From 3bca90b249d749ed5429f76e380d2ffa52fc0d41 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Sun, 30 Jul 2023 13:48:27 +0300 Subject: hires fix checkpoint selection --- modules/shared.py | 19 +++++++++++++------ 1 file changed, 13 insertions(+), 6 deletions(-) (limited to 'modules/shared.py') diff --git a/modules/shared.py b/modules/shared.py index aa72c9c8..807fb9e3 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -220,12 +220,19 @@ class State: return import modules.sd_samplers - if opts.show_progress_grid: - self.assign_current_image(modules.sd_samplers.samples_to_image_grid(self.current_latent)) - else: - self.assign_current_image(modules.sd_samplers.sample_to_image(self.current_latent)) - self.current_image_sampling_step = self.sampling_step + try: + if opts.show_progress_grid: + self.assign_current_image(modules.sd_samplers.samples_to_image_grid(self.current_latent)) + else: + self.assign_current_image(modules.sd_samplers.sample_to_image(self.current_latent)) + + self.current_image_sampling_step = self.sampling_step + + except Exception: + # when switching models during genration, VAE would be on CPU, so creating an image will fail. + # we silently ignore this error + errors.record_exception() def assign_current_image(self, image): self.current_image = image @@ -512,7 +519,7 @@ options_templates.update(options_section(('ui', "User interface"), { "ui_tab_order": OptionInfo([], "UI tab order", ui_components.DropdownMulti, lambda: {"choices": list(tab_names)}).needs_restart(), "hidden_tabs": OptionInfo([], "Hidden UI tabs", ui_components.DropdownMulti, lambda: {"choices": list(tab_names)}).needs_restart(), "ui_reorder_list": OptionInfo([], "txt2img/img2img UI item order", ui_components.DropdownMulti, lambda: {"choices": list(shared_items.ui_reorder_categories())}).info("selected items appear first").needs_restart(), - "hires_fix_show_sampler": OptionInfo(False, "Hires fix: show hires sampler selection").needs_restart(), + "hires_fix_show_sampler": OptionInfo(False, "Hires fix: show hires checkpoint and sampler selection").needs_restart(), "hires_fix_show_prompts": OptionInfo(False, "Hires fix: show hires prompt and negative prompt").needs_restart(), "disable_token_counters": OptionInfo(False, "Disable prompt token counters").needs_restart(), })) -- cgit v1.2.3 From b235022c615a7384f73c05fe240d8f4a28d103d4 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Tue, 1 Aug 2023 00:24:48 +0300 Subject: option to keep multiple models in memory --- modules/lowvram.py | 3 + modules/sd_hijack.py | 6 +- modules/sd_hijack_inpainting.py | 5 +- modules/sd_models.py | 136 +++++++++++++++++++++++++++++++++------- modules/sd_models_xl.py | 8 +-- modules/shared.py | 12 +++- 6 files changed, 135 insertions(+), 35 deletions(-) (limited to 'modules/shared.py') diff --git a/modules/lowvram.py b/modules/lowvram.py index 3f830664..96f52b7b 100644 --- a/modules/lowvram.py +++ b/modules/lowvram.py @@ -15,6 +15,9 @@ def send_everything_to_cpu(): def setup_for_low_vram(sd_model, use_medvram): + if getattr(sd_model, 'lowvram', False): + return + sd_model.lowvram = True parents = {} diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py index cfa5f0eb..7d692e3c 100644 --- a/modules/sd_hijack.py +++ b/modules/sd_hijack.py @@ -30,8 +30,10 @@ ldm.modules.attention.MemoryEfficientCrossAttention = ldm.modules.attention.Cros ldm.modules.attention.BasicTransformerBlock.ATTENTION_MODES["softmax-xformers"] = ldm.modules.attention.CrossAttention # silence new console spam from SD2 -ldm.modules.attention.print = lambda *args: None -ldm.modules.diffusionmodules.model.print = lambda *args: None +ldm.modules.attention.print = shared.ldm_print +ldm.modules.diffusionmodules.model.print = shared.ldm_print +ldm.util.print = shared.ldm_print +ldm.models.diffusion.ddpm.print = shared.ldm_print optimizers = [] current_optimizer: sd_hijack_optimizations.SdOptimization = None diff --git a/modules/sd_hijack_inpainting.py b/modules/sd_hijack_inpainting.py index c1977b19..97350f4f 100644 --- a/modules/sd_hijack_inpainting.py +++ b/modules/sd_hijack_inpainting.py @@ -91,7 +91,4 @@ def p_sample_plms(self, x, c, t, index, repeat_noise=False, use_original_steps=F return x_prev, pred_x0, e_t -def do_inpainting_hijack(): - # p_sample_plms is needed because PLMS can't work with dicts as conditionings - - ldm.models.diffusion.plms.PLMSSampler.p_sample_plms = p_sample_plms +ldm.models.diffusion.plms.PLMSSampler.p_sample_plms = p_sample_plms diff --git a/modules/sd_models.py b/modules/sd_models.py index acb1e817..77195f2f 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -15,7 +15,6 @@ import ldm.modules.midas as midas from ldm.util import instantiate_from_config from modules import paths, shared, modelloader, devices, script_callbacks, sd_vae, sd_disable_initialization, errors, hashes, sd_models_config, sd_unet, sd_models_xl -from modules.sd_hijack_inpainting import do_inpainting_hijack from modules.timer import Timer import tomesd @@ -423,6 +422,7 @@ sdxl_refiner_clip_weight = 'conditioner.embedders.0.model.ln_final.weight' class SdModelData: def __init__(self): self.sd_model = None + self.loaded_sd_models = [] self.was_loaded_at_least_once = False self.lock = threading.Lock() @@ -437,6 +437,7 @@ class SdModelData: try: load_model() + except Exception as e: errors.display(e, "loading stable diffusion model", full_traceback=True) print("", file=sys.stderr) @@ -448,11 +449,24 @@ class SdModelData: def set_sd_model(self, v): self.sd_model = v + try: + self.loaded_sd_models.remove(v) + except ValueError: + pass + + if v is not None: + self.loaded_sd_models.insert(0, v) + model_data = SdModelData() def get_empty_cond(sd_model): + from modules import extra_networks, processing + + p = processing.StableDiffusionProcessingTxt2Img() + extra_networks.activate(p, {}) + if hasattr(sd_model, 'conditioner'): d = sd_model.get_learned_conditioning([""]) return d['crossattn'] @@ -460,19 +474,43 @@ def get_empty_cond(sd_model): return sd_model.cond_stage_model([""]) +def send_model_to_cpu(m): + from modules import lowvram + + if shared.cmd_opts.lowvram or shared.cmd_opts.medvram: + lowvram.send_everything_to_cpu() + else: + m.to(devices.cpu) + + devices.torch_gc() + + +def send_model_to_device(m): + from modules import lowvram + + if shared.cmd_opts.lowvram or shared.cmd_opts.medvram: + lowvram.setup_for_low_vram(m, shared.cmd_opts.medvram) + else: + m.to(shared.device) + + +def send_model_to_trash(m): + m.to(device="meta") + devices.torch_gc() + + def load_model(checkpoint_info=None, already_loaded_state_dict=None): - from modules import lowvram, sd_hijack + from modules import sd_hijack checkpoint_info = checkpoint_info or select_checkpoint() + timer = Timer() + if model_data.sd_model: - sd_hijack.model_hijack.undo_hijack(model_data.sd_model) + send_model_to_trash(model_data.sd_model) model_data.sd_model = None - gc.collect() devices.torch_gc() - do_inpainting_hijack() - - timer = Timer() + timer.record("unload existing model") if already_loaded_state_dict is not None: state_dict = already_loaded_state_dict @@ -512,12 +550,9 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None): with sd_disable_initialization.LoadStateDictOnMeta(state_dict, devices.cpu): load_model_weights(sd_model, checkpoint_info, state_dict, timer) + timer.record("load weights from state dict") - if shared.cmd_opts.lowvram or shared.cmd_opts.medvram: - lowvram.setup_for_low_vram(sd_model, shared.cmd_opts.medvram) - else: - sd_model.to(shared.device) - + send_model_to_device(sd_model) timer.record("move model to device") sd_hijack.model_hijack.hijack(sd_model) @@ -525,7 +560,7 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None): timer.record("hijack") sd_model.eval() - model_data.sd_model = sd_model + model_data.set_sd_model(sd_model) model_data.was_loaded_at_least_once = True sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings(force_reload=True) # Reload embeddings after model load as they may or may not fit the model @@ -546,10 +581,61 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None): return sd_model +def reuse_model_from_already_loaded(sd_model, checkpoint_info, timer): + """ + Checks if the desired checkpoint from checkpoint_info is not already loaded in model_data.loaded_sd_models. + If it is loaded, returns that (moving it to GPU if necessary, and moving the currently loadded model to CPU if necessary). + If not, returns the model that can be used to load weights from checkpoint_info's file. + If no such model exists, returns None. + Additionaly deletes loaded models that are over the limit set in settings (sd_checkpoints_limit). + """ + + already_loaded = None + for i in reversed(range(len(model_data.loaded_sd_models))): + loaded_model = model_data.loaded_sd_models[i] + if loaded_model.sd_checkpoint_info.filename == checkpoint_info.filename: + already_loaded = loaded_model + continue + + if len(model_data.loaded_sd_models) > shared.opts.sd_checkpoints_limit > 0: + print(f"Unloading model {len(model_data.loaded_sd_models)} over the limit of {shared.opts.sd_checkpoints_limit}: {loaded_model.sd_checkpoint_info.title}") + model_data.loaded_sd_models.pop() + send_model_to_trash(loaded_model) + timer.record("send model to trash") + + if shared.opts.sd_checkpoints_keep_in_cpu: + send_model_to_cpu(sd_model) + timer.record("send model to cpu") + + if already_loaded is not None: + send_model_to_device(already_loaded) + timer.record("send model to device") + + model_data.set_sd_model(already_loaded) + print(f"Using already loaded model {already_loaded.sd_checkpoint_info.title}: done in {timer.summary()}") + return model_data.sd_model + elif shared.opts.sd_checkpoints_limit > 1 and len(model_data.loaded_sd_models) < shared.opts.sd_checkpoints_limit: + print(f"Loading model {checkpoint_info.title} ({len(model_data.loaded_sd_models) + 1} out of {shared.opts.sd_checkpoints_limit})") + + model_data.sd_model = None + load_model(checkpoint_info) + return model_data.sd_model + elif len(model_data.loaded_sd_models) > 0: + sd_model = model_data.loaded_sd_models.pop() + model_data.sd_model = sd_model + + print(f"Reusing loaded model {sd_model.sd_checkpoint_info.title} to load {checkpoint_info.title}") + return sd_model + else: + return None + + def reload_model_weights(sd_model=None, info=None): - from modules import lowvram, devices, sd_hijack + from modules import devices, sd_hijack checkpoint_info = info or select_checkpoint() + timer = Timer() + if not sd_model: sd_model = model_data.sd_model @@ -558,19 +644,17 @@ def reload_model_weights(sd_model=None, info=None): else: current_checkpoint_info = sd_model.sd_checkpoint_info if sd_model.sd_model_checkpoint == checkpoint_info.filename: - return - - sd_unet.apply_unet("None") + return sd_model - if shared.cmd_opts.lowvram or shared.cmd_opts.medvram: - lowvram.send_everything_to_cpu() - else: - sd_model.to(devices.cpu) + sd_model = reuse_model_from_already_loaded(sd_model, checkpoint_info, timer) + if sd_model is not None and sd_model.sd_checkpoint_info.filename == checkpoint_info.filename: + return sd_model + if sd_model is not None: + sd_unet.apply_unet("None") + send_model_to_cpu(sd_model) sd_hijack.model_hijack.undo_hijack(sd_model) - timer = Timer() - state_dict = get_checkpoint_state_dict(checkpoint_info, timer) checkpoint_config = sd_models_config.find_checkpoint_config(state_dict, checkpoint_info) @@ -578,7 +662,9 @@ def reload_model_weights(sd_model=None, info=None): timer.record("find config") if sd_model is None or checkpoint_config != sd_model.used_config: - del sd_model + if sd_model is not None: + send_model_to_trash(sd_model) + load_model(checkpoint_info, already_loaded_state_dict=state_dict) return model_data.sd_model @@ -601,6 +687,8 @@ def reload_model_weights(sd_model=None, info=None): print(f"Weights loaded in {timer.summary()}.") + model_data.set_sd_model(sd_model) + return sd_model diff --git a/modules/sd_models_xl.py b/modules/sd_models_xl.py index bc219508..01123321 100644 --- a/modules/sd_models_xl.py +++ b/modules/sd_models_xl.py @@ -98,10 +98,10 @@ def extend_sdxl(model): model.conditioner.wrapped = torch.nn.Module() -sgm.modules.attention.print = lambda *args: None -sgm.modules.diffusionmodules.model.print = lambda *args: None -sgm.modules.diffusionmodules.openaimodel.print = lambda *args: None -sgm.modules.encoders.modules.print = lambda *args: None +sgm.modules.attention.print = shared.ldm_print +sgm.modules.diffusionmodules.model.print = shared.ldm_print +sgm.modules.diffusionmodules.openaimodel.print = shared.ldm_print +sgm.modules.encoders.modules.print = shared.ldm_print # this gets the code to load the vanilla attention that we override sgm.modules.attention.SDP_IS_AVAILABLE = True diff --git a/modules/shared.py b/modules/shared.py index aa72c9c8..0184fcd0 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -392,6 +392,7 @@ options_templates.update(options_section(('system', "System"), { "print_hypernet_extra": OptionInfo(False, "Print extra hypernetwork information to console."), "list_hidden_files": OptionInfo(True, "Load models/files in hidden directories").info("directory is hidden if its name starts with \".\""), "disable_mmap_load_safetensors": OptionInfo(False, "Disable memmapping for loading .safetensors files.").info("fixes very slow loading speed in some cases"), + "hide_ldm_prints": OptionInfo(True, "Prevent Stability-AI's ldm/sgm modules from printing noise to console."), })) options_templates.update(options_section(('training', "Training"), { @@ -411,7 +412,9 @@ options_templates.update(options_section(('training', "Training"), { options_templates.update(options_section(('sd', "Stable Diffusion"), { "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": list_checkpoint_tiles()}, refresh=refresh_checkpoints), - "sd_checkpoint_cache": OptionInfo(0, "Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}), + "sd_checkpoints_limit": OptionInfo(1, "Maximum number of checkpoints loaded at the same time", gr.Slider, {"minimum": 1, "maximum": 10, "step": 1}), + "sd_checkpoints_keep_in_cpu": OptionInfo(True, "Only keep one model on device").info("will keep models other than the currently used one in RAM rather than VRAM"), + "sd_checkpoint_cache": OptionInfo(0, "Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}).info("obsolete; set to 0 and use the two settings above instead"), "sd_vae_checkpoint_cache": OptionInfo(0, "VAE Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}), "sd_vae": OptionInfo("Automatic", "SD VAE", gr.Dropdown, lambda: {"choices": shared_items.sd_vae_items()}, refresh=shared_items.refresh_vae_list).info("choose VAE model: Automatic = use one with same filename as checkpoint; None = use VAE from checkpoint"), "sd_vae_as_default": OptionInfo(True, "Ignore selected VAE for stable diffusion checkpoints that have their own .vae.pt next to them"), @@ -889,3 +892,10 @@ def walk_files(path, allowed_extensions=None): continue yield os.path.join(root, filename) + + +def ldm_print(*args, **kwargs): + if opts.hide_ldm_prints: + return + + print(*args, **kwargs) -- cgit v1.2.3 From 84b6fcd02ca6d6ab48c4b6be4bb8724b1c2e7014 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Thu, 3 Aug 2023 00:00:23 +0300 Subject: add NV option for Random number generator source setting, which allows to generate same pictures on CPU/AMD/Mac as on NVidia videocards. --- modules/devices.py | 39 ++++++++++++++- modules/processing.py | 6 +-- modules/rng_philox.py | 100 ++++++++++++++++++++++++++++++++++++++ modules/sd_samplers_kdiffusion.py | 5 +- modules/shared.py | 2 +- 5 files changed, 142 insertions(+), 10 deletions(-) create mode 100644 modules/rng_philox.py (limited to 'modules/shared.py') diff --git a/modules/devices.py b/modules/devices.py index 57e51da3..b58776d8 100644 --- a/modules/devices.py +++ b/modules/devices.py @@ -3,7 +3,7 @@ import contextlib from functools import lru_cache import torch -from modules import errors +from modules import errors, rng_philox if sys.platform == "darwin": from modules import mac_specific @@ -90,23 +90,58 @@ def cond_cast_float(input): return input.float() if unet_needs_upcast else input +nv_rng = None + + def randn(seed, shape): from modules.shared import opts - torch.manual_seed(seed) + manual_seed(seed) + + if opts.randn_source == "NV": + return torch.asarray(nv_rng.randn(shape), device=device) + if opts.randn_source == "CPU" or device.type == 'mps': return torch.randn(shape, device=cpu).to(device) + return torch.randn(shape, device=device) +def randn_like(x): + from modules.shared import opts + + if opts.randn_source == "NV": + return torch.asarray(nv_rng.randn(x.shape), device=x.device, dtype=x.dtype) + + if opts.randn_source == "CPU" or x.device.type == 'mps': + return torch.randn_like(x, device=cpu).to(x.device) + + return torch.randn_like(x) + + def randn_without_seed(shape): from modules.shared import opts + if opts.randn_source == "NV": + return torch.asarray(nv_rng.randn(shape), device=device) + if opts.randn_source == "CPU" or