def create_ui(interface: gr.Blocks, unrelated_tabs, tabname): edit_search = gr.Textbox('', show_label=False, elem_id=tabname+"_extra_search", elem_classes="search", placeholder="Search...", visible=False, interactive=True) dropdown_sort = gr.Dropdown(choices=['Default Sort', 'Date Created', 'Date Modified', 'Name'], value='Default Sort', elem_id=tabname+"_extra_sort", elem_classes="sort", multiselect=False, visible=False, show_label=False, interactive=True, label=tabname+"_extra_sort_order") - button_sortorder = ToolButton(up_down_symbol, elem_id=tabname+"_extra_sortorder", elem_classes="sortorder", visible=False) + button_sortorder = ToolButton(switch_values_symbol, elem_id=tabname+"_extra_sortorder", elem_classes="sortorder", visible=False) button_refresh = gr.Button('Refresh', elem_id=tabname+"_extra_refresh", visible=False) checkbox_show_dirs = gr.Checkbox(True, label='Show dirs', elem_id=tabname+"_extra_show_dirs", elem_classes="show-dirs", visible=False) From ff1bfd01ba33ee03b3eb99b1669bd29a3a6658ca Mon Sep 17 00:00:00 2001 From: catboxanon <122327233+catboxanon@users.noreply.github.com> Date: Wed, 9 Aug 2023 14:41:25 -0400 Subject: [PATCH 31/43] Remove up down symbol --- modules/ui.py | 1 - 1 file changed, 1 deletion(-) diff --git a/modules/ui.py b/modules/ui.py index 30b80417e..4e1daa8d9 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -78,7 +78,6 @@ extra_networks_symbol = '\U0001F3B4' # 🎴 switch_values_symbol = '\U000021C5' # ⇅ restore_progress_symbol = '\U0001F300' # 🌀 detect_image_size_symbol = '\U0001F4D0' # 📐 -up_down_symbol = '\u2195\ufe0f' # ↕️ plaintext_to_html = ui_common.plaintext_to_html From 2c5106ed06044ba4b67b1c856756e33a1ca5eeea Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Thu, 10 Aug 2023 07:57:52 +0300 Subject: [PATCH 32/43] additional work on gradio styles; make the accordion change affect all accordions, not just inside scripts div --- style.css | 18 ++++++++---------- 1 file changed, 8 insertions(+), 10 deletions(-) diff --git a/style.css b/style.css index cda5f6a02..dfd5ca367 100644 --- a/style.css +++ b/style.css @@ -43,13 +43,15 @@ div.form{ .block.gradio-radio, .block.gradio-checkboxgroup, .block.gradio-number, -.block.gradio-colorpicker, -div.gradio-group -{ +.block.gradio-colorpicker { border-width: 0 !important; box-shadow: none !important; } +div.gradio-group, div.styler{ + border-width: 0 !important; + background: none; +} .gap.compact{ padding: 0; gap: 0.2em 0; @@ -135,12 +137,8 @@ a{ cursor: pointer; } -div.styler{ - border: none; - background: var(--background-fill-primary); -} - -.block.gradio-textbox{ +/* gradio 3.39 puts a lot of overflow: hidden all over the place for an unknown reqasaon. */ +.block.gradio-textbox, div.gradio-group, div.gradio-group div, div.gradio-dropdown{ overflow: visible !important; } @@ -194,7 +192,7 @@ button.custom-button{ text-align: center; } -.gradio-group[id$="_script_container"] > div .gradio-group > div > div:is(.gradio-accordion, .form) { +div.gradio-accordion { border: 1px solid var(--block-border-color) !important; border-radius: 8px !important; margin: 2px 0; From 9199b6b7ebe96cdf09571ba874a103e8ed8c90ef Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Thu, 10 Aug 2023 11:20:46 +0300 Subject: [PATCH 33/43] add a custom UI element that combines accordion and checkbox rework hires fix UI to use accordion prevent bogus progress output in console when calculating hires fix dimensions --- javascript/inputAccordion.js | 37 +++++++++++++++++ modules/processing.py | 77 +++++++++++++++++++----------------- modules/ui.py | 23 ++++------- modules/ui_components.py | 31 +++++++++++++++ style.css | 15 ++++--- 5 files changed, 124 insertions(+), 59 deletions(-) create mode 100644 javascript/inputAccordion.js diff --git a/javascript/inputAccordion.js b/javascript/inputAccordion.js new file mode 100644 index 000000000..a5eef2297 --- /dev/null +++ b/javascript/inputAccordion.js @@ -0,0 +1,37 @@ +var observerAccordionOpen = new MutationObserver(function(mutations) { + mutations.forEach(function(mutationRecord) { + var elem = mutationRecord.target; + var open = elem.classList.contains('open'); + + var accordion = elem.parentNode; + accordion.classList.toggle('input-accordion-open', open); + + var checkbox = gradioApp().querySelector('#' + accordion.id + "-checkbox input"); + checkbox.checked = open; + updateInput(checkbox); + + extra = gradioApp().querySelector('#' + accordion.id + "-extra"); + if(extra){ + extra.style.display = open ? "" : "none"; + } + }); +}); + +function inputAccordionChecked(id, checked){ + var label = gradioApp().querySelector('#' + id + " .label-wrap"); + if(label.classList.contains('open') != checked){ + label.click(); + } +} + +onUiLoaded(function() { + for (var accordion of gradioApp().querySelectorAll('.input-accordion')) { + var labelWrap = accordion.querySelector('.label-wrap'); + observerAccordionOpen.observe(labelWrap, {attributes: true, attributeFilter: ['class']}); + + var extra = gradioApp().querySelector('#' + accordion.id + "-extra"); + if(extra){ + labelWrap.insertBefore(extra, labelWrap.lastElementChild) + } + } +}); diff --git a/modules/processing.py b/modules/processing.py index 6961b7b14..7819644c7 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -924,6 +924,45 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): self.hr_c = None self.hr_uc = None + def calculate_target_resolution(self): + 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 + self.hr_upscale_to_x = self.width + self.hr_upscale_to_y = self.height + + self.width, self.height = old_hires_fix_first_pass_dimensions(self.width, self.height) + self.applied_old_hires_behavior_to = (self.width, self.height) + + if self.hr_resize_x == 0 and self.hr_resize_y == 0: + self.extra_generation_params["Hires upscale"] = self.hr_scale + self.hr_upscale_to_x = int(self.width * self.hr_scale) + self.hr_upscale_to_y = int(self.height * self.hr_scale) + else: + self.extra_generation_params["Hires resize"] = f"{self.hr_resize_x}x{self.hr_resize_y}" + + if self.hr_resize_y == 0: + self.hr_upscale_to_x = self.hr_resize_x + self.hr_upscale_to_y = self.hr_resize_x * self.height // self.width + elif self.hr_resize_x == 0: + self.hr_upscale_to_x = self.hr_resize_y * self.width // self.height + self.hr_upscale_to_y = self.hr_resize_y + else: + target_w = self.hr_resize_x + target_h = self.hr_resize_y + src_ratio = self.width / self.height + dst_ratio = self.hr_resize_x / self.hr_resize_y + + if src_ratio < dst_ratio: + self.hr_upscale_to_x = self.hr_resize_x + self.hr_upscale_to_y = self.hr_resize_x * self.height // self.width + else: + self.hr_upscale_to_x = self.hr_resize_y * self.width // self.height + self.hr_upscale_to_y = self.hr_resize_y + + self.truncate_x = (self.hr_upscale_to_x - target_w) // opt_f + self.truncate_y = (self.hr_upscale_to_y - target_h) // opt_f + def init(self, all_prompts, all_seeds, all_subseeds): if self.enable_hr: if self.hr_checkpoint_name: @@ -948,43 +987,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): 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 - self.hr_upscale_to_x = self.width - self.hr_upscale_to_y = self.height - - self.width, self.height = old_hires_fix_first_pass_dimensions(self.width, self.height) - self.applied_old_hires_behavior_to = (self.width, self.height) - - if self.hr_resize_x == 0 and self.hr_resize_y == 0: - self.extra_generation_params["Hires upscale"] = self.hr_scale - self.hr_upscale_to_x = int(self.width * self.hr_scale) - self.hr_upscale_to_y = int(self.height * self.hr_scale) - else: - self.extra_generation_params["Hires resize"] = f"{self.hr_resize_x}x{self.hr_resize_y}" - - if self.hr_resize_y == 0: - self.hr_upscale_to_x = self.hr_resize_x - self.hr_upscale_to_y = self.hr_resize_x * self.height // self.width - elif self.hr_resize_x == 0: - self.hr_upscale_to_x = self.hr_resize_y * self.width // self.height - self.hr_upscale_to_y = self.hr_resize_y - else: - target_w = self.hr_resize_x - target_h = self.hr_resize_y - src_ratio = self.width / self.height - dst_ratio = self.hr_resize_x / self.hr_resize_y - - if src_ratio < dst_ratio: - self.hr_upscale_to_x = self.hr_resize_x - self.hr_upscale_to_y = self.hr_resize_x * self.height // self.width - else: - self.hr_upscale_to_x = self.hr_resize_y * self.width // self.height - self.hr_upscale_to_y = self.hr_resize_y - - self.truncate_x = (self.hr_upscale_to_x - target_w) // opt_f - self.truncate_y = (self.hr_upscale_to_y - target_h) // opt_f + self.calculate_target_resolution() if not state.processing_has_refined_job_count: if state.job_count == -1: diff --git a/modules/ui.py b/modules/ui.py index 4e1daa8d9..cbad3afe7 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -14,7 +14,7 @@ from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_grad 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, sd_samplers, processing, devices, ui_extra_networks -from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML +from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML, InputAccordion from modules.paths import script_path from modules.ui_common import create_refresh_button from modules.ui_gradio_extensions import reload_javascript @@ -94,11 +94,9 @@ def calc_resolution_hires(enable, width, height, hr_scale, hr_resize_x, hr_resiz return "" p = processing.StableDiffusionProcessingTxt2Img(width=width, height=height, enable_hr=True, hr_scale=hr_scale, hr_resize_x=hr_resize_x, hr_resize_y=hr_resize_y) + p.calculate_target_resolution() - with devices.autocast(): - p.init([""], [0], [0]) - - return f"resize: from {p.width}x{p.height} to {p.hr_resize_x or p.hr_upscale_to_x}x{p.hr_resize_y or p.hr_upscale_to_y}" + return f"from {p.width}x{p.height} to {p.hr_resize_x or p.hr_upscale_to_x}x{p.hr_resize_y or p.hr_upscale_to_y}" def resize_from_to_html(width, height, scale_by): @@ -436,11 +434,12 @@ def create_ui(): with FormRow(elem_classes="checkboxes-row", variant="compact"): restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="txt2img_restore_faces") tiling = gr.Checkbox(label='Tiling', value=False, elem_id="txt2img_tiling") - enable_hr = gr.Checkbox(label='Hires. fix', value=False, elem_id="txt2img_enable_hr") - hr_final_resolution = FormHTML(value="", elem_id="txtimg_hr_finalres", label="Upscaled resolution", interactive=False) elif category == "hires_fix": - with FormGroup(visible=False, elem_id="txt2img_hires_fix") as hr_options: + with InputAccordion(False, label="Hires. fix") as enable_hr: + with enable_hr.extra(): + hr_final_resolution = FormHTML(value="", elem_id="txtimg_hr_finalres", label="Upscaled resolution", interactive=False, min_width=0) + with FormRow(elem_id="txt2img_hires_fix_row1", variant="compact"): hr_upscaler = gr.Dropdown(label="Upscaler", elem_id="txt2img_hr_upscaler", choices=[*shared.latent_upscale_modes, *[x.name for x in shared.sd_upscalers]], value=shared.latent_upscale_default_mode) hr_second_pass_steps = gr.Slider(minimum=0, maximum=150, step=1, label='Hires steps', value=0, elem_id="txt2img_hires_steps") @@ -568,13 +567,6 @@ def create_ui(): show_progress=False, ) - enable_hr.change( - fn=lambda x: gr_show(x), - inputs=[enable_hr], - outputs=[hr_options], - show_progress = False, - ) - txt2img_paste_fields = [ (toprow.prompt, "Prompt"), (toprow.negative_prompt, "Negative prompt"), @@ -594,7 +586,6 @@ def create_ui(): (toprow.ui_styles.dropdown, lambda d: d["Styles array"] if isinstance(d.get("Styles array"), list) else gr.update()), (denoising_strength, "Denoising strength"), (enable_hr, lambda d: "Denoising strength" in d and ("Hires upscale" in d or "Hires upscaler" in d or "Hires resize-1" in d)), - (hr_options, lambda d: gr.Row.update(visible="Denoising strength" in d and ("Hires upscale" in d or "Hires upscaler" in d or "Hires resize-1" in d))), (hr_scale, "Hires upscale"), (hr_upscaler, "Hires upscaler"), (hr_second_pass_steps, "Hires steps"), diff --git a/modules/ui_components.py b/modules/ui_components.py index 8f8a70885..598ce738e 100644 --- a/modules/ui_components.py +++ b/modules/ui_components.py @@ -72,3 +72,34 @@ class DropdownEditable(FormComponent, gr.Dropdown): def get_block_name(self): return "dropdown" + +class InputAccordion(gr.Checkbox): + global_index = 0 + + def __init__(self, value, **kwargs): + self.accordion_id = kwargs.get('elem_id') + if self.accordion_id is None: + self.accordion_id = f"input-accordion-{self.global_index}" + self.global_index += 1 + + kwargs['elem_id'] = self.accordion_id + "-checkbox" + kwargs['visible'] = False + super().__init__(value, **kwargs) + + self.change(fn=None, _js='function(checked){ inputAccordionChecked("' + self.accordion_id + '", checked); }', inputs=[self]) + + self.accordion = gr.Accordion(kwargs.get('label', 'Accordion'), open=value, elem_id=self.accordion_id, elem_classes=['input-accordion']) + + def extra(self): + return gr.Column(elem_id=self.accordion_id + '-extra', elem_classes='input-accordion-extra', min_width=0) + + def __enter__(self): + self.accordion.