device.type == 'mps': return torch.randn(shape, device=cpu).to(device) + return torch.randn(shape, device=device) +def manual_seed(seed): + from modules.shared import opts + + if opts.randn_source == "NV": + global nv_rng + nv_rng = rng_philox.Generator(seed) + return + + torch.manual_seed(seed) + + def autocast(disable=False): from modules import shared diff --git a/modules/processing.py b/modules/processing.py index 0b66cd2a..8f34c8b4 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -492,7 +492,7 @@ def create_random_tensors(shape, seeds, subseeds=None, subseed_strength=0.0, see noise_shape = shape if seed_resize_from_h <= 0 or seed_resize_from_w <= 0 else (shape[0], seed_resize_from_h//8, seed_resize_from_w//8) subnoise = None - if subseeds is not None: + if subseeds is not None and subseed_strength != 0: subseed = 0 if i >= len(subseeds) else subseeds[i] subnoise = devices.randn(subseed, noise_shape) @@ -524,7 +524,7 @@ def create_random_tensors(shape, seeds, subseeds=None, subseed_strength=0.0, see cnt = p.sampler.number_of_needed_noises(p) if eta_noise_seed_delta > 0: - torch.manual_seed(seed + eta_noise_seed_delta) + devices.manual_seed(seed + eta_noise_seed_delta) for j in range(cnt): sampler_noises[j].append(devices.randn_without_seed(tuple(noise_shape))) @@ -636,7 +636,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter "Token merging ratio": None if token_merging_ratio == 0 else token_merging_ratio, "Token merging ratio hr": None if not enable_hr or token_merging_ratio_hr == 0 else token_merging_ratio_hr, "Init image hash": getattr(p, 'init_img_hash', None), - "RNG": opts.randn_source if opts.randn_source != "GPU" else None, + "RNG": opts.randn_source if opts.randn_source != "GPU" and opts.randn_source != "NV" else None, "NGMS": None if p.s_min_uncond == 0 else p.s_min_uncond, **p.extra_generation_params, "Version": program_version() if opts.add_version_to_infotext else None, diff --git a/modules/rng_philox.py b/modules/rng_philox.py new file mode 100644 index 00000000..b5c02483 --- /dev/null +++ b/modules/rng_philox.py @@ -0,0 +1,100 @@ +"""RNG imitiating torch cuda randn on CPU. You are welcome. + +Usage: + +``` +g = Generator(seed=0) +print(g.randn(shape=(3, 4))) +``` + +Expected output: +``` +[[-0.92466259 -0.42534415 -2.6438457 0.14518388] + [-0.12086647 -0.57972564 -0.62285122 -0.32838709] + [-1.07454231 -0.36314407 -1.67105067 2.26550497]] +``` +""" + +import numpy as np + +philox_m = [0xD2511F53, 0xCD9E8D57] +philox_w = [0x9E3779B9, 0xBB67AE85] + +two_pow32_inv = np.array([2.3283064e-10], dtype=np.float32) +two_pow32_inv_2pi = np.array([2.3283064e-10 * 6.2831855], dtype=np.float32) + + +def uint32(x): + """Converts (N,) np.uint64 array into (2, N) np.unit32 array.""" + return np.moveaxis(x.view(np.uint32).reshape(-1, 2), 0, 1) + + +def philox4_round(counter, key): + """A single round of the Philox 4x32 random number generator.""" + + v1 = uint32(counter[0].astype(np.uint64) * philox_m[0]) + v2 = uint32(counter[2].astype(np.uint64) * philox_m[1]) + + counter[0] = v2[1] ^ counter[1] ^ key[0] + counter[1] = v2[0] + counter[2] = v1[1] ^ counter[3] ^ key[1] + counter[3] = v1[0] + + +def philox4_32(counter, key, rounds=10): + """Generates 32-bit random numbers using the Philox 4x32 random number generator. + + Parameters: + counter (numpy.ndarray): A 4xN array of 32-bit integers representing the counter values (offset into generation). + key (numpy.ndarray): A 2xN array of 32-bit integers representing the key values (seed). + rounds (int): The number of rounds to perform. + + Returns: + numpy.ndarray: A 4xN array of 32-bit integers containing the generated random numbers. + """ + + for _ in range(rounds - 1): + philox4_round(counter, key) + + key[0] = key[0] + philox_w[0] + key[1] = key[1] + philox_w[1] + + philox4_round(counter, key) + return counter + + +def box_muller(x, y): + """Returns just the first out of two numbers generated by Box–Muller transform algorithm.""" + u = x.astype(np.float32) * two_pow32_inv + two_pow32_inv / 2 + v = y.astype(np.float32) * two_pow32_inv_2pi + two_pow32_inv_2pi / 2 + + s = np.sqrt(-2.0 * np.log(u)) + + r1 = s * np.sin(v) + return r1.astype(np.float32) + + +class Generator: + """RNG that produces same outputs as torch.randn(..., device='cuda') on CPU""" + + def __init__(self, seed): + self.seed = seed + self.offset = 0 + + def randn(self, shape): + """Generate a sequence of n standard normal random variables using the Philox 4x32 random number generator and the Box-Muller transform.""" + + n = 1 + for x in shape: + n *= x + + counter = np.zeros((4, n), dtype=np.uint32) + counter[0] = self.offset + counter[2] = np.arange(n, dtype=np.uint32) # up to 2^32 numbers can be generated - if you want more you'd need to spill into counter[3] + self.offset += 1 + + key = uint32(np.array([[self.seed] * n], dtype=np.uint64)) + + g = philox4_32(counter, key) + + return box_muller(g[0], g[1]).reshape(shape) # discard g[2] and g[3] diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index e0da3425..d72c1b5f 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -260,10 +260,7 @@ class TorchHijack: if noise.shape == x.shape: return noise - if opts.randn_source == "CPU" or x.device.type == 'mps': - return torch.randn_like(x, device=devices.cpu).to(x.device) - else: - return torch.randn_like(x) + return devices.randn_like(x) class KDiffusionSampler: diff --git a/modules/shared.py b/modules/shared.py index aa72c9c8..7103b4ca 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -428,7 +428,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "CLIP_stop_at_last_layers": OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}).link("wiki", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#clip-skip").info("ignore last layers of CLIP network; 1 ignores none, 2 ignores one layer"), "upcast_attn": OptionInfo(False, "Upcast cross attention layer to float32"), "auto_vae_precision": OptionInfo(True, "Automaticlly revert VAE to 32-bit floats").info("triggers when a tensor with NaNs is produced in VAE; disabling the option in this case will result in a black square image"), - "randn_source": OptionInfo("GPU", "Random number generator source.", gr.Radio, {"choices": ["GPU", "CPU"]}).info("changes seeds drastically; use CPU to produce the same picture across different videocard vendors"), + "randn_source": OptionInfo("GPU", "Random number generator source.", gr.Radio, {"choices": ["GPU", "CPU", "NV"]}).info("changes seeds drastically; use CPU to produce the same picture across different videocard vendors; use NV to produce same picture as on NVidia videocards"), })) options_templates.update(options_section(('sdxl', "Stable Diffusion XL"), { -- cgit v1.2.3 From 362789a3793025c698fa42372fd66c3c4f2d6413 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Fri, 4 Aug 2023 07:50:17 +0300 Subject: gradio 3.39 --- extensions-builtin/Lora/ui_edit_user_metadata.py | 2 +- modules/gradio_extensons.py | 60 ++++++++++++++++++++++++ modules/scripts.py | 60 ------------------------ modules/shared.py | 3 +- modules/ui.py | 24 +++++----- modules/ui_checkpoint_merger.py | 2 +- modules/ui_common.py | 2 +- modules/ui_components.py | 2 +- modules/ui_extensions.py | 8 ++-- modules/ui_postprocessing.py | 2 +- requirements.txt | 2 +- requirements_versions.txt | 2 +- style.css | 12 ++++- 13 files changed, 95 insertions(+), 86 deletions(-) create mode 100644 modules/gradio_extensons.py (limited to 'modules/shared.py') diff --git a/extensions-builtin/Lora/ui_edit_user_metadata.py b/extensions-builtin/Lora/ui_edit_user_metadata.py index 2ca997f7..390d9dde 100644 --- a/extensions-builtin/Lora/ui_edit_user_metadata.py +++ b/extensions-builtin/Lora/ui_edit_user_metadata.py @@ -167,7 +167,7 @@ class LoraUserMetadataEditor(ui_extra_networks_user_metadata.UserMetadataEditor) random_prompt = gr.Textbox(label='Random prompt', lines=4, max_lines=4, interactive=False) with gr.Column(scale=1, min_width=120): - generate_random_prompt = gr.Button('Generate').style(full_width=True, size="lg") + generate_random_prompt = gr.Button('Generate', size="lg", scale=1) self.edit_notes = gr.TextArea(label='Notes', lines=4) diff --git a/modules/gradio_extensons.py b/modules/gradio_extensons.py new file mode 100644 index 00000000..5af7fd8e --- /dev/null +++ b/modules/gradio_extensons.py @@ -0,0 +1,60 @@ +import gradio as gr + +from modules import scripts + +def add_classes_to_gradio_component(comp): + """ + this adds gradio-* to the component for css styling (ie gradio-button to gr.Button), as well as some others + """ + + comp.elem_classes = [f"gradio-{comp.get_block_name()}", *(comp.elem_classes or [])] + + if getattr(comp, 'multiselect', False): + comp.elem_classes.append('multiselect') + + +def IOComponent_init(self, *args, **kwargs): + self.webui_tooltip = kwargs.pop('tooltip', None) + + if scripts.scripts_current is not None: + scripts.scripts_current.before_component(self, **kwargs) + + scripts.script_callbacks.before_component_callback(self, **kwargs) + + res = original_IOComponent_init(self, *args, **kwargs) + + add_classes_to_gradio_component(self) + + scripts.script_callbacks.after_component_callback(self, **kwargs) + + if scripts.scripts_current is not None: + scripts.scripts_current.after_component(self, **kwargs) + + return res + + +def Block_get_config(self): + config = original_Block_get_config(self) + + webui_tooltip = getattr(self, 'webui_tooltip', None) + if webui_tooltip: + config["webui_tooltip"] = webui_tooltip + + return config + + +def BlockContext_init(self, *args, **kwargs): + res = original_BlockContext_init(self, *args, **kwargs) + + add_classes_to_gradio_component(self) + + return res + + +original_IOComponent_init = gr.components.IOComponent.__init__ +original_Block_get_config = gr.blocks.Block.get_config +original_BlockContext_init = gr.blocks.BlockContext.__init__ + +gr.components.IOComponent.__init__ = IOComponent_init +gr.blocks.Block.get_config = Block_get_config +gr.blocks.BlockContext.__init__ = BlockContext_init diff --git a/modules/scripts.py b/modules/scripts.py index edf7347e..f7d060aa 100644 --- a/modules/scripts.py +++ b/modules/scripts.py @@ -631,63 +631,3 @@ def reload_script_body_only(): reload_scripts = load_scripts # compatibility alias - - -def add_classes_to_gradio_component(comp): - """ - this adds gradio-* to the component for css styling (ie gradio-button to gr.Button), as well as some others - """ - - comp.elem_classes = [f"gradio-{comp.get_block_name()}", *(comp.elem_classes or [])] - - if getattr(comp, 'multiselect', False): - comp.elem_classes.append('multiselect') - - - -def IOComponent_init(self, *args, **kwargs): - self.webui_tooltip = kwargs.pop('tooltip', None) - - if scripts_current is not None: - scripts_current.before_component(self, **kwargs) - - script_callbacks.before_component_callback(self, **kwargs) - - res = original_IOComponent_init(self, *args, **kwargs) - - add_classes_to_gradio_component(self) - - script_callbacks.after_component_callback(self, **kwargs) - - if scripts_current is not None: - scripts_current.after_component(self, **kwargs) - - return res - - -def Block_get_config(self): - config = original_Block_get_config(self) - - webui_tooltip = getattr(self, 'webui_tooltip', None) - if webui_tooltip: - config["webui_tooltip"] = webui_tooltip - - return config - - -original_IOComponent_init = gr.components.IOComponent.__init__ -original_Block_get_config = gr.components.Block.get_config -gr.components.IOComponent.__init__ = IOComponent_init -gr.components.Block.get_config = Block_get_config - - -def BlockContext_init(self, *args, **kwargs): - res = original_BlockContext_init(self, *args, **kwargs) - - add_classes_to_gradio_component(self) - - return res - - -original_BlockContext_init = gr.blocks.BlockContext.__init__ -gr.blocks.BlockContext.__init__ = BlockContext_init diff --git a/modules/shared.py b/modules/shared.py index 7103b4ca..cec030f7 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -385,7 +385,8 @@ options_templates.update(options_section(('face-restoration', "Face restoration" })) options_templates.update(options_section(('system', "System"), { - "show_warnings": OptionInfo(False, "Show warnings in console."), + "show_warnings": OptionInfo(False, "Show warnings in console.").needs_restart(), + "show_gradio_deprecation_warnings": OptionInfo(True, "Show gradio deprecation warnings in console.").needs_restart(), "memmon_poll_rate": OptionInfo(8, "VRAM usage polls per second during generation.", gr.Slider, {"minimum": 0, "maximum": 40, "step": 1}).info("0 = disable"), "samples_log_stdout": OptionInfo(False, "Always print all generation info to standard output"), "multiple_tqdm": OptionInfo(True, "Add a second progress bar to the console that shows progress for an entire job."), diff --git a/modules/ui.py b/modules/ui.py index 03306ba9..822a7660 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -12,6 +12,7 @@ import numpy as np from PIL import Image, PngImagePlugin # noqa: F401 from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call +from modules import gradio_extensons # noqa: F401 from modules import sd_hijack, sd_models, script_callbacks, ui_extensions, deepbooru, extra_networks, ui_common, ui_postprocessing, progress, ui_loadsave, errors, shared_items, ui_settings, timer, sysinfo, ui_checkpoint_merger, ui_prompt_styles, scripts from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML from modules.paths import script_path @@ -34,6 +35,7 @@ from modules.generation_parameters_copypaste import image_from_url_text create_setting_component = ui_settings.create_setting_component warnings.filterwarnings("default" if opts.show_warnings else "ignore", category=UserWarning) +warnings.filterwarnings("default" if opts.show_gradio_deprecation_warnings else "ignore", category=gr.deprecation.GradioDeprecationWarning) # this is a fix for Windows users. Without it, javascript files will be served with text/html content-type and the browser will not show any UI mimetypes.init() @@ -146,7 +148,6 @@ def interrogate_deepbooru(image): def create_seed_inputs(target_interface): with FormRow(elem_id=f"{target_interface}_seed_row", variant="compact"): seed = (gr.Textbox if cmd_opts.use_textbox_seed else gr.Number)(label='Seed', value=-1, elem_id=f"{target_interface}_seed") - seed.style(container=False) random_seed = ToolButton(random_symbol, elem_id=f"{target_interface}_random_seed", label='Random seed') reuse_seed = ToolButton(reuse_symbol, elem_id=f"{target_interface}_reuse_seed", label='Reuse seed') @@ -158,7 +159,6 @@ def create_seed_inputs(target_interface): with FormRow(visible=False, elem_id=f"{target_interface}_subseed_row") as seed_extra_row_1: seed_extras.append(seed_extra_row_1) subseed = gr.Number(label='Variation seed', value=-1, elem_id=f"{target_interface}_subseed") - subseed.style(container=False) random_subseed = ToolButton(random_symbol, elem_id=f"{target_interface}_random_subseed") reuse_subseed = ToolButton(reuse_symbol, elem_id=f"{target_interface}_reuse_subseed") subseed_strength = gr.Slider(label='Variation strength', value=0.0, minimum=0, maximum=1, step=0.01, elem_id=f"{target_interface}_subseed_strength") @@ -408,7 +408,7 @@ def create_ui(): from modules import ui_extra_networks extra_networks_ui = ui_extra_networks.create_ui(extra_networks, toprow.extra_networks_button, 'txt2img') - with gr.Row().style(equal_height=False): + with gr.Row(equal_height=False): with gr.Column(variant='compact', elem_id="txt2img_settings"): scripts.scripts_txt2img.prepare_ui() @@ -636,7 +636,7 @@ def create_ui(): from modules import ui_extra_networks extra_networks_ui_img2img = ui_extra_networks.create_ui(extra_networks, toprow.extra_networks_button, 'img2img') - with FormRow().style(equal_height=False): + with FormRow(equal_height=False): with gr.Column(variant='compact', elem_id="img2img_settings"): copy_image_buttons = [] copy_image_destinations = {} @@ -658,19 +658,19 @@ def create_ui(): img2img_selected_tab = gr.State(0) with gr.TabItem('img2img', id='img2img', elem_id="img2img_img2img_tab") as tab_img2img: - init_img = gr.Image(label="Image for img2img", elem_id="img2img_image", show_label=False, source="upload", interactive=True, type="pil", tool="editor", image_mode="RGBA").style(height=opts.img2img_editor_height) + init_img = gr.Image(label="Image for img2img", elem_id="img2img_image", show_label=False, source="upload", interactive=True, type="pil", tool="editor", image_mode="RGBA", height=opts.img2img_editor_height) add_copy_image_controls('img2img', init_img) with gr.TabItem('Sketch', id='img2img_sketch', elem_id="img2img_img2img_sketch_tab") as tab_sketch: - sketch = gr.Image(label="Image for img2img", elem_id="img2img_sketch", show_label=False, source="upload", interactive=True, type="pil", tool="color-sketch", image_mode="RGBA").style(height=opts.img2img_editor_height) + sketch = gr.Image(label="Image for img2img", elem_id="img2img_sketch", show_label=False, source="upload", interactive=True, type="pil", tool="color-sketch", image_mode="RGBA", height=opts.img2img_editor_height) add_copy_image_controls('sketch', sketch) with gr.TabItem('Inpaint', id='inpaint', elem_id="img2img_inpaint_tab") as tab_inpaint: - init_img_with_mask = gr.Image(label="Image for inpainting with mask", show_label=False, elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool="sketch", image_mode="RGBA").style(height=opts.img2img_editor_height) + init_img_with_mask = gr.Image(label="Image for inpainting with mask", show_label=False, elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool="sketch", image_mode="RGBA", height=opts.img2img_editor_height) add_copy_image_controls('inpaint', init_img_with_mask) with gr.TabItem('Inpaint sketch', id='inpaint_sketch', elem_id="img2img_inpaint_sketch_tab") as tab_inpaint_color: - inpaint_color_sketch = gr.Image(label="Color sketch inpainting", show_label=False, elem_id="inpaint_sketch", source="upload", interactive=True, type="pil", tool="color-sketch", image_mode="RGBA").style(height=opts.img2img_editor_height) + inpaint_color_sketch = gr.Image(label="Color sketch inpainting", show_label=False, elem_id="inpaint_sketch", source="upload", interactive=True, type="pil", tool="color-sketch", image_mode="RGBA", height=opts.img2img_editor_height) inpaint_color_sketch_orig = gr.State(None) add_copy_image_controls('inpaint_sketch', inpaint_color_sketch) @@ -993,7 +993,7 @@ def create_ui(): ui_postprocessing.create_ui() with gr.Blocks(analytics_enabled=False) as pnginfo_interface: - with gr.Row().style(equal_height=False): + with gr.Row(equal_height=False): with gr.Column(variant='panel'): image = gr.Image(elem_id="pnginfo_image", label="Source", source="upload", interactive=True, type="pil") @@ -1018,10 +1018,10 @@ def create_ui(): modelmerger_ui = ui_checkpoint_merger.UiCheckpointMerger() with gr.Blocks(analytics_enabled=False) as train_interface: - with gr.Row().style(equal_height=False): + with gr.Row(equal_height=False): gr.HTML(value="

See wiki for detailed explanation.

") - with gr.Row(variant="compact").style(equal_height=False): + with gr.Row(variant="compact", equal_height=False): with gr.Tabs(elem_id="train_tabs"): with gr.Tab(label="Create embedding", id="create_embedding"): @@ -1181,7 +1181,7 @@ def create_ui(): with gr.Column(elem_id='ti_gallery_container'): ti_output = gr.Text(elem_id="ti_output", value="", show_label=False) - gr.Gallery(label='Output', show_label=False, elem_id='ti_gallery').style(columns=4) + gr.Gallery(label='Output', show_label=False, elem_id='ti_gallery', columns=4) gr.HTML(elem_id="ti_progress", value="") ti_outcome = gr.HTML(elem_id="ti_error", value="") diff --git a/modules/ui_checkpoint_merger.py b/modules/ui_checkpoint_merger.py index 4863d861..f9c5dd6b 100644 --- a/modules/ui_checkpoint_merger.py +++ b/modules/ui_checkpoint_merger.py @@ -29,7 +29,7 @@ def modelmerger(*args): class UiCheckpointMerger: def __init__(self): with gr.Blocks(analytics_enabled=False) as modelmerger_interface: - with gr.Row().style(equal_height=False): + with gr.Row(equal_height=False): with gr.Column(variant='compact'): self.interp_description = gr.HTML(value=update_interp_description("Weighted sum"), elem_id="modelmerger_interp_description") diff --git a/modules/ui_common.py b/modules/ui_common.py index ba75fa73..eefe0c0e 100644 --- a/modules/ui_common.py +++ b/modules/ui_common.py @@ -134,7 +134,7 @@ Requested path was: {f} with gr.Column(variant='panel', elem_id=f"{tabname}_results"): with gr.Group(elem_id=f"{tabname}_gallery_container"): - result_gallery = gr.Gallery(label='Output', show_label=False, elem_id=f"{tabname}_gallery").style(columns=4) + result_gallery = gr.Gallery(label='Output', show_label=False, elem_id=f"{tabname}_gallery", columns=4) generation_info = None with gr.Column(): diff --git a/modules/ui_components.py b/modules/ui_components.py index 64451df7..8f8a7088 100644 --- a/modules/ui_components.py +++ b/modules/ui_components.py @@ -35,7 +35,7 @@ class FormColumn(FormComponent, gr.Column): class FormGroup(FormComponent, gr.Group): - """Same as gr.Row but fits inside gradio forms""" + """Same as gr.Group but fits inside gradio forms""" def get_block_name(self): return "group" diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py index bd28bfcf..15a8b0bf 100644 --- a/modules/ui_extensions.py +++ b/modules/ui_extensions.py @@ -533,8 +533,8 @@ def create_ui(): apply = gr.Button(value=apply_label, variant="primary") check = gr.Button(value="Check for updates") extensions_disable_all = gr.Radio(label="Disable all extensions", choices=["none", "extra", "all"], value=shared.opts.disable_all_extensions, elem_id="extensions_disable_all") - extensions_disabled_list = gr.Text(elem_id="extensions_disabled_list", visible=False).style(container=False) - extensions_update_list = gr.Text(elem_id="extensions_update_list", visible=False).style(container=False) + extensions_disabled_list = gr.Text(elem_id="extensions_disabled_list", visible=False, container=False) + extensions_update_list = gr.Text(elem_id="extensions_update_list", visible=False, container=False) html = "" @@ -569,7 +569,7 @@ def create_ui(): with gr.Row(): refresh_available_extensions_button = gr.Button(value="Load from:", variant="primary") extensions_index_url = os.environ.get('WEBUI_EXTENSIONS_INDEX', "https://raw.githubusercontent.com/AUTOMATIC1111/stable-diffusion-webui-extensions/master/index.json") - available_extensions_index = gr.Text(value=extensions_index_url, label="Extension index URL").style(container=False) + available_extensions_index = gr.Text(value=extensions_index_url, label="Extension index URL", container=False) extension_to_install = gr.Text(elem_id="extension_to_install", visible=False) install_extension_button = gr.Button(elem_id="install_extension_button", visible=False) @@ -578,7 +578,7 @@ def create_ui(): sort_column = gr.Radio(value="newest first", label="Order", choices=["newest first", "oldest first", "a-z", "z-a", "internal order",'update time', 'create time', "stars"], type="index") with gr.Row(): - search_extensions_text = gr.Text(label="Search").style(container=False) + search_extensions_text = gr.Text(label="Search", container=False) install_result = gr.HTML() available_extensions_table = gr.HTML() diff --git a/modules/ui_postprocessing.py b/modules/ui_postprocessing.py index c7dc1154..802e1ce7 100644 --- a/modules/ui_postprocessing.py +++ b/modules/ui_postprocessing.py @@ -6,7 +6,7 @@ import modules.generation_parameters_copypaste as parameters_copypaste def create_ui(): tab_index = gr.State(value=0) - with gr.Row().style(equal_height=False, variant='compact'): + with gr.Row(equal_height=False, variant='compact'): with gr.Column(variant='compact'): with gr.Tabs(elem_id="mode_extras"): with gr.TabItem('Single Image', id="single_image", elem_id="extras_single_tab") as tab_single: diff --git a/requirements.txt b/requirements.txt index b3f8a7f4..afdc6ee2 100644 --- a/requirements.txt +++ b/requirements.txt @@ -7,7 +7,7 @@ blendmodes clean-fid einops gfpgan -gradio==3.32.0 +gradio==3.39.0 inflection jsonmerge kornia diff --git a/requirements_versions.txt b/requirements_versions.txt index d07ab456..82b8732d 100644 --- a/requirements_versions.txt +++ b/requirements_versions.txt @@ -7,7 +7,7 @@ clean-fid==0.1.35 einops==0.4.1 fastapi==0.94.0 gfpgan==1.3.8 -gradio==3.32.0 +gradio==3.39.0 httpcore==0.15 inflection==0.5.1 jsonmerge==1.8.0 diff --git a/style.css b/style.css index cf8470e4..86b4f61e 100644 --- a/style.css +++ b/style.css @@ -8,6 +8,7 @@ --checkbox-label-gap: 0.25em 0.1em; --section-header-text-size: 12pt; --block-background-fill: transparent; + } .block.padded:not(.gradio-accordion) { @@ -42,7 +43,8 @@ div.form{ .block.gradio-radio, .block.gradio-checkboxgroup, .block.gradio-number, -.block.gradio-colorpicker +.block.gradio-colorpicker, +div.gradio-group { border-width: 0 !important; box-shadow: none !important; @@ -133,6 +135,11 @@ a{ cursor: pointer; } +div.styler{ + border: none; + background: var(--background-fill-primary); +} + /* general styled components */ @@ -164,7 +171,7 @@ a{ .checkboxes-row > div{ flex: 0; white-space: nowrap; - min-width: auto; + min-width: auto !important; } button.custom-button{ @@ -388,6 +395,7 @@ div#extras_scale_to_tab div.form{ #quicksettings > div, #quicksettings > fieldset{ max-width: 24em; min-width: 24em; + width: 24em; padding: 0; border: none; box-shadow: none; -- cgit v1.2.3 From 75336dfc84cae280036bc52a6805eb10d9ae30ba Mon Sep 17 00:00:00 2001 From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com> Date: Fri, 4 Aug 2023 13:38:52 +0800 Subject: add TAESD for i2i and t2i --- modules/processing.py | 13 +++++------ modules/sd_samplers_common.py | 38 ++++++++++++++++++++++++++----- modules/sd_vae_approx.py | 2 +- modules/sd_vae_taesd.py | 52 ++++++++++++++++++++++++++++++++++++------- modules/shared.py | 2 ++ 5 files changed, 86 insertions(+), 21 deletions(-) (limited to 'modules/shared.py') diff --git a/modules/processing.py b/modules/processing.py index 8f34c8b4..099d86b7 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -573,9 +573,10 @@ def decode_latent_batch(model, batch, target_device=None, check_for_nans=False): def decode_first_stage(model, x): - x = model.decode_first_stage(x.to(devices.dtype_vae)) - - return x + from modules.sd_samplers_common import samples_to_images_tensor, approximation_indexes + x = x.to(devices.dtype_vae) + approx_index = approximation_indexes.get(opts.sd_vae_decode_method, 0) + return samples_to_images_tensor(x, approx_index, model) def get_fixed_seed(seed): @@ -1344,10 +1345,8 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing): raise RuntimeError(f"bad number of images passed: {len(imgs)}; expecting {self.batch_size} or less") image = torch.from_numpy(batch_images) - image = 2. * image - 1. - image = image.to(shared.device, dtype=devices.dtype_vae) - - self.init_latent = self.sd_model.get_first_stage_encoding(self.sd_model.encode_first_stage(image)) + from modules.sd_samplers_common import images_tensor_to_samples, approximation_indexes + self.init_latent = images_tensor_to_samples(image, approximation_indexes.get(opts.sd_vae_encode_method), self.sd_model) devices.torch_gc() if self.resize_mode == 3: diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py index 5deda761..5a45e8eb 100644 --- a/modules/sd_samplers_common.py +++ b/modules/sd_samplers_common.py @@ -23,19 +23,29 @@ def setup_img2img_steps(p, steps=None): approximation_indexes = {"Full": 0, "Approx NN": 1, "Approx cheap": 2, "TAESD": 3} -def single_sample_to_image(sample, approximation=None): +def samples_to_images_tensor(sample, approximation=None, model=None): + '''latents -> images [-1, 1]''' if approximation is None: approximation = approximation_indexes.get(opts.show_progress_type, 0) if approximation == 2: - x_sample = sd_vae_approx.cheap_approximation(sample) * 0.5 + 0.5 + x_sample = sd_vae_approx.cheap_approximation(sample) elif approximation == 1: - x_sample = sd_vae_approx.model()(sample.to(devices.device, devices.dtype).unsqueeze(0))[0].detach() * 0.5 + 0.5 + x_sample = sd_vae_approx.model()(sample.to(devices.device, devices.dtype)).detach() elif approximation == 3: x_sample = sample * 1.5 - x_sample = sd_vae_taesd.model()(x_sample.to(devices.device, devices.dtype).unsqueeze(0))[0].detach() + x_sample = sd_vae_taesd.decoder_model()(x_sample.to(devices.device, devices.dtype)).detach() + x_sample = x_sample * 2 - 1 else: - x_sample = processing.decode_first_stage(shared.sd_model, sample.unsqueeze(0))[0] * 0.5 + 0.5 + if model is None: + model = shared.sd_model + x_sample = model.decode_first_stage(sample) + + return x_sample + + +def single_sample_to_image(sample, approximation=None): + x_sample = samples_to_images_tensor(sample.unsqueeze(0), approximation)[0] * 0.5 + 0.5 x_sample = torch.clamp(x_sample, min=0.0, max=1.0) x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2) @@ -52,6 +62,24 @@ def samples_to_image_grid(samples, approximation=None): return images.image_grid([single_sample_to_image(sample, approximation) for sample in samples]) +def images_tensor_to_samples(image, approximation=None, model=None): + '''image[0, 1] -> latent''' + if approximation is None: + approximation = approximation_indexes.get(opts.sd_vae_encode_method, 0) + + if approximation == 3: + image = image.to(devices.device, devices.dtype) + x_latent = sd_vae_taesd.encoder_model()(image) / 1.5 + else: + if model is None: + model = shared.sd_model + image = image.to(shared.device, dtype=devices.dtype_vae) + image = image * 2 - 1 + x_latent = model.get_first_stage_encoding(model.encode_first_stage(image)) + + return x_latent + + def store_latent(decoded): state.current_latent = decoded diff --git a/modules/sd_vae_approx.py b/modules/sd_vae_approx.py index 86bd658a..3965e223 100644 --- a/modules/sd_vae_approx.py +++ b/modules/sd_vae_approx.py @@ -81,6 +81,6 @@ def cheap_approximation(sample): coefs = torch.tensor(coeffs).to(sample.device) - x_sample = torch.einsum("lxy,lr -> rxy", sample, coefs) + x_sample = torch.einsum("...lxy,lr -> ...rxy", sample, coefs) return x_sample diff --git a/modules/sd_vae_taesd.py b/modules/sd_vae_taesd.py index 5bf7c76e..808eb362 100644 --- a/modules/sd_vae_taesd.py +++ b/modules/sd_vae_taesd.py @@ -44,7 +44,17 @@ def decoder(): ) -class TAESD(nn.Module): +def encoder(): + return nn.Sequential( + conv(3, 64), Block(64, 64), + conv(64, 64, stride=2, bias=False), Block(64, 64), Block(64, 64), Block(64, 64), + conv(64, 64, stride=2, bias=False), Block(64, 64), Block(64, 64), Block(64, 64), + conv(64, 64, stride=2, bias=False), Block(64, 64), Block(64, 64), Block(64, 64), + conv(64, 4), + ) + + +class TAESDDecoder(nn.Module): latent_magnitude = 3 latent_shift = 0.5 @@ -55,21 +65,28 @@ class TAESD(nn.Module): self.decoder.load_state_dict( torch.load(decoder_path, map_location='cpu' if devices.device.type != 'cuda' else None)) - @staticmethod - def unscale_latents(x): - """[0, 1] -> raw latents""" - return x.sub(TAESD.latent_shift).mul(2 * TAESD.latent_magnitude) + +class TAESDEncoder(nn.Module): + latent_magnitude = 3 + latent_shift = 0.5 + + def __init__(self, encoder_path="taesd_encoder.pth"): + """Initialize pretrained TAESD on the given device from the given checkpoints.""" + super().__init__() + self.encoder = encoder() + self.encoder.load_state_dict( + torch.load(encoder_path, map_location='cpu' if devices.device.type != 'cuda' else None)) def download_model(model_path, model_url): if not os.path.exists(model_path): os.makedirs(os.path.dirname(model_path), exist_ok=True) - print(f'Downloading TAESD decoder to: {model_path}') + print(f'Downloading TAESD model to: {model_path}') torch.hub.download_url_to_file(model_url, model_path) -def model(): +def decoder_model(): model_name = "taesdxl_decoder.pth" if getattr(shared.sd_model, 'is_sdxl', False) else "taesd_decoder.pth" loaded_model = sd_vae_taesd_models.get(model_name) @@ -78,7 +95,7 @@ def model(): download_model(model_path, 'https://github.com/madebyollin/taesd/raw/main/' + model_name) if os.path.exists(model_path): - loaded_model = TAESD(model_path) + loaded_model = TAESDDecoder(model_path) loaded_model.eval() loaded_model.to(devices.device, devices.dtype) sd_vae_taesd_models[model_name] = loaded_model @@ -86,3 +103,22 @@ def model(): raise FileNotFoundError('TAESD model not found') return loaded_model.decoder + + +def encoder_model(): + model_name = "taesdxl_encoder.pth" if getattr(shared.sd_model, 'is_sdxl', False) else "taesd_encoder.pth" + loaded_model = sd_vae_taesd_models.get(model_name) + + if loaded_model is None: + model_path = os.path.join(paths_internal.models_path, "VAE-taesd", model_name) + download_model(model_path, 'https://github.com/madebyollin/taesd/raw/main/' + model_name) + + if os.path.exists(model_path): + loaded_model = TAESDEncoder(model_path) + loaded_model.eval() + loaded_model.to(devices.device, devices.dtype) + sd_vae_taesd_models[model_name] = loaded_model + else: + raise FileNotFoundError('TAESD model not found') + + return loaded_model.encoder diff --git a/modules/shared.py b/modules/shared.py index cec030f7..61ba9347 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -430,6 +430,8 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "upcast_attn": OptionInfo(False, "Upcast cross attention layer to float32"), "auto_vae_precision": OptionInfo(True, "Automaticlly revert VAE to 32-bit floats").info("triggers when a tensor with NaNs is produced in VAE; disabling the option in this case will result in a black square image"), "randn_source": OptionInfo("GPU", "Random number generator source.", gr.Radio, {"choices": ["GPU", "CPU", "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"), + "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 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(('sdxl', "Stable Diffusion XL"), { -- cgit v1.2.3 From 1d60a609a9d7a7f79517dc0c87d4b834b89db252 Mon Sep 17 00:00:00 2001 From: w-e-w <40751091+w-e-w@users.noreply.github.com> Date: Sat, 5 Aug 2023 09:25:21 +0900 Subject: configurable masks