__enter__() + return self + + def __exit__(self, exc_type, exc_val, exc_tb): + self.accordion.__exit__(exc_type, exc_val, exc_tb) + + def get_block_name(self): + return "checkbox" + diff --git a/style.css b/style.css index dfd5ca367..5163e53c2 100644 --- a/style.css +++ b/style.css @@ -329,12 +329,6 @@ div.gradio-accordion { border-radius: 0 0.5rem 0.5rem 0; } -#txtimg_hr_finalres{ - min-height: 0 !important; - padding: .625rem .75rem; - margin-left: -0.75em -} - #img2img_scale_resolution_preview.block{ display: flex; align-items: end; @@ -1016,3 +1010,12 @@ div.block.gradio-box.popup-dialog, .popup-dialog { div.block.gradio-box.popup-dialog > div:last-child, .popup-dialog > div:last-child{ margin-top: 1em; } + +div.block.input-accordion{ + margin-bottom: 0.4em; +} + +.input-accordion-extra{ + flex: 0 0 auto !important; + margin: 0 0.5em 0 auto; +} From 33446acf47a8c3e0c0964782189562df3c4bcf4f Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Thu, 10 Aug 2023 12:41:41 +0300 Subject: [PATCH 34/43] face restoration and tiling moved to settings - use "Options in main UI" setting if you want them back --- modules/generation_parameters_copypaste.py | 2 ++ modules/img2img.py | 4 +--- modules/processing.py | 11 +++++++++-- modules/shared_options.py | 2 ++ modules/txt2img.py | 4 +--- modules/ui.py | 12 ++---------- 6 files changed, 17 insertions(+), 18 deletions(-) diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index d932c67d5..bdff32665 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -343,6 +343,8 @@ infotext_to_setting_name_mapping = [ ('Pad conds', 'pad_cond_uncond'), ('VAE Encoder', 'sd_vae_encode_method'), ('VAE Decoder', 'sd_vae_decode_method'), + ('Tiling', 'tiling'), + ('Face restoration', 'face_restoration'), ] diff --git a/modules/img2img.py b/modules/img2img.py index e06ac1d6e..c7bbbac8f 100644 --- a/modules/img2img.py +++ b/modules/img2img.py @@ -116,7 +116,7 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args, to_scale=Fal process_images(p) -def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_styles, init_img, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, steps: int, sampler_name: str, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, image_cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, selected_scale_tab: int, height: int, width: int, scale_by: float, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, img2img_batch_inpaint_mask_dir: str, override_settings_texts, img2img_batch_use_png_info: bool, img2img_batch_png_info_props: list, img2img_batch_png_info_dir: str, request: gr.Request, *args): +def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_styles, init_img, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, steps: int, sampler_name: str, mask_blur: int, mask_alpha: float, inpainting_fill: int, n_iter: int, batch_size: int, cfg_scale: float, image_cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, selected_scale_tab: int, height: int, width: int, scale_by: float, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, img2img_batch_inpaint_mask_dir: str, override_settings_texts, img2img_batch_use_png_info: bool, img2img_batch_png_info_props: list, img2img_batch_png_info_dir: str, request: gr.Request, *args): override_settings = create_override_settings_dict(override_settings_texts) is_batch = mode == 5 @@ -179,8 +179,6 @@ def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_s cfg_scale=cfg_scale, width=width, height=height, - restore_faces=restore_faces, - tiling=tiling, init_images=[image], mask=mask, mask_blur=mask_blur, diff --git a/modules/processing.py b/modules/processing.py index 7819644c7..68a8f1c6a 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -111,7 +111,7 @@ class StableDiffusionProcessing: cached_uc = [None, None] cached_c = [None, None] - def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prompt: str = "", styles: List[str] = None, seed: int = -1, subseed: int = -1, subseed_strength: float = 0, seed_resize_from_h: int = -1, seed_resize_from_w: int = -1, seed_enable_extras: bool = True, sampler_name: str = None, batch_size: int = 1, n_iter: int = 1, steps: int = 50, cfg_scale: float = 7.0, width: int = 512, height: int = 512, restore_faces: bool = False, tiling: bool = False, do_not_save_samples: bool = False, do_not_save_grid: bool = False, extra_generation_params: Dict[Any, Any] = None, overlay_images: Any = None, negative_prompt: str = None, eta: float = None, do_not_reload_embeddings: bool = False, denoising_strength: float = 0, ddim_discretize: str = None, s_min_uncond: float = 0.0, s_churn: float = 0.0, s_tmax: float = None, s_tmin: float = 0.0, s_noise: float = None, override_settings: Dict[str, Any] = None, override_settings_restore_afterwards: bool = True, sampler_index: int = None, script_args: list = None): + def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prompt: str = "", styles: List[str] = None, seed: int = -1, subseed: int = -1, subseed_strength: float = 0, seed_resize_from_h: int = -1, seed_resize_from_w: int = -1, seed_enable_extras: bool = True, sampler_name: str = None, batch_size: int = 1, n_iter: int = 1, steps: int = 50, cfg_scale: float = 7.0, width: int = 512, height: int = 512, restore_faces: bool = None, tiling: bool = None, do_not_save_samples: bool = False, do_not_save_grid: bool = False, extra_generation_params: Dict[Any, Any] = None, overlay_images: Any = None, negative_prompt: str = None, eta: float = None, do_not_reload_embeddings: bool = False, denoising_strength: float = 0, ddim_discretize: str = None, s_min_uncond: float = 0.0, s_churn: float = 0.0, s_tmax: float = None, s_tmin: float = 0.0, s_noise: float = None, override_settings: Dict[str, Any] = None, override_settings_restore_afterwards: bool = True, sampler_index: int = None, script_args: list = None): if sampler_index is not None: print("sampler_index argument for StableDiffusionProcessing does not do anything; use sampler_name", file=sys.stderr) @@ -564,7 +564,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter "CFG scale": p.cfg_scale, "Image CFG scale": getattr(p, 'image_cfg_scale', None), "Seed": p.all_seeds[0] if use_main_prompt else all_seeds[index], - "Face restoration": (opts.face_restoration_model if p.restore_faces else None), + "Face restoration": opts.face_restoration_model if p.restore_faces else None, "Size": f"{p.width}x{p.height}", "Model hash": getattr(p, 'sd_model_hash', None if not opts.add_model_hash_to_info or not shared.sd_model.sd_model_hash else