color and default brush color --- modules/shared.py | 3 +++ modules/ui.py | 6 +++--- 2 files changed, 6 insertions(+), 3 deletions(-) (limited to 'modules/shared.py') diff --git a/modules/shared.py b/modules/shared.py index cec030f7..1eb00b8f 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -492,6 +492,9 @@ options_templates.update(options_section(('ui', "User interface"), { "localization": OptionInfo("None", "Localization", gr.Dropdown, lambda: {"choices": ["None"] + list(localization.localizations.keys())}, refresh=lambda: localization.list_localizations(cmd_opts.localizations_dir)).needs_restart(), "gradio_theme": OptionInfo("Default", "Gradio theme", ui_components.DropdownEditable, lambda: {"choices": ["Default"] + gradio_hf_hub_themes}).needs_restart(), "img2img_editor_height": OptionInfo(720, "img2img: height of image editor", gr.Slider, {"minimum": 80, "maximum": 1600, "step": 1}).info("in pixels").needs_restart(), + "img2img_sketch_default_brush_color": OptionInfo("#000000", "sketch brush color", ui_components.FormColorPicker, {}).info("default brush color of img2img sketch) (requires reload"), + "img2img_inpaint_mask_brush_color": OptionInfo("#000000", "inpaint mask brush color", ui_components.FormColorPicker, {}).info("brush color of inpaint mask) (requires reload"), + "img2img_inpaint_sketch_default_brush_color": OptionInfo("#000000", "inpaint sketch brush color", ui_components.FormColorPicker, {}).info("default brush color of img2img inpaint sketch) (requires reload"), "return_grid": OptionInfo(True, "Show grid in results for web"), "return_mask": OptionInfo(False, "For inpainting, include the greyscale mask in results for web"), "return_mask_composite": OptionInfo(False, "For inpainting, include masked composite in results for web"), diff --git a/modules/ui.py b/modules/ui.py index 6cf3dff8..843a75ef 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -663,15 +663,15 @@ def create_ui(): add_copy_image_controls('img2img', init_img) with gr.TabItem('Sketch', id='img2img_sketch', elem_id="img2img_img2img_sketch_tab") as tab_sketch: - sketch = gr.Image(label="Image for img2img", elem_id="img2img_sketch", show_label=False, source="upload", interactive=True, type="pil", tool="color-sketch", image_mode="RGBA", height=opts.img2img_editor_height) + sketch = gr.Image(label="Image for img2img", elem_id="img2img_sketch", show_label=False, source="upload", interactive=True, type="pil", tool="color-sketch", image_mode="RGBA", height=opts.img2img_editor_height, brush_color=opts.img2img_sketch_default_brush_color) add_copy_image_controls('sketch', sketch) with gr.TabItem('Inpaint', id='inpaint', elem_id="img2img_inpaint_tab") as tab_inpaint: - init_img_with_mask = gr.Image(label="Image for inpainting with mask", show_label=False, elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool="sketch", image_mode="RGBA", height=opts.img2img_editor_height, brush_color='#ffffff') + init_img_with_mask = gr.Image(label="Image for inpainting with mask", show_label=False, elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool="sketch", image_mode="RGBA", height=opts.img2img_editor_height, brush_color=opts.img2img_inpaint_mask_brush_color) add_copy_image_controls('inpaint', init_img_with_mask) with gr.TabItem('Inpaint sketch', id='inpaint_sketch', elem_id="img2img_inpaint_sketch_tab") as tab_inpaint_color: - inpaint_color_sketch = gr.Image(label="Color sketch inpainting", show_label=False, elem_id="inpaint_sketch", source="upload", interactive=True, type="pil", tool="color-sketch", image_mode="RGBA", height=opts.img2img_editor_height, brush_color='#ffffff') + inpaint_color_sketch = gr.Image(label="Color sketch inpainting", show_label=False, elem_id="inpaint_sketch", source="upload", interactive=True, type="pil", tool="color-sketch", image_mode="RGBA", height=opts.img2img_editor_height, brush_color=opts.img2img_inpaint_sketch_default_brush_color) inpaint_color_sketch_orig = gr.State(None) add_copy_image_controls('inpaint_sketch', inpaint_color_sketch) -- cgit v1.2.3 From e7140a36c07c7590334eaaea07a3c79d7e044db9 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Sat, 5 Aug 2023 07:36:25 +0300 Subject: change default color to white --- modules/shared.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) (limited to 'modules/shared.py') diff --git a/modules/shared.py b/modules/shared.py index 1eb00b8f..fca6ad63 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -492,9 +492,9 @@ options_templates.update(options_section(('ui', "User interface"), { "localization": OptionInfo("None", "Localization", gr.Dropdown, lambda: {"choices": ["None"] + list(localization.localizations.keys())}, refresh=lambda: localization.list_localizations(cmd_opts.localizations_dir)).needs_restart(), "gradio_theme": OptionInfo("Default", "Gradio theme", ui_components.DropdownEditable, lambda: {"choices": ["Default"] + gradio_hf_hub_themes}).needs_restart(), "img2img_editor_height": OptionInfo(720, "img2img: height of image editor", gr.Slider, {"minimum": 80, "maximum": 1600, "step": 1}).info("in pixels").needs_restart(), - "img2img_sketch_default_brush_color": OptionInfo("#000000", "sketch brush color", ui_components.FormColorPicker, {}).info("default brush color of img2img sketch) (requires reload"), - "img2img_inpaint_mask_brush_color": OptionInfo("#000000", "inpaint mask brush color", ui_components.FormColorPicker, {}).info("brush color of inpaint mask) (requires reload"), - "img2img_inpaint_sketch_default_brush_color": OptionInfo("#000000", "inpaint sketch brush color", ui_components.FormColorPicker, {}).info("default brush color of img2img inpaint sketch) (requires reload"), + "img2img_sketch_default_brush_color": OptionInfo("#ffffff", "sketch brush color", ui_components.FormColorPicker, {}).info("default brush color of img2img sketch").needs_restart(), + "img2img_inpaint_mask_brush_color": OptionInfo("#ffffff", "inpaint mask brush color", ui_components.FormColorPicker, {}).info("brush color of inpaint mask").needs_restart(), + "img2img_inpaint_sketch_default_brush_color": OptionInfo("#ffffff", "inpaint sketch brush color", ui_components.FormColorPicker, {}).info("default brush color of img2img inpaint sketch").needs_restart(), "return_grid": OptionInfo(True, "Show grid in results for web"), "return_mask": OptionInfo(False, "For inpainting, include the greyscale mask in results for web"), "return_mask_composite": OptionInfo(False, "For inpainting, include masked composite in results for web"), -- cgit v1.2.3 From d8371d0b3c90252bfb4de619a2e6f80296845554 Mon Sep 17 00:00:00 2001 From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com> Date: Sat, 5 Aug 2023 12:37:46 +0800 Subject: update info --- modules/shared.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/shared.py') diff --git a/modules/shared.py b/modules/shared.py index 61ba9347..3491ad79 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -430,7 +430,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "upcast_attn": OptionInfo(False, "Upcast cross attention layer to float32"), "auto_vae_precision": OptionInfo(True, "Automaticlly revert VAE to 32-bit floats").info("triggers when a tensor with NaNs is produced in VAE; disabling the option in this case will result in a black square image"), "randn_source": OptionInfo("GPU", "Random number generator source.", gr.Radio, {"choices": ["GPU", "CPU", "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"), - "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 or inpaint mask)"), + "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-dix 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"), })) -- cgit v1.2.3 From d2b842ce079949f2eafa8a4a6e2374f0e5acac34 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Sat, 5 Aug 2023 07:46:22 +0300 Subject: move img2img settings to their own section --- modules/shared.py | 32 +++++++++++++++++++------------- 1 file changed, 19 insertions(+), 13 deletions(-) (limited to 'modules/shared.py') diff --git a/modules/shared.py b/modules/shared.py index fca6ad63..55199cb9 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -417,12 +417,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "sd_vae": OptionInfo("Automatic", "SD VAE", gr.Dropdown, lambda: {"choices": shared_items.sd_vae_items()}, refresh=shared_items.refresh_vae_list).info("choose VAE model: Automatic = use one with same filename as checkpoint; None = use VAE from checkpoint"), "sd_vae_as_default": OptionInfo(True, "Ignore selected VAE for stable diffusion checkpoints that have their own .vae.pt next to them"), "sd_unet": OptionInfo("Automatic", "SD Unet", gr.Dropdown, lambda: {"choices": shared_items.sd_unet_items()}, refresh=shared_items.refresh_unet_list).info("choose Unet model: Automatic = use one with same filename as checkpoint; None = use Unet from checkpoint"), - "inpainting_mask_weight": OptionInfo(1.0, "Inpainting conditioning mask strength", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), - "initial_noise_multiplier": OptionInfo(1.0, "Noise multiplier for img2img", gr.Slider, {"minimum": 0.5, "maximum": 1.5, "step": 0.01}), - "img2img_color_correction": OptionInfo(False, "Apply color correction to img2img results to match original colors."), - "img2img_fix_steps": OptionInfo(False, "With img2img, do exactly the amount of steps the slider specifies.").info("normally you'd do less with less denoising"), - "img2img_background_color": OptionInfo("#ffffff", "With img2img, fill image's transparent parts with this color.", ui_components.FormColorPicker, {}), - "enable_quantization": OptionInfo(False, "Enable quantization in K samplers for sharper and cleaner results. This may change existing seeds. Requires restart to apply."), + "enable_quantization": OptionInfo(False, "Enable quantization in K samplers for sharper and cleaner results. This may change existing seeds").needs_restart(), "enable_emphasis": OptionInfo(True, "Enable emphasis").info("use (text) to make model pay more attention to text and [text] to make it pay less attention"), "enable_batch_seeds": OptionInfo(True, "Make K-diffusion samplers produce same images in a batch as when making a single image"), "comma_padding_backtrack": OptionInfo(20, "Prompt word wrap length limit", gr.Slider, {"minimum": 0, "maximum": 74, "step": 1}).info("in tokens - for texts shorter than specified, if they don't fit into 75 token limit, move them to the next 75 token chunk"), @@ -439,6 +434,22 @@ options_templates.update(options_section(('sdxl', "Stable Diffusion XL"), { "sdxl_refiner_high_aesthetic_score": OptionInfo(6.0, "SDXL high aesthetic score", gr.Number).info("used for refiner model prompt"), })) + +options_templates.update(options_section(('img2img', "img2img"), { + "inpainting_mask_weight": OptionInfo(1.0, "Inpainting conditioning mask strength", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), + "initial_noise_multiplier": OptionInfo(1.0, "Noise multiplier for img2img", gr.Slider, {"minimum": 0.5, "maximum": 1.5, "step": 0.01}), + "img2img_color_correction": OptionInfo(False, "Apply color correction to img2img results to match original colors."), + "img2img_fix_steps": OptionInfo(False, "With img2img, do exactly the amount of steps the slider specifies.").info("normally you'd do less with less denoising"), + "img2img_background_color": OptionInfo("#ffffff", "With img2img, fill transparent parts of the input image with this color.", ui_components.FormColorPicker, {}), + "img2img_editor_height": OptionInfo(720, "Height of the image editor", gr.Slider, {"minimum": 80, "maximum": 1600, "step": 1}).info("in pixels").needs_restart(), + "img2img_sketch_default_brush_color": OptionInfo("#ffffff", "Sketch initial brush color", ui_components.FormColorPicker, {}).info("default brush color of img2img sketch").needs_restart(), + "img2img_inpaint_mask_brush_color": OptionInfo("#ffffff", "Inpaint mask brush color", ui_components.FormColorPicker, {}).info("brush color of inpaint mask").needs_restart(), + "img2img_inpaint_sketch_default_brush_color": OptionInfo("#ffffff", "Inpaint sketch initial brush color", ui_components.FormColorPicker, {}).info("default brush color of img2img inpaint sketch").needs_restart(), + "return_mask": OptionInfo(False, "For inpainting, include the greyscale mask in results for web"), + "return_mask_composite": OptionInfo(False, "For inpainting, include masked composite in results for web"), +})) + + options_templates.update(options_section(('optimizations', "Optimizations"), { "cross_attention_optimization": OptionInfo("Automatic", "Cross attention optimization", gr.Dropdown, lambda: {"choices": shared_items.cross_attention_optimizations()}), "s_min_uncond": OptionInfo(0.0, "Negative Guidance minimum sigma", gr.Slider, {"minimum": 0.0, "maximum": 15.0, "step": 0.01}).link("PR", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/9177").info("skip negative prompt for some steps when the image is almost ready; 0=disable, higher=faster"), @@ -458,7 +469,7 @@ options_templates.update(options_section(('compatibility', "Compatibility"), { "hires_fix_use_firstpass_conds": OptionInfo(False, "For hires fix, calculate conds of second pass using extra networks of first pass."), })) -options_templates.update(options_section(('interrogate', "Interrogate Options"), { +options_templates.update(options_section(('interrogate', "Interrogate"), { "interrogate_keep_models_in_memory": OptionInfo(False, "Keep models in VRAM"), "interrogate_return_ranks": OptionInfo(False, "Include ranks of model tags matches in results.").info("booru only"), "interrogate_clip_num_beams": OptionInfo(1, "BLIP: num_beams", gr.Slider, {"minimum": 1, "maximum": 16, "step": 1}), @@ -491,13 +502,7 @@ options_templates.update(options_section(('extra_networks', "Extra Networks"), { options_templates.update(options_section(('ui', "User interface"), { "localization": OptionInfo("None", "Localization", gr.Dropdown, lambda: {"choices": ["None"] + list(localization.localizations.keys())}, refresh=lambda: localization.list_localizations(cmd_opts.localizations_dir)).needs_restart(), "gradio_theme": OptionInfo("Default", "Gradio theme", ui_components.DropdownEditable, lambda: {"choices": ["Default"] + gradio_hf_hub_themes}).needs_restart(), - "img2img_editor_height": OptionInfo(720, "img2img: height of image editor", gr.Slider, {"minimum": 80, "maximum": 1600, "step": 1}).info("in pixels").needs_restart(), - "img2img_sketch_default_brush_color": OptionInfo("#ffffff", "sketch brush color", ui_components.FormColorPicker, {}).info("default brush color of img2img sketch").needs_restart(), - "img2img_inpaint_mask_brush_color": OptionInfo("#ffffff", "inpaint mask brush color", ui_components.FormColorPicker, {}).info("brush color of inpaint mask").needs_restart(), - "img2img_inpaint_sketch_default_brush_color": OptionInfo("#ffffff", "inpaint sketch brush color", ui_components.FormColorPicker, {}).info("default brush color of img2img inpaint sketch").needs_restart(), "return_grid": OptionInfo(True, "Show grid in results for web"), - "return_mask": OptionInfo(False, "For inpainting, include the greyscale mask in results for web"), - "return_mask_composite": OptionInfo(False, "For inpainting, include masked composite in results for web"), "do_not_show_images": OptionInfo(False, "Do not show any images in results for web"), "send_seed": OptionInfo(True, "Send seed when sending prompt or image to other interface"), "send_size": OptionInfo(True, "Send size when sending prompt or image to another interface"), @@ -521,6 +526,7 @@ options_templates.update(options_section(('ui', "User interface"), { "disable_token_counters": OptionInfo(False, "Disable prompt token counters").needs_restart(), })) + options_templates.update(options_section(('infotext', "Infotext"), { "add_model_hash_to_info": OptionInfo(True, "Add model hash to generation information"), "add_model_name_to_info": OptionInfo(True, "Add model name to generation information"), -- cgit v1.2.3 From a6b245e46f28efe013637e5e9b0600b88df79dc9 Mon Sep 17 00:00:00 2001 From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com> Date: Sat, 5 Aug 2023 12:49:35 +0800 Subject: dix --- modules/shared.