shared.sd_model.sd_model_hash), "Model": (None if not opts.add_model_name_to_info else shared.sd_model.sd_checkpoint_info.name_for_extra), @@ -580,6 +580,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter "Init image hash": getattr(p, 'init_img_hash', 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, + "Tiling": "True" if p.tiling else None, **p.extra_generation_params, "Version": program_version() if opts.add_version_to_infotext else None, "User": p.user if opts.add_user_name_to_info else None, @@ -645,6 +646,12 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: seed = get_fixed_seed(p.seed) subseed = get_fixed_seed(p.subseed) + if p.restore_faces is None: + p.restore_faces = opts.face_restoration + + if p.tiling is None: + p.tiling = opts.tiling + modules.sd_hijack.model_hijack.apply_circular(p.tiling) modules.sd_hijack.model_hijack.clear_comments() diff --git a/modules/shared_options.py b/modules/shared_options.py index 7468bc81a..f72859d9d 100644 --- a/modules/shared_options.py +++ b/modules/shared_options.py @@ -92,6 +92,7 @@ options_templates.update(options_section(('upscaling', "Upscaling"), { })) options_templates.update(options_section(('face-restoration', "Face restoration"), { + "face_restoration": OptionInfo(False, "Restore faces").info("will use a third-party model on generation result to reconstruct faces"), "face_restoration_model": OptionInfo("CodeFormer", "Face restoration model", gr.Radio, lambda: {"choices": [x.name() for x in shared.face_restorers]}), "code_former_weight": OptionInfo(0.5, "CodeFormer weight", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}).info("0 = maximum effect; 1 = minimum effect"), "face_restoration_unload": OptionInfo(False, "Move face restoration model from VRAM into RAM after processing"), @@ -138,6 +139,7 @@ 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"), "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"), + "tiling": OptionInfo(False, "Tiling").info("produce a tileable picture"), })) options_templates.update(options_section(('sdxl', "Stable Diffusion XL"), { diff --git a/modules/txt2img.py b/modules/txt2img.py index edad89305..5ea96bbaf 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_name: str, 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_name: str, 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_name: str, 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_name: str, 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( @@ -32,8 +32,6 @@ def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, step cfg_scale=cfg_scale, width=width, height=height, - restore_faces=restore_faces, - tiling=tiling, enable_hr=enable_hr, denoising_strength=denoising_strength if enable_hr else None, hr_scale=hr_scale, diff --git a/modules/ui.py b/modules/ui.py index cbad3afe7..09a826fdd 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -432,8 +432,7 @@ def create_ui(): elif category == "checkboxes": with FormRow(elem_classes="checkboxes-row", variant="compact"): - restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="txt2img_restore_faces") - tiling = gr.Checkbox(label='Tiling', value=False, elem_id="txt2img_tiling") + pass elif category == "hires_fix": with InputAccordion(False, label="Hires. fix") as enable_hr: @@ -516,8 +515,6 @@ def create_ui(): toprow.ui_styles.dropdown, steps, sampler_name, - restore_faces, - tiling, batch_count, batch_size, cfg_scale, @@ -572,7 +569,6 @@ def create_ui(): (toprow.negative_prompt, "Negative prompt"), (steps, "Steps"), (sampler_name, "Sampler"), - (restore_faces, "Face restoration"), (cfg_scale, "CFG scale"), (seed, "Seed"), (width, "Size-1"), @@ -792,8 +788,7 @@ def create_ui(): elif category == "checkboxes": with FormRow(elem_classes="checkboxes-row", variant="compact"): - restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="img2img_restore_faces") - tiling = gr.Checkbox(label='Tiling', value=False, elem_id="img2img_tiling") + pass elif category == "batch": if not opts.dimensions_and_batch_together: @@ -866,8 +861,6 @@ def create_ui(): mask_blur, mask_alpha, inpainting_fill, - restore_faces, - tiling, batch_count, batch_size, cfg_scale, @@ -959,7 +952,6 @@ def create_ui(): (toprow.negative_prompt, "Negative prompt"), (steps, "Steps"), (sampler_name, "Sampler"), - (restore_faces, "Face restoration"), (cfg_scale, "CFG scale"), (image_cfg_scale, "Image CFG scale"), (seed, "Seed"), From 6c23061a7d03791babeec569d28a691758e4322d Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Thu, 10 Aug 2023 12:50:03 +0300 Subject: [PATCH 35/43] avoid importing gradio in tests because it spams warnings --- test/conftest.py | 16 ++++++++++++---- 1 file changed, 12 insertions(+), 4 deletions(-) diff --git a/test/conftest.py b/test/conftest.py index 0723f62a4..31a5d9eaf 100644 --- a/test/conftest.py +++ b/test/conftest.py @@ -1,17 +1,25 @@ import os import pytest -from PIL import Image -from gradio.processing_utils import encode_pil_to_base64 +import base64 + test_files_path = os.path.dirname(__file__) + "/test_files" +def file_to_base64(filename): + with open(filename, "rb") as file: + data = file.read() + + base64_str = str(base64.b64encode(data), "utf-8") + return "data:image/png;base64," + base64_str + + @pytest.fixture(scope="session") # session so we don't read this over and over def img2img_basic_image_base64() -> str: - return encode_pil_to_base64(Image.open(os.path.join(test_files_path, "img2img_basic.png"))) + return file_to_base64(os.path.join(test_files_path, "img2img_basic.png")) @pytest.fixture(scope="session") # session so we don't read this over and over def mask_basic_image_base64() -> str: - return encode_pil_to_base64(Image.open(os.path.join(test_files_path, "mask_basic.png"))) + return file_to_base64(os.path.join(test_files_path, "mask_basic.png")) From faca86620d53b122eac00fd0a4ab54b3a2e3108e Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Thu, 10 Aug 2023 12:58:00 +0300 Subject: [PATCH 36/43] linter fixes --- javascript/inputAccordion.js | 12 ++++++------ modules/ui.py | 2 +- 2 files changed, 7 insertions(+), 7 deletions(-) diff --git a/javascript/inputAccordion.js b/javascript/inputAccordion.js index a5eef2297..f2839852e 100644 --- a/javascript/inputAccordion.js +++ b/javascript/inputAccordion.js @@ -10,16 +10,16 @@ var observerAccordionOpen = new MutationObserver(function(mutations) { checkbox.checked = open; updateInput(checkbox); - extra = gradioApp().querySelector('#' + accordion.id + "-extra"); - if(extra){ + var extra = gradioApp().querySelector('#' + accordion.id + "-extra"); + if (extra) { extra.style.display = open ? "" : "none"; } }); }); -function inputAccordionChecked(id, checked){ +function inputAccordionChecked(id, checked) { var label = gradioApp().querySelector('#' + id + " .label-wrap"); - if(label.classList.contains('open') != checked){ + if (label.classList.contains('open') != checked) { label.click(); } } @@ -30,8 +30,8 @@ onUiLoaded(function() { observerAccordionOpen.observe(labelWrap, {attributes: true, attributeFilter: ['class']}); var extra = gradioApp().querySelector('#' + accordion.id + "-extra"); - if(extra){ - labelWrap.insertBefore(extra, labelWrap.lastElementChild) + if (extra) { + labelWrap.insertBefore(extra, labelWrap.lastElementChild); } } }); diff --git a/modules/ui.py b/modules/ui.py index 09a826fdd..b87e95a64 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -13,7 +13,7 @@ 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, sd_samplers, processing, devices, ui_extra_networks +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, sd_samplers, processing, ui_extra_networks from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML, InputAccordion from modules.paths import script_path from modules.ui_common import create_refresh_button From 08838105923255e66ef0d58115fc9ce671d202ae Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Thu, 10 Aug 2023 13:02:50 +0300 Subject: [PATCH 37/43] comment for InputAccordion --- modules/ui_components.py | 18 ++++++++++++++++++ 1 file changed, 18 insertions(+) diff --git a/modules/ui_components.py b/modules/ui_components.py index 598ce738e..9df9ddf40 100644 --- a/modules/ui_components.py +++ b/modules/ui_components.py @@ -74,6 +74,11 @@ class DropdownEditable(FormComponent, gr.Dropdown): class InputAccordion(gr.Checkbox): + """A gr.Accordion that can be used as an input - returns True if open, False if closed. + + Actaully just a hidden checkbox, but creates an accordion that follows and is followed by the state of the checkbox. + """ + global_index = 0 def __init__(self, value, **kwargs): @@ -91,6 +96,19 @@ class InputAccordion(gr.Checkbox): self.accordion = gr.Accordion(kwargs.get('label', 'Accordion'), open=value, elem_id=self.accordion_id, elem_classes=['input-accordion']) def extra(self): + """Allows you to put something into the label of the accordion. + + Use it like this: + + ``` + with InputAccordion(False, label="Accordion") as acc: + with acc.extra(): + FormHTML(value="hello", min_width=0) + + ... + ``` + """ + return gr.Column(elem_id=self.accordion_id + '-extra', elem_classes='input-accordion-extra', min_width=0) def __enter__(self): From 4d93f48f090e19a81d1608837e8e6449045601a8 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Thu, 10 Aug 2023 15:32:54 +0300 Subject: [PATCH 38/43] fix for multiple input accordions --- modules/ui_components.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/modules/ui_components.py b/modules/ui_components.py index 9df9ddf40..bfe2fbd97 100644 --- a/modules/ui_components.py +++ b/modules/ui_components.py @@ -84,8 +84,8 @@ class InputAccordion(gr.Checkbox): def __init__(self, value, **kwargs): self.accordion_id = kwargs.get('elem_id') if self.accordion_id is None: - self.accordion_id = f"input-accordion-{self.global_index}" - self.global_index += 1 + self.accordion_id = f"input-accordion-{InputAccordion.global_index}" + InputAccordion.global_index += 1 kwargs['elem_id'] = self.accordion_id + "-checkbox" kwargs['visible'] = False From 1b3093fe3aedb20aa8d505ceeea7900ac592e6fe Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Thu, 10 Aug 2023 15:58:53 +0300 Subject: [PATCH 39/43] fix --use-textbox-seed --- modules/processing.py | 12 ++++++++++-- modules/ui.py | 6 +++++- modules/ui_loadsave.py | 5 ++++- 3 files changed, 19 insertions(+), 4 deletions(-) diff --git a/modules/processing.py b/modules/processing.py index 68a8f1c6a..f06c374a2 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -521,7 +521,15 @@ def decode_latent_batch(model, batch, target_device=None, check_for_nans=False): def get_fixed_seed(seed): - if seed is None or seed == '' or seed == -1: + if seed == '' or seed is None: + seed = -1 + elif isinstance(seed, str): + try: + seed = int(seed) + except Exception: + seed = -1 + + if seed == -1: return int(random.randrange(4294967294)) return seed @@ -728,7 +736,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: # strength, which is saved as "Model Strength: 1.0" in the infotext if n == 0: with open(os.path.join(paths.data_path, "params.txt"), "w", encoding="utf8") as file: - processed = Processed(p, [], p.seed, "") + processed = Processed(p, []) file.write(processed.infotext(p, 0)) p.setup_conds() diff --git a/modules/ui.py b/modules/ui.py index b87e95a64..e7433cbd7 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -144,7 +144,11 @@ 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") + if cmd_opts.use_textbox_seed: + seed = gr.Textbox(label='Seed', value="", elem_id=f"{target_interface}_seed") + else: + seed = gr.Number(label='Seed', value=-1, elem_id=f"{target_interface}_seed") + 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') diff --git a/modules/ui_loadsave.py b/modules/ui_loadsave.py index 0052a5cce..99d763e1c 100644 --- a/modules/ui_loadsave.py +++ b/modules/ui_loadsave.py @@ -8,7 +8,7 @@ from modules.ui_components import ToolButton class UiLoadsave: - """allows saving and restorig default values for gradio components""" + """allows saving and restoring default values for gradio components""" def __init__(self, filename): self.filename = filename @@ -48,6 +48,9 @@ class UiLoadsave: elif condition and not condition(saved_value): pass else: + if isinstance(x, gr.Textbox) and field == 'value': # due to an undersirable behavior of gr.Textbox, if you give it an int value instead of str, everything dies + saved_value = str(saved_value) + setattr(obj, field, saved_value) if init_field is not None: init_field(saved_value) From 4f6582cb668d4f4beea64f1c7baae721c85cfc69 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Thu, 10 Aug 2023 16:10:42 +0300 Subject: [PATCH 40/43] add precision=0 to gr.Number seed --- modules/ui.