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/shared.py') diff --git a/modules/shared.py b/modules/shared.py index 3491ad79..df454d4a 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -430,7 +430,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "upcast_attn": OptionInfo(False, "Upcast cross attention layer to float32"), "auto_vae_precision": OptionInfo(True, "Automaticlly revert VAE to 32-bit floats").info("triggers when a tensor with NaNs is produced in VAE; disabling the option in this case will result in a black square image"), "randn_source": OptionInfo("GPU", "Random number generator source.", gr.Radio, {"choices": ["GPU", "CPU", "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"), - "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-dix or inpaint mask)"), + "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"), })) -- cgit v1.2.3 From 7a64601428378c30e92efc00af7729db1b22dfb0 Mon Sep 17 00:00:00 2001 From: w-e-w <40751091+w-e-w@users.noreply.github.com> Date: Sat, 5 Aug 2023 14:21:28 +0900 Subject: need Reload UI not Restart --- .../scripts/extra_options_section.py | 4 +- modules/shared.py | 44 +++++++++++----------- 2 files changed, 25 insertions(+), 23 deletions(-) (limited to 'modules/shared.py') diff --git a/extensions-builtin/extra-options-section/scripts/extra_options_section.py b/extensions-builtin/extra-options-section/scripts/extra_options_section.py index a05e10d8..7bb0a1bb 100644 --- a/extensions-builtin/extra-options-section/scripts/extra_options_section.py +++ b/extensions-builtin/extra-options-section/scripts/extra_options_section.py @@ -43,6 +43,6 @@ class ExtraOptionsSection(scripts.Script): shared.options_templates.update(shared.options_section(('ui', "User interface"), { - "extra_options": shared.OptionInfo([], "Options in main UI", ui_components.DropdownMulti, lambda: {"choices": list(shared.opts.data_labels.keys())}).js("info", "settingsHintsShowQuicksettings").info("setting entries that also appear in txt2img/img2img interfaces").needs_restart(), - "extra_options_accordion": shared.OptionInfo(False, "Place options in main UI into an accordion") + "extra_options": shared.OptionInfo([], "Options in main UI", ui_components.DropdownMulti, lambda: {"choices": list(shared.opts.data_labels.keys())}).js("info", "settingsHintsShowQuicksettings").info("setting entries that also appear in txt2img/img2img interfaces").needs_reload_ui(), + "extra_options_accordion": shared.OptionInfo(False, "Place options in main UI into an accordion").needs_restart() })) diff --git a/modules/shared.py b/modules/shared.py index 8245250a..fb317972 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -286,7 +286,9 @@ class OptionInfo: self.comment_after += " (requires restart)" return self - + def needs_reload_ui(self): + self.comment_after += " (requires Reload UI)" + return self def options_section(section_identifier, options_dict): @@ -392,8 +394,8 @@ options_templates.update(options_section(('face-restoration', "Face restoration" })) options_templates.update(options_section(('system', "System"), { - "show_warnings": OptionInfo(False, "Show warnings in console.").needs_restart(), - "show_gradio_deprecation_warnings": OptionInfo(True, "Show gradio deprecation warnings in console.").needs_restart(), + "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."), @@ -427,7 +429,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "sd_vae": OptionInfo("Automatic", "SD VAE", gr.Dropdown, lambda: {"choices": shared_items.sd_vae_items()}, refresh=shared_items.refresh_vae_list).info("choose VAE model: Automatic = use one with same filename as checkpoint; None = use VAE from checkpoint"), "sd_vae_as_default": OptionInfo(True, "Ignore selected VAE for stable diffusion checkpoints that have their own .vae.pt next to them"), "sd_unet": OptionInfo("Automatic", "SD Unet", gr.Dropdown, lambda: {"choices": shared_items.sd_unet_items()}, refresh=shared_items.refresh_unet_list).info("choose Unet model: Automatic = use one with same filename as checkpoint; None = use Unet from checkpoint"), - "enable_quantization": OptionInfo(False, "Enable quantization in K samplers for sharper and cleaner results. This may change existing seeds").needs_restart(), + "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"), @@ -451,10 +453,10 @@ options_templates.update(options_section(('img2img', "img2img"), { "img2img_color_correction": OptionInfo(False, "Apply color correction to img2img results to match original colors."), "img2img_fix_steps": OptionInfo(False, "With img2img, do exactly the amount of steps the slider specifies.").info("normally you'd do less with less denoising"), "img2img_background_color": OptionInfo("#ffffff", "With img2img, fill transparent parts of the input image with this color.", ui_components.FormColorPicker, {}), - "img2img_editor_height": OptionInfo(720, "Height of the image editor", gr.Slider, {"minimum": 80, "maximum": 1600, "step": 1}).info("in pixels").needs_restart(), - "img2img_sketch_default_brush_color": OptionInfo("#ffffff", "Sketch initial brush color", ui_components.FormColorPicker, {}).info("default brush color of img2img sketch").needs_restart(), - "img2img_inpaint_mask_brush_color": OptionInfo("#ffffff", "Inpaint mask brush color", ui_components.FormColorPicker, {}).info("brush color of inpaint mask").needs_restart(), - "img2img_inpaint_sketch_default_brush_color": OptionInfo("#ffffff", "Inpaint sketch initial brush color", ui_components.FormColorPicker, {}).info("default brush color of img2img inpaint sketch").needs_restart(), + "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"), })) @@ -503,15 +505,15 @@ options_templates.update(options_section(('extra_networks', "Extra Networks"), { "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_restart(), + "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_restart(), - "gradio_theme": OptionInfo("Default", "Gradio theme", ui_components.DropdownEditable, lambda: {"choices": ["Default"] + gradio_hf_hub_themes}).needs_restart(), + "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}).needs_reload_ui(), "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"), @@ -521,19 +523,19 @@ options_templates.update(options_section(('ui', "User interface"), { "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_restart(), - "dimensions_and_batch_together": OptionInfo(True, "Show Width/Height and Batch sliders in same row").needs_restart(), + "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_restart(), - "ui_tab_order": OptionInfo([], "UI tab order", ui_components.DropdownMulti, lambda: {"choices": list(tab_names)}).needs_restart(), - "hidden_tabs": OptionInfo([], "Hidden UI tabs", ui_components.DropdownMulti, lambda: {"choices": list(tab_names)}).needs_restart(), - "ui_reorder_list": OptionInfo([], "txt2img/img2img UI item order", ui_components.DropdownMulti, lambda: {"choices": list(shared_items.ui_reorder_categories())}).info("selected items appear first").needs_restart(), - "hires_fix_show_sampler": OptionInfo(False, "Hires fix: show hires checkpoint and sampler selection").needs_restart(), - "hires_fix_show_prompts": OptionInfo(False, "Hires fix: show hires prompt and negative prompt").needs_restart(), - "disable_token_counters": OptionInfo(False, "Disable prompt token counters").needs_restart(), + "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(), })) @@ -564,7 +566,7 @@ 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_restart(), + "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']}), -- cgit v1.2.3 From 36ca80d0046f85529682dc966a2bf822b00d8f2b Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Sat, 5 Aug 2023 10:43:06 +0300 Subject: put VAE into a separate settings page --- modules/shared.py | 15 ++++++++------- 1 file changed, 8 insertions(+), 7 deletions(-) (limited to 'modules/shared.py') diff --git a/modules/shared.py b/modules/shared.py index 367f815e..c6adda73 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -425,9 +425,6 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "sd_checkpoints_limit": OptionInfo(1, "Maximum number of checkpoints loaded at the same time", gr.Slider, {"minimum": 1, "maximum": 10, "step": 1}), "sd_checkpoints_keep_in_cpu": OptionInfo(True, "Only keep one model on device").info("will keep models other than the currently used one in RAM rather than VRAM"), "sd_checkpoint_cache": OptionInfo(0, "Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}).info("obsolete; set to 0 and use the two settings above instead"), - "sd_vae_checkpoint_cache": OptionInfo(0, "VAE Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}), - "sd_vae": OptionInfo("Automatic", "SD VAE", gr.Dropdown, lambda: {"choices": shared_items.sd_vae_items()}, refresh=shared_items.refresh_vae_list).info("choose VAE model: Automatic = use one with same filename as checkpoint; None = use VAE from checkpoint"), - "sd_vae_as_default": OptionInfo(True, "Ignore selected VAE for stable diffusion checkpoints that have their own .vae.pt next to them"), "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"), @@ -435,10 +432,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "comma_padding_backtrack": OptionInfo(20, "Prompt word wrap length limit", gr.Slider, {"minimum": 0, "maximum": 74, "step": 1}).info("in tokens - for texts shorter than specified, if they don't fit into 75 token limit, move them to the next 75 token chunk"), "CLIP_stop_at_last_layers": OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}).link("wiki", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#clip-skip").info("ignore last layers of CLIP network; 1 ignores none, 2 ignores one layer"), "upcast_attn": OptionInfo(False, "Upcast cross attention layer to float32"), - "auto_vae_precision": OptionInfo(True, "Automaticlly revert VAE to 32-bit floats").info("triggers when a tensor with NaNs is produced in VAE; disabling the option in this case will result in a black square image"), "randn_source": OptionInfo("GPU", "Random number generator source.", gr.Radio, {"choices": ["GPU", "CPU", "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"), - "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(('sdxl', "Stable Diffusion XL"), { @@ -448,6 +442,14 @@ options_templates.update(options_section(('sdxl', "Stable Diffusion XL"), { "sdxl_refiner_high_aesthetic_score": OptionInfo(6.0, "SDXL high aesthetic score", gr.Number).info("used for refiner model prompt"), })) +options_templates.update(options_section(('vae', "VAE"), { + "sd_vae_checkpoint_cache": OptionInfo(0, "VAE Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}), + "sd_vae": OptionInfo("Automatic", "SD VAE", gr.Dropdown, lambda: {"choices": shared_items.sd_vae_items()}, refresh=shared_items.refresh_vae_list).info("choose VAE model: Automatic = use one with same filename as checkpoint; None = use VAE from checkpoint"), + "sd_vae_as_default": OptionInfo(True, "Ignore selected VAE for stable diffusion checkpoints that have their own .vae.pt next to them"), + "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"), + "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}), @@ -463,7 +465,6 @@ options_templates.update(options_section(('img2img', "img2img"), { "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"), -- cgit v1.2.3 From 60183eebc37a69545e41cb6b00189609b85129b0 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Sat, 5 Aug 2023 11:18:13 +0300 Subject: add description to VAE setting page --- modules/shared.py | 20 ++++++++++++++++++++ style.css | 7 +++++++ 2 files changed, 27 insertions(+) (limited to 'modules/shared.py') diff --git a/modules/shared.py b/modules/shared.py index c6adda73..92adc563 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -259,6 +259,7 @@ class OptionInfo: 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""" @@ -291,6 +292,13 @@ class OptionInfo: 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 @@ -443,6 +451,12 @@ options_templates.update(options_section(('sdxl', "Stable Diffusion XL"), { })) 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_as_default": OptionInfo(True, "Ignore selected VAE for stable diffusion checkpoints that have their own .vae.pt next to them"), @@ -619,6 +633,9 @@ class Options: 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") @@ -648,6 +665,9 @@ class Options: if oldval == value: return False + if self.data_labels[key].do_not_save: + return False + try: setattr(self, key, value) except RuntimeError: diff --git a/style.css b/style.css index dc4d37b9..8c1f273c 100644 --- a/style.css +++ b/style.css @@ -494,6 +494,13 @@ table.popup-table .link{ font-size: 18pt; } +#settings .settings-info{ + max-width: 48em; + border: 1px dotted #777; + margin: 0; + padding: 1em; +} + /* live preview */ .progressDiv{ -- cgit v1.2.3 From 1d7dcdb6c38c7bca945b3fa8a5d4a1f93446f22a Mon Sep 17 00:00:00 2001 From: w-e-w <40751091+w-e-w@users.noreply.github.com> Date: Sat, 5 Aug 2023 19:07:39 +0900 Subject: Option to not save incomplete images --- modules/processing.py | 19 +++++++++++-------- modules/shared.py | 1 + 2 files changed, 12 insertions(+), 8 deletions(-) (limited to 'modules/shared.py') diff --git a/modules/processing.py b/modules/processing.py index 43cb763f..bf4f938b 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -103,6 +103,10 @@ def txt2img_image_conditioning(sd_model, x, width, height): return x.new_zeros(x.shape[0], 5, 1, 1, dtype=x.dtype, device=x.device) +def save_images_if_interrupted(): + return not (opts.dont_save_interrupted_images and (state.interrupted or state.skipped)) + + class StableDiffusionProcessing: """ The first set of paramaters: sd_models -> do_not_reload_embeddings represent the minimum required to create a StableDiffusionProcessing @@ -821,6 +825,8 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: def infotext(index=0, use_main_prompt=False): return create_infotext(p, p.prompts, p.seeds, p.subseeds, use_main_prompt=use_main_prompt, index=index, all_negative_prompts=p.negative_prompts) + save_images_if_interrupt = save_images_if_interrupted() + for i, x_sample in enumerate(x_samples_ddim): p.batch_index = i @@ -828,7 +834,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: x_sample = x_sample.astype(np.uint8) if p.restore_faces: - if opts.save and not p.do_not_save_samples and opts.save_images_before_face_restoration: + if opts.save and not p.do_not_save_samples and opts.save_images_before_face_restoration and save_images_if_interrupt: images.save_image(Image.fromarray(x_sample), p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(i), p=p, suffix="-before-face-restoration") devices.torch_gc() @@ -842,16 +848,15 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: pp = scripts.PostprocessImageArgs(image) p.scripts.postprocess_image(p, pp) image = pp.image - if p.color_corrections is not None and i < len(p.color_corrections): - if opts.save and not p.do_not_save_samples and opts.save_images_before_color_correction: + if opts.save and not p.do_not_save_samples and opts.save_images_before_color_correction and save_images_if_interrupt: image_without_cc = apply_overlay(image, p.paste_to, i, p.overlay_images) images.save_image(image_without_cc, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(i), p=p, suffix="-before-color-correction") image = apply_color_correction(p.color_corrections[i], image) image = apply_overlay(image, p.paste_to, i, p.overlay_images) - if opts.samples_save and not p.do_not_save_samples: + if opts.samples_save and not p.do_not_save_samples and save_images_if_interrupt: images.save_image(image, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(i), p=p) text = infotext(i) @@ -859,8 +864,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: if opts.enable_pnginfo: image.info["parameters"] = text output_images.append(image) - - if hasattr(p, 'mask_for_overlay') and p.mask_for_overlay and any([opts.save_mask, opts.save_mask_composite, opts.return_mask, opts.return_mask_composite]): + if hasattr(p, 'mask_for_overlay') and p.mask_for_overlay and any([opts.save_mask, opts.save_mask_composite, opts.return_mask, opts.return_mask_composite]) and save_images_if_interrupt: image_mask = p.mask_for_overlay.convert('RGB') image_mask_composite = Image.composite(image.convert('RGBA').convert('RGBa'), Image.new('RGBa', image.size), images.resize_image(2, p.mask_for_overlay, image.width, image.height).convert('L')).convert('RGBA') @@ -896,7 +900,6 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: grid.info["parameters"] = text output_images.insert(0, grid) index_of_first_image = 1 - if opts.grid_save: images.save_image(grid, p.outpath_grids, "grid", p.all_seeds[0], p.all_prompts[0], opts.grid_format, info=infotext(use_main_prompt=True), short_filename=not opts.grid_extended_filename, p=p, grid=True) @@ -1091,7 +1094,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): def save_intermediate(image, index): """saves image before applying hires fix, if enabled in options; takes as an argument either an image or batch with latent space images""" - if not opts.save or self.do_not_save_samples or not opts.save_images_before_highres_fix: + if not opts.save or self.do_not_save_samples or not opts.save_images_before_highres_fix or not save_images_if_interrupted(): return if not isinstance(image, Image.Image): diff --git a/modules/shared.py b/modules/shared.py index 516ad7e8..a7de686c 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -356,6 +356,7 @@ options_templates.update(options_section(('saving-images', "Saving images/grids" "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"), + "dont_save_interrupted_images": OptionInfo(False, "Don't save incomplete images").info("Don't save images that has been interrupted in mid-generation, they will still show up in webui output."), })) options_templates.update(options_section(('saving-paths', "Paths for saving"), { -- cgit v1.2.3 From 8ece321df34af982164a8a38bfa67c2f26484bc8 Mon Sep 17 00:00:00 2001 From: dhwz Date: Sat, 5 Aug 2023 16:03:06 +0200 Subject: add new gradio themes --- modules/shared.py | 23 +++++++++++++++++++++-- 1 file changed, 21 insertions(+), 2 deletions(-) (limited to 'modules/shared.py') diff --git a/modules/shared.py b/modules/shared.py index 92adc563..14cef51f 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -51,16 +51,35 @@ restricted_opts = { # 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", - "freddyaboulton/dracula_revamped", "gradio/dracula_test", "abidlabs/dracula_test", + "abidlabs/Lime", "abidlabs/pakistan", + "Ama434/neutral-barlow", "dawood/microsoft_windows", - "ysharma/steampunk" + "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" ] -- cgit v1.2.3 From 1f7fc4d7a350c38121af84527873bf8a40643fe3 Mon Sep 17 00:00:00 2001 From: dhwz Date: Sat, 5 Aug 2023 16:07:57 +0200 Subject: fix whitespace --- modules/shared.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/shared.py') diff --git a/modules/shared.py b/modules/shared.py index 14cef51f..9530d80e 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -79,7 +79,7 @@ gradio_hf_hub_themes = [ "step-3-profit/Midnight-Deep", "Taithrah/Minimal", "ysharma/huggingface", - "ysharma/steampunk" + "ysharma/steampunk" ] -- cgit v1.2.3 From c6278c15a81bf65efb65ded50368972a920cc198 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Sat, 5 Aug 2023 17:11:37 +0300 Subject: add explanation for gradio themes --- modules/shared.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/shared.py') diff --git a/modules/shared.py b/modules/shared.py index 9530d80e..a99b500b 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -549,7 +549,7 @@ options_templates.update(options_section(('extra_networks', "Extra Networks"), { options_templates.update(options_section(('ui', "User interface"), { "localization": OptionInfo("None", "Localization", gr.Dropdown, lambda: {"choices": ["None"] + list(localization.localizations.keys())}, refresh=lambda: localization.list_localizations(cmd_opts.localizations_dir)).needs_reload_ui(), - "gradio_theme": OptionInfo("Default", "Gradio theme", ui_components.DropdownEditable, lambda: {"choices": ["Default"] + gradio_hf_hub_themes}).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(), "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"), -- cgit v1.2.3 From dfc01c68cd204fd091b3cf5b855d5c0f77a6526a Mon Sep 17 00:00:00 2001 From: catboxanon <122327233+catboxanon@users.noreply.github.com> Date: Sat, 5 Aug 2023 21:23:58 -0400 Subject: Increase s_churn max value --- modules/shared.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/shared.py') diff --git a/modules/shared.py b/modules/shared.py index a99b500b..1a6cc86d 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -606,7 +606,7 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters" "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": 1.0, "step": 0.01}), + 's_churn': OptionInfo(0.0, "sigma churn", gr.Slider, {"minimum": 0.0, "maximum": 100.0, "step": 0.01}), 's_tmin': OptionInfo(0.0, "sigma tmin", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), 's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), '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"), -- cgit v1.2.3 From c11104fed5ffee7b9a22674889580028296c5e55 Mon Sep 17 00:00:00 2001 From: catboxanon <122327233+catboxanon@users.noreply.github.com> Date: Sat, 5 Aug 2023 21:42:03 -0400 Subject: Add s_tmax --- modules/processing.py | 2 +- modules/shared.py | 1 + 2 files changed, 2 insertions(+), 1 deletion(-) (limited to 'modules/shared.py') diff --git a/modules/processing.py b/modules/processing.py index a9d66005..a5cd2a47 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -148,7 +148,7 @@ class StableDiffusionProcessing: self.s_min_uncond = s_min_uncond or opts.s_min_uncond self.s_churn = s_churn or opts.s_churn self.s_tmin = s_tmin or opts.s_tmin - self.s_tmax = s_tmax or float('inf') # not representable as a standard ui option + self.s_tmax = opts.data.get('s_tmax', 0) or float('inf') # not representable as a standard ui option self.s_noise = s_noise or opts.s_noise self.override_settings = {k: v for k, v in (override_settings or {}).items() if k not in shared.restricted_opts} self.override_settings_restore_afterwards = override_settings_restore_afterwards diff --git a/modules/shared.py b/modules/shared.py index a99b500b..b1c0c0e9 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -608,6 +608,7 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters" "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": 1.0, "step": 0.01}), 's_tmin': OptionInfo(0.0, "sigma tmin", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), + 's_tmax': OptionInfo(0.0, "sigma tmax", gr.Slider, {"minimum": 0.0, "maximum": 999.0, "step": 0.01}).info("0 = inf"), 's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), '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"), -- cgit v1.2.3 From d86d12e9117772f041682124badc7baac7c57911 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Sun, 6 Aug 2023 06:21:36 +0300 Subject: rework saving incomplete images --- modules/processing.py | 18 +++++++++--------- modules/shared.py | 2 +- 2 files changed, 10 insertions(+), 10 deletions(-) (limited to 'modules/shared.py') diff --git a/modules/processing.py b/modules/processing.py index 8f26621b..aef8fafd 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -103,10 +103,6 @@ def txt2img_image_conditioning(sd_model, x, width, height): return x.new_zeros(x.shape[0], 5, 1, 1, dtype=x.dtype, device=x.device) -def save_images_if_interrupted(): - return not (opts.dont_save_interrupted_images and (state.interrupted or state.skipped)) - - class StableDiffusionProcessing: """ The first set of paramaters: sd_models -> do_not_reload_embeddings represent the minimum required to create a StableDiffusionProcessing @@ -372,6 +368,10 @@ class StableDiffusionProcessing: def parse_extra_network_prompts(self): self.prompts, self.extra_network_data = extra_networks.parse_prompts(self.prompts) + def save_samples(self) -> bool: + """Returns whether generated images need to be written to disk""" + return opts.samples_save and not self.do_not_save_samples and (opts.save_incomplete_images or not state.interrupted and not state.skipped) + class Processed: def __init__(self, p: StableDiffusionProcessing, images_list, seed=-1, info="", subseed=None, all_prompts=None, all_negative_prompts=None, all_seeds=None, all_subseeds=None, index_of_first_image=0, infotexts=None, comments=""): @@ -827,7 +827,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: def infotext(index=0, use_main_prompt=False): return create_infotext(p, p.prompts, p.seeds, p.subseeds, use_main_prompt=use_main_prompt, index=index, all_negative_prompts=p.negative_prompts) - save_images_if_interrupt = save_images_if_interrupted() + save_samples = p.save_samples() for i, x_sample in enumerate(x_samples_ddim): p.batch_index = i @@ -836,7 +836,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: x_sample = x_sample.astype(np.uint8) if p.restore_faces: - if opts.save and not p.do_not_save_samples and opts.save_images_before_face_restoration and save_images_if_interrupt: + if save_samples and opts.save_images_before_face_restoration: images.save_image(Image.fromarray(x_sample), p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(i), p=p, suffix="-before-face-restoration") devices.torch_gc() @@ -851,14 +851,14 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: p.scripts.postprocess_image(p, pp) image = pp.image if p.color_corrections is not None and i < len(p.color_corrections): - if opts.save and not p.do_not_save_samples and opts.save_images_before_color_correction and save_images_if_interrupt: + if save_samples and opts.save_images_before_color_correction: image_without_cc = apply_overlay(image, p.paste_to, i, p.overlay_images) images.save_image(image_without_cc, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(i), p=p, suffix="-before-color-correction") image = apply_color_correction(p.color_corrections[i], image) image = apply_overlay(image, p.paste_to, i, p.overlay_images) - if opts.samples_save and not p.do_not_save_samples and save_images_if_interrupt: + if save_samples: images.save_image(image, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(i), p=p) text = infotext(i) @@ -1096,7 +1096,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): def save_intermediate(image, index): """saves image before applying hires fix, if enabled in options; takes as an argument either an image or batch with latent space images""" - if not opts.save or self.do_not_save_samples or not opts.save_images_before_highres_fix or not save_images_if_interrupted(): + if not self.save_samples() or not opts.save_images_before_highres_fix: return if not isinstance(image, Image.Image): diff --git a/modules/shared.py b/modules/shared.py index 2bd49ff1..3276d45e 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -385,7 +385,7 @@ options_templates.update(options_section(('saving-images', "Saving images/grids" "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"), - "dont_save_interrupted_images": OptionInfo(False, "Don't save incomplete images").info("Don't save images that has been interrupted in mid-generation, they will still show up in webui output."), + "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"), { -- cgit v1.2.3 From e9c591b10194a866f1e508899047aca6681c90dc Mon Sep 17 00:00:00 2001 From: w-e-w <40751091+w-e-w@users.noreply.github.com> Date: Sun, 6 Aug 2023 12:06:46 +0900 Subject: Gradio theme cache --- modules/shared.py | 9 +++++++-- 1 file changed, 7 insertions(+), 2 deletions(-) (limited to 'modules/shared.py') diff --git a/modules/shared.py b/modules/shared.py index a99b500b..5e17a4be 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -550,6 +550,7 @@ options_templates.update(options_section(('extra_networks', "Extra Networks"), { options_templates.update(options_section(('ui', "User interface"), { "localization": OptionInfo("None", "Localization", gr.Dropdown, lambda: {"choices": ["None"] + list(localization.localizations.keys())}, refresh=lambda: localization.list_localizations(cmd_opts.localizations_dir)).needs_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"), @@ -863,13 +864,17 @@ def reload_gradio_theme(theme_name=None): gradio_theme = gr.themes.Default(**default_theme_args) else: try: - gradio_theme = gr.themes.ThemeClass.from_hub(theme_name) + theme_cache_path = os.path.join(script_path, 'tmp', 'gradio_themes', 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: + 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 -- cgit v1.2.3 From f9950da3e30e6c8e2993d1d69d6e5c26c6a56485 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Sun, 6 Aug 2023 12:39:28 +0300 Subject: create dir for gradio themes cache if it's missing --- modules/shared.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) (limited to 'modules/shared.py') diff --git a/modules/shared.py b/modules/shared.py index 525371cc..8e1b8063 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -866,10 +866,12 @@ def reload_gradio_theme(theme_name=None): gradio_theme = gr.themes.Default(**default_theme_args) else: try: - theme_cache_path = os.path.join(script_path, 'tmp', 'gradio_themes', f'{theme_name.replace("/", "_")}.json') + 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: -- cgit v1.2.3 From 57e8a11d17a6646fdf551320f5f714fba752987a Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Sun, 6 Aug 2023 13:25:51 +0300 Subject: enable cond cache by default --- modules/processing.py | 31 ++++++++++++++++++------------- modules/shared.py | 2 +- 2 files changed, 19 insertions(+), 14 deletions(-) (limited to 'modules/shared.py') diff --git a/modules/processing.py b/modules/processing.py index 7d21fb12..31745006 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -295,7 +295,7 @@ class StableDiffusionProcessing: self.sampler = None self.c = None self.uc = None - if not opts.experimental_persistent_cond_cache: + if not opts.persistent_cond_cache: StableDiffusionProcessing.cached_c = [None, None] StableDiffusionProcessing.cached_uc = [None, None] @@ -319,6 +319,21 @@ 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] + def cached_params(self, required_prompts, steps, extra_network_data): + """Returns parameters that invalidate the cond cache if changed""" + + return ( + required_prompts, + steps, + opts.CLIP_stop_at_last_layers, + shared.sd_model.sd_checkpoint_info, + extra_network_data, + opts.sdxl_crop_left, + opts.sdxl_crop_top, + self.width, + self.height, + ) + def get_conds_with_caching(self, function, required_prompts, steps, caches, extra_network_data): """ Returns the result of calling function(shared.sd_model, required_prompts, steps) @@ -332,17 +347,7 @@ class StableDiffusionProcessing: caches is a list with items described above. """ - cached_params = ( - required_prompts, - steps, - opts.CLIP_stop_at_last_layers, - shared.sd_model.sd_checkpoint_info, - extra_network_data, - opts.sdxl_crop_left, - opts.sdxl_crop_top, - self.width, - self.height, - ) + cached_params = self.cached_params(required_prompts, steps, extra_network_data) for cache in caches: if cache[0] is not None and cached_params == cache[0]: @@ -1184,7 +1189,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): super().close() self.hr_c = None self.hr_uc = None - if not opts.experimental_persistent_cond_cache: + if not opts.persistent_cond_cache: StableDiffusionProcessingTxt2Img.cached_hr_uc = [None, None] StableDiffusionProcessingTxt2Img.cached_hr_c = [None, None] diff --git a/modules/shared.py b/modules/shared.py index 8e1b8063..078e8135 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -506,7 +506,7 @@ options_templates.update(options_section(('optimizations', "Optimizations"), { "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"), - "experimental_persistent_cond_cache": OptionInfo(False, "persistent cond cache").info("Experimental, keep cond caches across jobs, reduce overhead."), + "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"), { -- cgit v1.2.3 From 976963ab6dc46141cceba9a007546c53f35e033a Mon Sep 17 00:00:00 2001 From: catboxanon <122327233+catboxanon@users.noreply.github.com> Date: Sun, 6 Aug 2023 12:30:23 -0400 Subject: Clean up k-diffusion sigma params --- modules/shared.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) (limited to 'modules/shared.py') diff --git a/modules/shared.py b/modules/shared.py index 078e8135..57e9158e 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -609,13 +609,13 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters" "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}), - 's_tmin': OptionInfo(0.0, "sigma tmin", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), + 's_tmin': OptionInfo(0.0, "sigma tmin", gr.Slider, {"minimum": 0.0, "maximum": 10.0, "step": 0.01}), 's_tmax': OptionInfo(0.0, "sigma tmax", gr.Slider, {"minimum": 0.0, "maximum": 999.0, "step": 0.01}).info("0 = inf"), - 's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), + 's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.1, "step": 0.001}), '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 schedule"), - 'rho': OptionInfo(0.0, "rho", gr.Number).info("0 = default (7 for karras, 1 for polyexponential); higher values result in a more steep noise schedule (decreases faster)"), + '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"]}), -- cgit v1.2.3 From 7bcfb4654f677801602c80c0823eb0ad11f5b4b6 Mon Sep 17 00:00:00 2001 From: catboxanon <122327233+catboxanon@users.noreply.github.com> Date: Sun, 6 Aug 2023 12:41:21 -0400 Subject: Add info to k-diffusion sigma params --- modules/shared.