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/modules/ui.py b/modules/ui.py index e7433cbd7..c08f412d8 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -147,7 +147,7 @@ def create_seed_inputs(target_interface): if cmd_opts.use_textbox_seed: seed = gr.Textbox(label='Seed', value="", elem_id=f"{target_interface}_seed") else: - seed = gr.Number(label='Seed', value=-1, elem_id=f"{target_interface}_seed") + seed = gr.Number(label='Seed', value=-1, elem_id=f"{target_interface}_seed", precision=0) 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') @@ -159,7 +159,7 @@ 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 = gr.Number(label='Variation seed', value=-1, elem_id=f"{target_interface}_subseed", precision=0) 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") From b13806c15065bd9a91edef2b8516c461ce585361 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Thu, 10 Aug 2023 16:15:34 +0300 Subject: [PATCH 41/43] fix a bug preventing normal operation if a string is added to a gr.Number component via ui-config.json --- modules/ui_loadsave.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/modules/ui_loadsave.py b/modules/ui_loadsave.py index 99d763e1c..ef6b0154e 100644 --- a/modules/ui_loadsave.py +++ b/modules/ui_loadsave.py @@ -50,6 +50,8 @@ class UiLoadsave: else: if isinstance(x, gr.Textbox) and field == 'value': # due to an undersirable behavior of gr.Textbox, if you give it an int value instead of str, everything dies saved_value = str(saved_value) + elif isinstance(x, gr.Number) and field == 'value': + saved_value = float(saved_value) setattr(obj, field, saved_value) if init_field is not None: From 9d78d317ae492db59ebf8b31fda9a049f6c9bd14 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Thu, 10 Aug 2023 16:22:10 +0300 Subject: [PATCH 42/43] add VAE to infotext --- modules/generation_parameters_copypaste.py | 1 + modules/processing.py | 2 ++ modules/sd_vae.py | 16 +++++++++++++++- 3 files changed, 18 insertions(+), 1 deletion(-) diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index bdff32665..6ace29cf3 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -341,6 +341,7 @@ infotext_to_setting_name_mapping = [ ('RNG', 'randn_source'), ('NGMS', 's_min_uncond'), ('Pad conds', 'pad_cond_uncond'), + ('VAE', 'sd_vae'), ('VAE Encoder', 'sd_vae_encode_method'), ('VAE Decoder', 'sd_vae_decode_method'), ('Tiling', 'tiling'), diff --git a/modules/processing.py b/modules/processing.py index f06c374a2..44d47e8ca 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -576,6 +576,8 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter "Size": f"{p.width}x{p.height}", "Model hash": getattr(p, 'sd_model_hash', None if not opts.add_model_hash_to_info or not shared.sd_model.sd_model_hash else shared.sd_model.sd_model_hash), "Model": (None if not opts.add_model_name_to_info else shared.sd_model.sd_checkpoint_info.name_for_extra), + "VAE hash": sd_vae.get_loaded_vae_hash() if opts.add_model_hash_to_info else None, + "VAE": sd_vae.get_loaded_vae_name() if opts.add_model_name_to_info else None, "Variation seed": (None if p.subseed_strength == 0 else (p.all_subseeds[0] if use_main_prompt else all_subseeds[index])), "Variation seed strength": (None if p.subseed_strength == 0 else p.subseed_strength), "Seed resize from": (None if p.seed_resize_from_w <= 0 or p.seed_resize_from_h <= 0 else f"{p.seed_resize_from_w}x{p.seed_resize_from_h}"), diff --git a/modules/sd_vae.py b/modules/sd_vae.py index 5ac1ac31f..1db01992d 100644 --- a/modules/sd_vae.py +++ b/modules/sd_vae.py @@ -2,7 +2,7 @@ import os import collections from dataclasses import dataclass -from modules import paths, shared, devices, script_callbacks, sd_models, extra_networks, lowvram, sd_hijack +from modules import paths, shared, devices, script_callbacks, sd_models, extra_networks, lowvram, sd_hijack, hashes import glob from copy import deepcopy @@ -20,6 +20,20 @@ checkpoint_info = None checkpoints_loaded = collections.OrderedDict() +def get_loaded_vae_name(): + if loaded_vae_file is None: + return None + + return os.path.basename(loaded_vae_file) + + +def get_loaded_vae_hash(): + if loaded_vae_file is None: + return None + + return hashes.sha256(loaded_vae_file, 'vae')[0:10] + + def get_base_vae(model): if base_vae is not None and checkpoint_info == model.sd_checkpoint_info and model: return base_vae From 070b034cd5b49eb5056a18b43f88aa223fec9e0b Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Thu, 10 Aug 2023 16:42:26 +0300 Subject: [PATCH 43/43] put infotext label for setting into OptionInfo definition rather than in a separate list --- modules/generation_parameters_copypaste.py | 39 +++++---------- modules/options.py | 4 +- modules/shared_options.py | 56 +++++++++++----------- 3 files changed, 42 insertions(+), 57 deletions(-) diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 6ace29cf3..386517aca 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -316,37 +316,18 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model infotext_to_setting_name_mapping = [ - ('Clip skip', 'CLIP_stop_at_last_layers', ), + +] +"""Mapping of infotext labels to setting names. Only left for backwards compatibility - use OptionInfo(..., infotext='...') instead. +Example content: + +infotext_to_setting_name_mapping = [ ('Conditional mask weight', 'inpainting_mask_weight'), ('Model hash', 'sd_model_checkpoint'), ('ENSD', 'eta_noise_seed_delta'), ('Schedule type', 'k_sched_type'), - ('Schedule max sigma', 'sigma_max'), - ('Schedule min sigma', 'sigma_min'), - ('Schedule rho', 'rho'), - ('Noise multiplier', 'initial_noise_multiplier'), - ('Eta', 'eta_ancestral'), - ('Eta DDIM', 'eta_ddim'), - ('Sigma churn', 's_churn'), - ('Sigma tmin', 's_tmin'), - ('Sigma tmax', 's_tmax'), - ('Sigma noise', 's_noise'), - ('Discard penultimate sigma', 'always_discard_next_to_last_sigma'), - ('UniPC variant', 'uni_pc_variant'), - ('UniPC skip type', 'uni_pc_skip_type'), - ('UniPC order', 'uni_pc_order'), - ('UniPC lower order final', 'uni_pc_lower_order_final'), - ('Token merging ratio', 'token_merging_ratio'), - ('Token merging ratio hr', 'token_merging_ratio_hr'), - ('RNG', 'randn_source'), - ('NGMS', 's_min_uncond'), - ('Pad conds', 'pad_cond_uncond'), - ('VAE', 'sd_vae'), - ('VAE Encoder', 'sd_vae_encode_method'), - ('VAE Decoder', 'sd_vae_decode_method'), - ('Tiling', 'tiling'), - ('Face restoration', 'face_restoration'), ] +""" def create_override_settings_dict(text_pairs): @@ -367,7 +348,8 @@ def create_override_settings_dict(text_pairs): params[k] = v.strip() - for param_name, setting_name in infotext_to_setting_name_mapping: + mapping = [(info.infotext, k) for k, info in shared.opts.data_labels.items() if info.infotext] + for param_name, setting_name in mapping + infotext_to_setting_name_mapping: value = params.get(param_name, None) if value is None: @@ -421,7 +403,8 @@ def