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) (limited to 'modules/shared.py') diff --git a/modules/shared.py b/modules/shared.py index 57e9158e..f0fb9dc7 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -608,10 +608,10 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters" "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}), - 's_tmin': OptionInfo(0.0, "sigma tmin", gr.Slider, {"minimum": 0.0, "maximum": 10.0, "step": 0.01}), - 's_tmax': OptionInfo(0.0, "sigma tmax", gr.Slider, {"minimum": 0.0, "maximum": 999.0, "step": 0.01}).info("0 = inf"), - 's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.1, "step": 0.001}), + '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"), -- cgit v1.2.3 From c96e4750d895a47290dc7f96e030197069c75fa4 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Mon, 7 Aug 2023 08:07:09 +0300 Subject: SD VAE rework 2 - the setting for preferring opts.sd_vae has been inverted and reworded - resolve_vae function made easier to read and now returns an object rather than a tuple - if the checkbox for overriding per-model preferences is checked, opts.sd_vae overrides checkpoint user metadata - changing VAE in user metadata for currently loaded model immediately applies the selection --- modules/sd_models.py | 2 +- modules/sd_vae.py | 71 +++++++++++++++++----- modules/shared.py | 6 +- .../ui_extra_networks_checkpoints_user_metadata.py | 8 ++- webui.py | 2 +- 5 files changed, 69 insertions(+), 20 deletions(-) (limited to 'modules/shared.py') diff --git a/modules/sd_models.py b/modules/sd_models.py index f6051604..d65735e3 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -356,7 +356,7 @@ def load_model_weights(model, checkpoint_info: CheckpointInfo, state_dict, timer sd_vae.delete_base_vae() sd_vae.clear_loaded_vae() - vae_file, vae_source = sd_vae.resolve_vae(checkpoint_info.filename) + vae_file, vae_source = sd_vae.resolve_vae(checkpoint_info.filename).tuple() sd_vae.load_vae(model, vae_file, vae_source) timer.record("load VAE") diff --git a/modules/sd_vae.py b/modules/sd_vae.py index 0bd5e19b..38bcb840 100644 --- a/modules/sd_vae.py +++ b/modules/sd_vae.py @@ -1,5 +1,7 @@ import os import collections +from dataclasses import dataclass + from modules import paths, shared, devices, script_callbacks, sd_models, extra_networks import glob from copy import deepcopy @@ -97,37 +99,74 @@ def find_vae_near_checkpoint(checkpoint_file): return None -def resolve_vae(checkpoint_file): - if shared.cmd_opts.vae_path is not None: - return shared.cmd_opts.vae_path, 'from commandline argument' +@dataclass +class VaeResolution: + vae: str = None + source: str = None + resolved: bool = True + + def tuple(self): + return self.vae, self.source + + +def is_automatic(): + return shared.opts.sd_vae in {"Automatic", "auto"} # "auto" for people with old config + + +def resolve_vae_from_setting() -> VaeResolution: + if shared.opts.sd_vae == "None": + return VaeResolution() + + vae_from_options = vae_dict.get(shared.opts.sd_vae, None) + if vae_from_options is not None: + return VaeResolution(vae_from_options, 'specified in settings') + + if not is_automatic(): + print(f"Couldn't find VAE named {shared.opts.sd_vae}; using None instead") + return VaeResolution(resolved=False) + + +def resolve_vae_from_user_metadata(checkpoint_file) -> VaeResolution: metadata = extra_networks.get_user_metadata(checkpoint_file) vae_metadata = metadata.get("vae", None) if vae_metadata is not None and vae_metadata != "Automatic": if vae_metadata == "None": - return None, None + return VaeResolution() vae_from_metadata = vae_dict.get(vae_metadata, None) if vae_from_metadata is not None: - return vae_from_metadata, "from user metadata" + return VaeResolution(vae_from_metadata, "from user metadata") + + return VaeResolution(resolved=False) - is_automatic = shared.opts.sd_vae in {"Automatic", "auto"} # "auto" for people with old config +def resolve_vae_near_checkpoint(checkpoint_file) -> VaeResolution: vae_near_checkpoint = find_vae_near_checkpoint(checkpoint_file) if vae_near_checkpoint is not None and (shared.opts.sd_vae_as_default or is_automatic): - return vae_near_checkpoint, 'found near the checkpoint' + return VaeResolution(vae_near_checkpoint, 'found near the checkpoint') - if shared.opts.sd_vae == "None": - return None, None + return VaeResolution(resolved=False) - vae_from_options = vae_dict.get(shared.opts.sd_vae, None) - if vae_from_options is not None: - return vae_from_options, 'specified in settings' - if not is_automatic: - print(f"Couldn't find VAE named {shared.opts.sd_vae}; using None instead") +def resolve_vae(checkpoint_file) -> VaeResolution: + if shared.cmd_opts.vae_path is not None: + return VaeResolution(shared.cmd_opts.vae_path, 'from commandline argument') + + if shared.opts.sd_vae_overrides_per_model_preferences and not is_automatic(): + return resolve_vae_from_setting() + + res = resolve_vae_from_user_metadata(checkpoint_file) + if res.resolved: + return res + + res = resolve_vae_near_checkpoint(checkpoint_file) + if res.resolved: + return res + + res = resolve_vae_from_setting() - return None, None + return res def load_vae_dict(filename, map_location): @@ -201,7 +240,7 @@ def reload_vae_weights(sd_model=None, vae_file=unspecified): checkpoint_file = checkpoint_info.filename if vae_file == unspecified: - vae_file, vae_source = resolve_vae(checkpoint_file) + vae_file, vae_source = resolve_vae(checkpoint_file).tuple() else: vae_source = "from function argument" diff --git a/modules/shared.py b/modules/shared.py index 078e8135..da53f2d9 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -479,7 +479,7 @@ 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_as_default": OptionInfo(True, "Ignore selected VAE for stable diffusion checkpoints that have their own .vae.pt next to them"), + "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"), "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"), @@ -733,6 +733,10 @@ class Options: 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(',')] diff --git a/modules/ui_extra_networks_checkpoints_user_metadata.py b/modules/ui_extra_networks_checkpoints_user_metadata.py index 2c69aab8..25df0a80 100644 --- a/modules/ui_extra_networks_checkpoints_user_metadata.py +++ b/modules/ui_extra_networks_checkpoints_user_metadata.py @@ -1,6 +1,6 @@ import gradio as gr -from modules import ui_extra_networks_user_metadata, sd_vae +from modules import ui_extra_networks_user_metadata, sd_vae, shared from modules.ui_common import create_refresh_button @@ -18,6 +18,10 @@ class CheckpointUserMetadataEditor(ui_extra_networks_user_metadata.UserMetadataE self.write_user_metadata(name, user_metadata) + def update_vae(self, name): + if name == shared.sd_model.sd_checkpoint_info.name_for_extra: + sd_vae.reload_vae_weights() + def put_values_into_components(self, name): user_metadata = self.get_user_metadata(name) values = super().put_values_into_components(name) @@ -58,3 +62,5 @@ class CheckpointUserMetadataEditor(ui_extra_networks_user_metadata.UserMetadataE ] self.setup_save_handler(self.button_save, self.save_user_metadata, edited_components) + self.button_save.click(fn=self.update_vae, inputs=[self.edit_name_input]) + diff --git a/webui.py b/webui.py index 1803ea8a..a5b11575 100644 --- a/webui.py +++ b/webui.py @@ -211,7 +211,7 @@ def configure_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_as_default", 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) -- cgit v1.2.3 From 4c72377bbf227276914c4012b339f0b3da8b366b Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Mon, 7 Aug 2023 09:42:13 +0300 Subject: Options in main UI update - correctly read values from pasted infotext - setting for column count - infotext paste: do not add a field to override settings if some other component is already handling it --- .../scripts/extra_options_section.py | 39 +++++++++++++++++----- modules/generation_parameters_copypaste.py | 5 +++ modules/shared.py | 2 +- 3 files changed, 37 insertions(+), 9 deletions(-) (limited to 'modules/shared.py') diff --git a/extensions-builtin/extra-options-section/scripts/extra_options_section.py b/extensions-builtin/extra-options-section/scripts/extra_options_section.py index 7bb0a1bb..d5c29bf2 100644 --- a/extensions-builtin/extra-options-section/scripts/extra_options_section.py +++ b/extensions-builtin/extra-options-section/scripts/extra_options_section.py @@ -1,5 +1,7 @@ +import math + import gradio as gr -from modules import scripts, shared, ui_components, ui_settings +from modules import scripts, shared, ui_components, ui_settings, generation_parameters_copypaste from modules.ui_components import FormColumn @@ -19,15 +21,33 @@ class ExtraOptionsSection(scripts.Script): def ui(self, is_img2img): self.comps = [] self.setting_names = [] + self.infotext_fields = [] + + mapping = {k: v for v, k in generation_parameters_copypaste.infotext_to_setting_name_mapping} with gr.Blocks() as interface: - with gr.Accordion("Options", open=False) if shared.opts.extra_options_accordion and shared.opts.extra_options else gr.Group(), gr.Row(): - for setting_name in shared.opts.extra_options: - with FormColumn(): - comp = ui_settings.create_setting_component(setting_name) + with gr.Accordion("Options", open=False) if shared.opts.extra_options_accordion and shared.opts.extra_options else gr.Group(): + + row_count = math.ceil(len(shared.opts.extra_options) / shared.opts.extra_options_cols) + + for row in range(row_count): + with gr.Row(): + for col in range(shared.opts.extra_options_cols): + index = row * shared.opts.extra_options_cols + col + if index >= len(shared.opts.extra_options): + break + + setting_name = shared.opts.extra_options[index] - self.comps.append(comp) - self.setting_names.append(setting_name) + with FormColumn(): + comp = ui_settings.create_setting_component(setting_name) + + self.comps.append(comp) + self.setting_names.append(setting_name) + + setting_infotext_name = mapping.get(setting_name) + if setting_infotext_name is not None: + self.infotext_fields.append((comp, setting_infotext_name)) def get_settings_values(): return [ui_settings.get_value_for_setting(key) for key in self.setting_names] @@ -44,5 +64,8 @@ class ExtraOptionsSection(scripts.Script): shared.options_templates.update(shared.options_section(('ui', "User interface"), { "extra_options": shared.OptionInfo([], "Options in main UI", ui_components.DropdownMulti, lambda: {"choices": list(shared.opts.data_labels.keys())}).js("info", "settingsHintsShowQuicksettings").info("setting entries that also appear in txt2img/img2img interfaces").needs_reload_ui(), - "extra_options_accordion": shared.OptionInfo(False, "Place options in main UI into an accordion").needs_restart() + "extra_options_cols": shared.OptionInfo(1, "Options in main UI - number of columns", gr.Number, {"precision": 0}).needs_reload_ui(), + "extra_options_accordion": shared.OptionInfo(False, "Options in main UI - place into an accordion").needs_reload_ui() })) + + diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index e71c9601..5758e6f3 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -414,10 +414,15 @@ def connect_paste(button, paste_fields, input_comp, override_settings_component, return res if override_settings_component is not None: + already_handled_fields = {key: 1 for _, key in paste_fields} + def paste_settings(params): vals = {} for param_name, setting_name in infotext_to_setting_name_mapping: + if param_name in already_handled_fields: + continue + v = params.get(param_name, None) if v is None: continue diff --git a/modules/shared.py b/modules/shared.py index 115e5276..4d854928 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -612,7 +612,7 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters" '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"), + '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)"), -- cgit v1.2.3 From c75bda867be5345bf959daf23bdc19eadc90841a Mon Sep 17 00:00:00 2001 From: w-e-w <40751091+w-e-w@users.noreply.github.com> Date: Tue, 8 Aug 2023 11:22:35 +0900 Subject: setting: Automatically open webui in browser on startup --- modules/shared.py | 1 + webui.py | 15 +++++++++++---- 2 files changed, 12 insertions(+), 4 deletions(-) (limited to 'modules/shared.py') diff --git a/modules/shared.py b/modules/shared.py index aa72c9c8..5a7be85b 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -385,6 +385,7 @@ options_templates.update(options_section(('face-restoration', "Face restoration" })) 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."), "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"), diff --git a/webui.py b/webui.py index 2dc4f1aa..844e2548 100644 --- a/webui.py +++ b/webui.py @@ -398,6 +398,13 @@ def webui(): gradio_auth_creds = list(get_gradio_auth_creds()) or None + auto_launch_browser = False + if os.getenv('SD_WEBUI_RESTARTING') != '1': + if shared.opts.auto_launch_browser == "Remote" or cmd_opts.autolaunch: + auto_launch_browser = True + elif shared.opts.auto_launch_browser == "Local": + auto_launch_browser = not any([cmd_opts.listen, cmd_opts.share, cmd_opts.ngrok]) + app, local_url, share_url = shared.demo.launch( share=cmd_opts.share, server_name=server_name, @@ -407,7 +414,7 @@ def webui(): ssl_verify=cmd_opts.disable_tls_verify, debug=cmd_opts.gradio_debug, auth=gradio_auth_creds, - inbrowser=cmd_opts.autolaunch and os.getenv('SD_WEBUI_RESTARTING') != '1', + inbrowser=auto_launch_browser, prevent_thread_lock=True, allowed_paths=cmd_opts.gradio_allowed_path, app_kwargs={ @@ -417,9 +424,6 @@ def webui(): root_path=f"/{cmd_opts.subpath}" if cmd_opts.subpath else "", ) - # after initial launch, disable --autolaunch for subsequent restarts - cmd_opts.autolaunch = False - startup_timer.record("gradio launch") # gradio uses a very open CORS policy via app.user_middleware, which makes it possible for @@ -464,6 +468,9 @@ def webui(): shared.demo.close() break + # disable auto launch webui in browser for subsequent UI Reload + os.environ.setdefault('SD_WEBUI_RESTARTING', '1') + print('Restarting UI...') shared.demo.close() time.sleep(0.5) -- cgit v1.2.3 From 2a72d76d6f3d34b1ffccec7736b19e7d52033dad Mon Sep 17 00:00:00 2001 From: dhwz Date: Tue, 8 Aug 2023 19:08:37 +0200 Subject: fix typo --- modules/processing.py | 2 +- modules/shared.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) (limited to 'modules/shared.py') diff --git a/modules/processing.py b/modules/processing.py index 31745006..dc6e8ff1 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 97f1eab5..e34847ce 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"), })) -- cgit v1.2.3 From 0d5dc9a6e7f6362e423a06bf0e75dd5854025394 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Wed, 9 Aug 2023 08:43:31 +0300 Subject: 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 (limited to 'modules/shared.py') diff --git a/modules/devices.py b/modules/devices.py index 00a00b18..ce59dc53 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 aa72b132..2df5e8c7 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 00000000..2d7baea5 --- /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 adda963b..97bc0804 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 e34847ce..e9b980a4 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 -- cgit v1.2.3 From da0712ee7d6e9353e6d2d1828d6217bd122fbd51 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Wed, 9 Aug 2023 08:47:53 +0300 Subject: Split history: mv modules/shared.py temp --- modules/shared.py | 976 ------------------------------------------------------ temp | 976 ++++++++++++++++++++++++++++++++++++++++++++++++++++++ 2 files changed, 976 insertions(+), 976 deletions(-) delete mode 100644 modules/shared.py create mode 100644 temp (limited to 'modules/shared.py') diff --git a/modules/shared.py b/modules/shared.py deleted file mode 100644 index e9b980a4..00000000 --- a/modules/shared.py +++ /dev/null @@ -1,976 +0,0 @@ -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.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() - - -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" - -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'), - "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 - -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/temp b/temp new file mode 100644 index 00000000..e9b980a4 --- /dev/null +++ b/temp @@ -0,0 +1,976 @@ +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.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() + + +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" + +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'), + "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 + +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) -- cgit v1.2.3 From 7d81ecbea6b558addd356d49c56891d04bc91fd4 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Wed, 9 Aug 2023 08:47:53 +0300 Subject: Split history: mv temp modules/shared.py --- modules/shared.py | 976 ++++++++++++++++++++++++++++++++++++++++++++++++++++++ temp | 976 ------------------------------------------------------ 2 files changed, 976 insertions(+), 976 deletions(-) create mode 100644 modules/shared.py delete mode 100644 temp (limited to 'modules/shared.py') diff --git a/modules/shared.py b/modules/shared.py new file mode 100644 index 00000000..e9b980a4 --- /dev/null +++ b/modules/shared.py @@ -0,0 +1,976 @@ +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.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() + + +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" + +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'), + "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 + +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/temp b/temp deleted file mode 100644 index e9b980a4..00000000 --- a/temp +++ /dev/null @@ -1,976 +0,0 @@ -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.