connect_paste(button, paste_fields, input_comp, override_settings_component, def paste_settings(params): vals = {} - for param_name, setting_name in infotext_to_setting_name_mapping: + mapping = [(info.infotext, k) for k, info in shared.opts.data_labels.items() if info.infotext] + for param_name, setting_name in mapping + infotext_to_setting_name_mapping: if param_name in already_handled_fields: continue diff --git a/modules/options.py b/modules/options.py index 59cb75ecf..db1fb157e 100644 --- a/modules/options.py +++ b/modules/options.py @@ -8,7 +8,7 @@ from modules.shared_cmd_options import cmd_opts class OptionInfo: - def __init__(self, default=None, label="", component=None, component_args=None, onchange=None, section=None, refresh=None, comment_before='', comment_after=''): + def __init__(self, default=None, label="", component=None, component_args=None, onchange=None, section=None, refresh=None, comment_before='', comment_after='', infotext=None): self.default = default self.label = label self.component = component @@ -24,6 +24,8 @@ class OptionInfo: self.comment_after = comment_after """HTML text that will be added before label in UI""" + self.infotext = infotext + def link(self, label, url): self.comment_before += f"[{label}]" return self diff --git a/modules/shared_options.py b/modules/shared_options.py index f72859d9d..9ae51f186 100644 --- a/modules/shared_options.py +++ b/modules/shared_options.py @@ -92,7 +92,7 @@ options_templates.update(options_section(('upscaling', "Upscaling"), { })) options_templates.update(options_section(('face-restoration', "Face restoration"), { - "face_restoration": OptionInfo(False, "Restore faces").info("will use a third-party model on generation result to reconstruct faces"), + "face_restoration": OptionInfo(False, "Restore faces", infotext='Face restoration').info("will use a third-party model on generation result to reconstruct faces"), "face_restoration_model": OptionInfo("CodeFormer", "Face restoration model", gr.Radio, lambda: {"choices": [x.name() for x in shared.face_restorers]}), "code_former_weight": OptionInfo(0.5, "CodeFormer weight", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}).info("0 = maximum effect; 1 = minimum effect"), "face_restoration_unload": OptionInfo(False, "Move face restoration model from VRAM into RAM after processing"), @@ -127,7 +127,7 @@ 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": shared_items.list_checkpoint_tiles()}, refresh=shared_items.refresh_checkpoints), + "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": shared_items.list_checkpoint_tiles()}, refresh=shared_items.refresh_checkpoints, infotext='Model hash'), "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"), @@ -136,10 +136,10 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "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"), - "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"), + "CLIP_stop_at_last_layers": OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}, infotext="Clip skip").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", "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"), - "tiling": OptionInfo(False, "Tiling").info("produce a tileable picture"), + "tiling": OptionInfo(False, "Tiling", infotext='Tiling').info("produce a tileable picture"), })) options_templates.update(options_section(('sdxl', "Stable Diffusion XL"), { @@ -157,16 +157,16 @@ image into latent space representation and back. Latent space representation is For img2img, VAE is used to process user's input image before the sampling, and to create an image after sampling. """), "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": OptionInfo("Automatic", "SD VAE", gr.Dropdown, lambda: {"choices": shared_items.sd_vae_items()}, refresh=shared_items.refresh_vae_list, infotext='VAE').info("choose VAE model: Automatic = use one with same filename as checkpoint; None = use VAE from checkpoint"), "sd_vae_overrides_per_model_preferences": OptionInfo(True, "Selected VAE overrides per-model preferences").info("you can set per-model VAE either by editing user metadata for checkpoints, or by making the VAE have same name as checkpoint"), "auto_vae_precision": OptionInfo(True, "Automatically revert VAE to 32-bit floats").info("triggers when a tensor with NaNs is produced in VAE; disabling the option in this case will result in a black square image"), - "sd_vae_encode_method": OptionInfo("Full", "VAE type for encode", gr.Radio, {"choices": ["Full", "TAESD"]}).info("method to encode image to latent (use in img2img, hires-fix or inpaint mask)"), - "sd_vae_decode_method": OptionInfo("Full", "VAE type for decode", gr.Radio, {"choices": ["Full", "TAESD"]}).info("method to decode latent to image"), + "sd_vae_encode_method": OptionInfo("Full", "VAE type for encode", gr.Radio, {"choices": ["Full", "TAESD"]}, infotext='VAE Encoder').info("method to encode image to latent (use in img2img, hires-fix or inpaint mask)"), + "sd_vae_decode_method": OptionInfo("Full", "VAE type for decode", gr.Radio, {"choices": ["Full", "TAESD"]}, infotext='VAE Decoder').info("method to decode latent to image"), })) 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}), + "inpainting_mask_weight": OptionInfo(1.0, "Inpainting conditioning mask strength", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}, infotext='Conditional mask weight'), + "initial_noise_multiplier": OptionInfo(1.0, "Noise multiplier for img2img", gr.Slider, {"minimum": 0.5, "maximum": 1.5, "step": 0.01}, infotext='Noise multiplier'), "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, {}), @@ -181,10 +181,10 @@ options_templates.update(options_section(('img2img', "img2img"), { 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"), - "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": OptionInfo(0.0, "Token merging ratio", gr.Slider, {"minimum": 0.0, "maximum": 0.9, "step": 0.1}, infotext='Token merging ratio').