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() - - -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" - -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'), - "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 - -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) -- cgit v1.2.3 From 386245a26427a64f364f66f6fecd03b3bccfd7f3 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Wed, 9 Aug 2023 10:25:35 +0300 Subject: 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 | 961 ++--------------------------- 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 | 692 +-------------------- 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, 762 insertions(+), 1665 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 (limited to 'modules/shared.py') diff --git a/modules/devices.py b/modules/devices.py index ce59dc53..c01f0602 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 e4633af4..bf9a1878 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 5758e6f3..d932c67d 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 ba3c43a4..019c1d60 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 e8f585da..c1320288 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 9ceb43ba..bce527cc 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 00000000..59cb75ec --- /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 2d7baea5..f927a318 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 53c1df54..88a09899 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 8266fa39..08dd03f1 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 38bcb840..5ac1ac31 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 e9b980a4..8ba72f49 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 -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 - - +config_filename = cmd_opts.ui_settings_file 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 +demo = None +device = None -opts = Options() -if os.path.exists(config_filename): - opts.load(config_filename) +weight_load_location = None +xformers_available = False -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. - """ +hypernetworks = {} - sd_model_val = None +loaded_hypernetworks = [] - @property - def sd_model(self): - import modules.sd_models +state = None - return modules.sd_models.model_data.get_sd_model() +prompt_styles = None - @sd_model.setter - def sd_model(self, value): - import modules.sd_models +interrogator = None - modules.sd_models.model_data.set_sd_model(value) +face_restorers = [] +options_templates = None +opts = None -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 - - 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 +mem_mon = None - yield os.path.join(root, filename) +options_section = options.options_section +OptionInfo = options.OptionInfo +OptionHTML = options.OptionHTML +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 -def ldm_print(*args, **kwargs): - if opts.hide_ldm_prints: - return +reload_gradio_theme = shared_gradio_themes.reload_gradio_theme - 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 00000000..af24938b --- /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 00000000..ad1f2212 --- /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 00000000..e7fc18d2 --- /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 89792e88..e4ec40a8 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 e9b980a4..7468bc81 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.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 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 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 00000000..3dc9c788 --- /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 00000000..cf82e104 --- /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 cf24c6dd..7d906e1f 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 e3753e97..30b80417 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 303af9cd..99d19ff0 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 00000000..60afc067 --- /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 6d36f880..0f1ace97 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() -- cgit v1.2.3 From 7ba8f11688bee1a04b48d8108627fd25ada69721 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Wed, 9 Aug 2023 15:06:03 +0300 Subject: fix missing restricted_opts from shared --- modules/shared.py | 1 + modules/shared_init.py | 1 + 2 files changed, 2 insertions(+) (limited to 'modules/shared.py') diff --git a/modules/shared.py b/modules/shared.py index 8ba72f49..d9d01484 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 e7fc18d2..b88d1d8e 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) -- cgit v1.2.3 From dfd6ea3fcaf2eb701af61136a290132303a729d5 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Mon, 21 Aug 2023 15:07:10 +0300 Subject: ditch --always-batch-cond-uncond in favor of an UI setting --- modules/cmd_args.py | 2 +- modules/sd_samplers_cfg_denoiser.py | 4 ++-- modules/shared.py | 2 +- modules/shared_options.py | 3 ++- 4 files changed, 6 insertions(+), 5 deletions(-) (limited to 'modules/shared.py') diff --git a/modules/cmd_args.py b/modules/cmd_args.py index f360f484..9f8e5b30 100644 --- a/modules/cmd_args.py +++ b/modules/cmd_args.py @@ -37,7 +37,7 @@ parser.add_argument("--allow-code", action='store_true', help="allow custom scri parser.add_argument("--medvram", action='store_true', help="enable stable diffusion model optimizations for sacrificing a little speed for low VRM usage") parser.add_argument("--lowvram", action='store_true', help="enable stable diffusion model optimizations for sacrificing a lot of speed for very low VRM usage") parser.add_argument("--lowram", action='store_true', help="load stable diffusion checkpoint weights to VRAM instead of RAM") -parser.add_argument("--always-batch-cond-uncond", action='store_true', help="disables cond/uncond batching that is enabled to save memory with --medvram or --lowvram") +parser.add_argument("--always-batch-cond-uncond", action='store_true', help="does not do anything") parser.add_argument("--unload-gfpgan", action='store_true', help="does not do anything.") parser.add_argument("--precision", type=str, help="evaluate at this precision", choices=["full", "autocast"], default="autocast") parser.add_argument("--upcast-sampling", action='store_true', help="upcast sampling. No effect with --no-half. Usually produces similar results to --no-half with better performance while using less memory.") diff --git a/modules/sd_samplers_cfg_denoiser.py b/modules/sd_samplers_cfg_denoiser.py index bc9b97e4..b8101d38 100644 --- a/modules/sd_samplers_cfg_denoiser.py +++ b/modules/sd_samplers_cfg_denoiser.py @@ -165,7 +165,7 @@ class CFGDenoiser(torch.nn.Module): else: cond_in = catenate_conds([tensor, uncond]) - if shared.batch_cond_uncond: + if shared.opts.batch_cond_uncond: x_out = self.inner_model(x_in, sigma_in, cond=make_condition_dict(cond_in, image_cond_in)) else: x_out = torch.zeros_like(x_in) @@ -175,7 +175,7 @@ class CFGDenoiser(torch.nn.Module): x_out[a:b] = self.inner_model(x_in[a:b], sigma_in[a:b], cond=make_condition_dict(subscript_cond(cond_in, a, b), image_cond_in[a:b])) else: x_out = torch.zeros_like(x_in) - batch_size = batch_size*2 if shared.batch_cond_uncond else batch_size + batch_size = batch_size*2 if shared.opts.batch_cond_uncond else batch_size for batch_offset in range(0, tensor.shape[0], batch_size): a = batch_offset b = min(a + batch_size, tensor.shape[0]) diff --git a/modules/shared.py b/modules/shared.py index d9d01484..0c57b712 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -10,7 +10,7 @@ from modules import util 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) +batch_cond_uncond = True # old field, unused now in favor of shared.opts.batch_cond_uncond parallel_processing_allowed = not cmd_opts.lowvram and not cmd_opts.medvram styles_filename = cmd_opts.styles_file config_filename = cmd_opts.ui_settings_file diff --git a/modules/shared_options.py b/modules/shared_options.py index 6f1a738d..095cf479 100644 --- a/modules/shared_options.py +++ b/modules/shared_options.py @@ -192,7 +192,8 @@ options_templates.update(options_section(('optimizations', "Optimizations"), { "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}, 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"), + "persistent_cond_cache": OptionInfo(True, "Persistent cond cache").info("do not recalculate conds from prompts if prompts have not changed since previous calculation"), + "batch_cond_uncond": OptionInfo(True, "Batch cond/uncond").info("do both conditional and unconditional denoising in one batch; uses a bit more VRAM during sampling, but improves speed; previously this was controlled by --always-batch-cond-uncond comandline argument"), })) options_templates.update(options_section(('compatibility', "Compatibility"), { -- cgit v1.2.3 From 016554e43740e0b7ded75e89255de81270de9d6c Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Tue, 22 Aug 2023 18:49:08 +0300 Subject: add --medvram-sdxl --- modules/cmd_args.py | 1 + modules/interrogate.py | 5 ++--- modules/lowvram.py | 18 ++++++++++++++++-- modules/sd_models.py | 16 ++++++++-------- modules/sd_unet.py | 2 +- modules/sd_vae.py | 4 ++-- modules/shared.py | 2 +- 7 files changed, 31 insertions(+), 17 deletions(-) (limited to 'modules/shared.py') diff --git a/modules/cmd_args.py b/modules/cmd_args.py index 9f8e5b30..f0f361bd 100644 --- a/modules/cmd_args.py +++ b/modules/cmd_args.py @@ -35,6 +35,7 @@ parser.add_argument("--hypernetwork-dir", type=str, default=os.path.join(models_ parser.add_argument("--localizations-dir", type=str, default=os.path.join(script_path, 'localizations'), help="localizations directory") parser.add_argument("--allow-code", action='store_true', help="allow custom script execution from webui") parser.add_argument("--medvram", action='store_true', help="enable stable diffusion model optimizations for sacrificing a little speed for low VRM usage") +parser.add_argument("--medvram-sdxl", action='store_true', help="enable --medvram optimization just for SDXL models") parser.add_argument("--lowvram", action='store_true', help="enable stable diffusion model optimizations for sacrificing a lot of speed for very low VRM usage") parser.add_argument("--lowram", action='store_true', help="load stable diffusion checkpoint weights to VRAM instead of RAM") parser.add_argument("--always-batch-cond-uncond", action='store_true', help="does not do anything") diff --git a/modules/interrogate.py b/modules/interrogate.py index a3ae1dd5..3045560d 100644 --- a/modules/interrogate.py +++ b/modules/interrogate.py @@ -186,9 +186,8 @@ class InterrogateModels: res = "" shared.state.begin(job="interrogate") try: - if shared.cmd_opts.lowvram or shared.cmd_opts.medvram: - lowvram.send_everything_to_cpu() - devices.torch_gc() + lowvram.send_everything_to_cpu() + devices.torch_gc() self.load() diff --git a/modules/lowvram.py b/modules/lowvram.py index 96f52b7b..45701046 100644 --- a/modules/lowvram.py +++ b/modules/lowvram.py @@ -1,5 +1,5 @@ import torch -from modules import devices +from modules import devices, shared module_in_gpu = None cpu = torch.device("cpu") @@ -14,6 +14,20 @@ def send_everything_to_cpu(): module_in_gpu = None +def is_needed(sd_model): + return shared.cmd_opts.lowvram or shared.cmd_opts.medvram or shared.cmd_opts.medvram_sdxl and hasattr(sd_model, 'conditioner') + + +def apply(sd_model): + enable = is_needed(sd_model) + shared.parallel_processing_allowed = not enable + + if enable: + setup_for_low_vram(sd_model, not shared.cmd_opts.lowvram) + else: + sd_model.lowvram = False + + def setup_for_low_vram(sd_model, use_medvram): if getattr(sd_model, 'lowvram', False): return @@ -130,4 +144,4 @@ def setup_for_low_vram(sd_model, use_medvram): def is_enabled(sd_model): - return getattr(sd_model, 'lowvram', False) + return sd_model.lowvram diff --git a/modules/sd_models.py b/modules/sd_models.py index 27d15e66..4331853a 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -517,7 +517,7 @@ def get_empty_cond(sd_model): def send_model_to_cpu(m): - if shared.cmd_opts.lowvram or shared.cmd_opts.medvram: + if m.lowvram: lowvram.send_everything_to_cpu() else: m.to(devices.cpu) @@ -525,17 +525,17 @@ def send_model_to_cpu(m): devices.torch_gc() -def model_target_device(): - if shared.cmd_opts.lowvram or shared.cmd_opts.medvram: +def model_target_device(m): + if lowvram.is_needed(m): return devices.cpu else: return devices.device def send_model_to_device(m): - if shared.cmd_opts.lowvram or shared.cmd_opts.medvram: - lowvram.setup_for_low_vram(m, shared.cmd_opts.medvram) - else: + lowvram.apply(m) + + if not m.lowvram: m.to(shared.device) @@ -601,7 +601,7 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None): '': torch.float16, } - with sd_disable_initialization.LoadStateDictOnMeta(state_dict, device=model_target_device(), weight_dtype_conversion=weight_dtype_conversion): + with sd_disable_initialization.LoadStateDictOnMeta(state_dict, device=model_target_device(sd_model), weight_dtype_conversion=weight_dtype_conversion): load_model_weights(sd_model, checkpoint_info, state_dict, timer) timer.record("load weights from state dict") @@ -743,7 +743,7 @@ def reload_model_weights(sd_model=None, info=None): script_callbacks.model_loaded_callback(sd_model) timer.record("script callbacks") - if not shared.cmd_opts.lowvram and not shared.cmd_opts.medvram: + if not sd_model.lowvram: sd_model.to(devices.device) timer.record("move model to device") diff --git a/modules/sd_unet.py b/modules/sd_unet.py index 6d708ad2..5525cfbc 100644 --- a/modules/sd_unet.py +++ b/modules/sd_unet.py @@ -47,7 +47,7 @@ def apply_unet(option=None): if current_unet_option is None: current_unet = None - if not (shared.cmd_opts.lowvram or shared.cmd_opts.medvram): + if not shared.sd_model.lowvram: shared.sd_model.model.diffusion_model.to(devices.device) return diff --git a/modules/sd_vae.py b/modules/sd_vae.py index ee118656..669097da 100644 --- a/modules/sd_vae.py +++ b/modules/sd_vae.py @@ -263,7 +263,7 @@ def reload_vae_weights(sd_model=None, vae_file=unspecified): if loaded_vae_file == vae_file: return - if shared.cmd_opts.lowvram or shared.cmd_opts.medvram: + if sd_model.lowvram: lowvram.send_everything_to_cpu() else: sd_model.to(devices.cpu) @@ -275,7 +275,7 @@ def reload_vae_weights(sd_model=None, vae_file=unspecified): sd_hijack.model_hijack.hijack(sd_model) script_callbacks.model_loaded_callback(sd_model) - if not shared.cmd_opts.lowvram and not shared.cmd_opts.medvram: + if not sd_model.lowvram: sd_model.to(devices.device) print("VAE weights loaded.") diff --git a/modules/shared.py b/modules/shared.py index 0c57b712..f321159d 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -11,7 +11,7 @@ cmd_opts = shared_cmd_options.cmd_opts parser = shared_cmd_options.parser batch_cond_uncond = True # old field, unused now in favor of shared.opts.batch_cond_uncond -parallel_processing_allowed = not cmd_opts.lowvram and not cmd_opts.medvram +parallel_processing_allowed = True styles_filename = cmd_opts.styles_file config_filename = cmd_opts.ui_settings_file hide_dirs = {"visible": not cmd_opts.hide_ui_dir_config} -- cgit v1.2.3 From 3ec5ce941626c3c5ff4aac884c926ceb4ba60d37 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Tue, 22 Aug 2023 19:05:03 +0300 Subject: add type annotations for extra fields of shared.sd_model --- modules/sd_models_types.py | 31 +++++++++++++++++++++++++++++++ modules/shared.py | 5 ++--- 2 files changed, 33 insertions(+), 3 deletions(-) create mode 100644 modules/sd_models_types.py (limited to 'modules/shared.py') diff --git a/modules/sd_models_types.py b/modules/sd_models_types.py new file mode 100644 index 00000000..5ffd2f4f --- /dev/null +++ b/modules/sd_models_types.py @@ -0,0 +1,31 @@ +from ldm.models.diffusion.ddpm import LatentDiffusion +from typing import TYPE_CHECKING + + +if TYPE_CHECKING: + from modules.sd_models import CheckpointInfo + + +class WebuiSdModel(LatentDiffusion): + """This class is not actually instantinated, but its fields are created and fieeld by webui""" + + lowvram: bool + """True if lowvram/medvram optimizations are enabled -- see modules.lowvram for more info""" + + sd_model_hash: str + """short hash, 10 first characters of SHA1 hash of the model file; may be None if --no-hashing flag is used""" + + sd_model_checkpoint: str + """path to the file on disk that model weights were obtained from""" + + sd_checkpoint_info: 'CheckpointInfo' + """structure with additional information about the file with model's weights""" + + is_sdxl: bool + """True if the model's architecture is SDXL""" + + is_sd2: bool + """True if the model's architecture is SD 2.x""" + + is_sd1: bool + """True if the model's architecture is SD 1.x""" diff --git a/modules/shared.py b/modules/shared.py index f321159d..63661939 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -2,9 +2,8 @@ import sys import gradio as gr -from modules import shared_cmd_options, shared_gradio_themes, options, shared_items +from modules import shared_cmd_options, shared_gradio_themes, options, shared_items, sd_models_types 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 modules import util cmd_opts = shared_cmd_options.cmd_opts @@ -40,7 +39,7 @@ options_templates = None opts = None restricted_opts = None -sd_model: LatentDiffusion = None +sd_model: sd_models_types.WebuiSdModel = None settings_components = None """assinged from ui.py, a mapping on setting names to gradio components repsponsible for those settings""" -- cgit v1.2.3