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"), - "pad_cond_uncond": OptionInfo(False, "Pad prompt/negative prompt to be same length").info("improves performance when prompt and negative prompt have different lengths; changes seeds"), + "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}, infotext='Token merging ratio hr').info("only applies if non-zero and overrides above"), + "pad_cond_uncond": OptionInfo(False, "Pad prompt/negative prompt to be same length", infotext='Pad conds').info("improves performance when prompt and negative prompt have different lengths; changes seeds"), "persistent_cond_cache": OptionInfo(True, "Persistent cond cache").info("Do not recalculate conds from prompts if prompts have not changed since previous calculation"), })) @@ -284,23 +284,23 @@ options_templates.update(options_section(('ui', "Live previews"), { options_templates.update(options_section(('sampler-params', "Sampler parameters"), { "hide_samplers": OptionInfo([], "Hide samplers in user interface", gr.CheckboxGroup, lambda: {"choices": [x.name for x in shared_items.list_samplers()]}).needs_reload_ui(), - "eta_ddim": OptionInfo(0.0, "Eta for DDIM", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}).info("noise multiplier; higher = more unperdictable results"), - "eta_ancestral": OptionInfo(1.0, "Eta for ancestral samplers", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}).info("noise multiplier; applies to Euler a and other samplers that have a in them"), + "eta_ddim": OptionInfo(0.0, "Eta for DDIM", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}, infotext='Eta DDIM').info("noise multiplier; higher = more unperdictable results"), + "eta_ancestral": OptionInfo(1.0, "Eta for ancestral samplers", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}, infotext='Eta').info("noise multiplier; applies to Euler a and other samplers that have a in them"), "ddim_discretize": OptionInfo('uniform', "img2img DDIM discretize", gr.Radio, {"choices": ['uniform', 'quad']}), - 's_churn': OptionInfo(0.0, "sigma churn", gr.Slider, {"minimum": 0.0, "maximum": 100.0, "step": 0.01}).info('amount of stochasticity; only applies to Euler, Heun, and DPM2'), - 's_tmin': OptionInfo(0.0, "sigma tmin", gr.Slider, {"minimum": 0.0, "maximum": 10.0, "step": 0.01}).info('enable stochasticity; start value of the sigma range; only applies to Euler, Heun, and DPM2'), - 's_tmax': OptionInfo(0.0, "sigma tmax", gr.Slider, {"minimum": 0.0, "maximum": 999.0, "step": 0.01}).info("0 = inf; end value of the sigma range; only applies to Euler, Heun, and DPM2"), - 's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.1, "step": 0.001}).info('amount of additional noise to counteract loss of detail during sampling; only applies to Euler, Heun, and DPM2'), - 'k_sched_type': OptionInfo("Automatic", "Scheduler type", gr.Dropdown, {"choices": ["Automatic", "karras", "exponential", "polyexponential"]}).info("lets you override the noise schedule for k-diffusion samplers; choosing Automatic disables the three parameters below"), - 'sigma_min': OptionInfo(0.0, "sigma min", gr.Number).info("0 = default (~0.03); minimum noise strength for k-diffusion noise scheduler"), - 'sigma_max': OptionInfo(0.0, "sigma max", gr.Number).info("0 = default (~14.6); maximum noise strength for k-diffusion noise scheduler"), - 'rho': OptionInfo(0.0, "rho", gr.Number).info("0 = default (7 for karras, 1 for polyexponential); higher values result in a steeper noise schedule (decreases faster)"), - 'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}).info("ENSD; does not improve anything, just produces different results for ancestral samplers - only useful for reproducing images"), - 'always_discard_next_to_last_sigma': OptionInfo(False, "Always discard next-to-last sigma").link("PR", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/6044"), - 'uni_pc_variant': OptionInfo("bh1", "UniPC variant", gr.Radio, {"choices": ["bh1", "bh2", "vary_coeff"]}), - 'uni_pc_skip_type': OptionInfo("time_uniform", "UniPC skip type", gr.Radio, {"choices": ["time_uniform", "time_quadratic", "logSNR"]}), - 'uni_pc_order': OptionInfo(3, "UniPC order", gr.Slider, {"minimum": 1, "maximum": 50, "step": 1}).info("must be < sampling steps"), - 'uni_pc_lower_order_final': OptionInfo(True, "UniPC lower order final"), + 's_churn': OptionInfo(0.0, "sigma churn", gr.Slider, {"minimum": 0.0, "maximum": 100.0, "step": 0.01}, infotext='Sigma churn').info('amount of stochasticity; only applies to Euler, Heun, and DPM2'), + 's_tmin': OptionInfo(0.0, "sigma tmin", gr.Slider, {"minimum": 0.0, "maximum": 10.0, "step": 0.01}, infotext='Sigma tmin').info('enable stochasticity; start value of the sigma range; only applies to Euler, Heun, and DPM2'), + 's_tmax': OptionInfo(0.0, "sigma tmax", gr.Slider, {"minimum": 0.0, "maximum": 999.0, "step": 0.01}, infotext='Sigma tmax').info("0 = inf; end value of the sigma range; only applies to Euler, Heun, and DPM2"), + 's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.1, "step": 0.001}, infotext='Sigma noise').info('amount of additional noise to counteract loss of detail during sampling; only applies to Euler, Heun, and DPM2'), + 'k_sched_type': OptionInfo("Automatic", "Scheduler type", gr.Dropdown, {"choices": ["Automatic", "karras", "exponential", "polyexponential"]}, infotext='Schedule type').info("lets you override the noise schedule for k-diffusion samplers; choosing Automatic disables the three parameters below"), + 'sigma_min': OptionInfo(0.0, "sigma min", gr.Number, infotext='Schedule max sigma').info("0 = default (~0.03); minimum noise strength for k-diffusion noise scheduler"), + 'sigma_max': OptionInfo(0.0, "sigma max", gr.Number, infotext='Schedule min sigma').info("0 = default (~14.6); maximum noise strength for k-diffusion noise scheduler"), + 'rho': OptionInfo(0.0, "rho", gr.Number, infotext='Schedule rho').info("0 = default (7 for karras, 1 for polyexponential); higher values result in a steeper noise schedule (decreases faster)"), + 'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}, infotext='ENSD').info("ENSD; does not improve anything, just produces different results for ancestral samplers - only useful for reproducing images"), + 'always_discard_next_to_last_sigma': OptionInfo(False, "Always discard next-to-last sigma", infotext='Discard penultimate sigma').link("PR", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/6044"), + 'uni_pc_variant': OptionInfo("bh1", "UniPC variant", gr.Radio, {"choices": ["bh1", "bh2", "vary_coeff"]}, infotext='UniPC variant'), + 'uni_pc_skip_type': OptionInfo("time_uniform", "UniPC skip type", gr.Radio, {"choices": ["time_uniform", "time_quadratic", "logSNR"]}, infotext='UniPC skip type'), + 'uni_pc_order': OptionInfo(3, "UniPC order", gr.Slider, {"minimum": 1, "maximum": 50, "step": 1}, infotext='UniPC order').info("must be < sampling steps"), + 'uni_pc_lower_order_final': OptionInfo(True, "UniPC lower order final", infotext='UniPC lower order final'), })) options_templates.update(options_section(('postprocessing', "Postprocessing"), {