diff --git a/CHANGELOG.md b/CHANGELOG.md index 295d26c8c..596b1ec45 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,3 +1,8 @@ +## 1.9.4 + +### Bug Fixes: +* pin setuptools version to fix the startup error ([#15882](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/15882)) + ## 1.9.3 ### Bug Fixes: diff --git a/extensions-builtin/Lora/networks.py b/extensions-builtin/Lora/networks.py index 42b14dc23..18809364b 100644 --- a/extensions-builtin/Lora/networks.py +++ b/extensions-builtin/Lora/networks.py @@ -260,6 +260,16 @@ def load_networks(names, te_multipliers=None, unet_multipliers=None, dyn_dims=No loaded_networks.clear() + unavailable_networks = [] + for name in names: + if name.lower() in forbidden_network_aliases and available_networks.get(name) is None: + unavailable_networks.append(name) + elif available_network_aliases.get(name) is None: + unavailable_networks.append(name) + + if unavailable_networks: + update_available_networks_by_names(unavailable_networks) + networks_on_disk = [available_networks.get(name, None) if name.lower() in forbidden_network_aliases else available_network_aliases.get(name, None) for name in names] if any(x is None for x in networks_on_disk): list_available_networks() @@ -566,22 +576,16 @@ def network_MultiheadAttention_load_state_dict(self, *args, **kwargs): return originals.MultiheadAttention_load_state_dict(self, *args, **kwargs) -def list_available_networks(): - available_networks.clear() - available_network_aliases.clear() - forbidden_network_aliases.clear() - available_network_hash_lookup.clear() - forbidden_network_aliases.update({"none": 1, "Addams": 1}) - - os.makedirs(shared.cmd_opts.lora_dir, exist_ok=True) - +def process_network_files(names: list[str] | None = None): candidates = list(shared.walk_files(shared.cmd_opts.lora_dir, allowed_extensions=[".pt", ".ckpt", ".safetensors"])) candidates += list(shared.walk_files(shared.cmd_opts.lyco_dir_backcompat, allowed_extensions=[".pt", ".ckpt", ".safetensors"])) for filename in candidates: if os.path.isdir(filename): continue - name = os.path.splitext(os.path.basename(filename))[0] + # if names is provided, only load networks with names in the list + if names and name not in names: + continue try: entry = network.NetworkOnDisk(name, filename) except OSError: # should catch FileNotFoundError and PermissionError etc. @@ -597,6 +601,22 @@ def list_available_networks(): available_network_aliases[entry.alias] = entry +def update_available_networks_by_names(names: list[str]): + process_network_files(names) + + +def list_available_networks(): + available_networks.clear() + available_network_aliases.clear() + forbidden_network_aliases.clear() + available_network_hash_lookup.clear() + forbidden_network_aliases.update({"none": 1, "Addams": 1}) + + os.makedirs(shared.cmd_opts.lora_dir, exist_ok=True) + + process_network_files() + + re_network_name = re.compile(r"(.*)\s*\([0-9a-fA-F]+\)") diff --git a/javascript/ui.js b/javascript/ui.js index e0f5feebd..16faacebb 100644 --- a/javascript/ui.js +++ b/javascript/ui.js @@ -337,8 +337,8 @@ onOptionsChanged(function() { let txt2img_textarea, img2img_textarea = undefined; function restart_reload() { + document.body.style.backgroundColor = "var(--background-fill-primary)"; document.body.innerHTML = '

Reloading...

'; - var requestPing = function() { requestGet("./internal/ping", {}, function(data) { location.reload(); diff --git a/modules/images.py b/modules/images.py index c0ff8a630..1be176cdf 100644 --- a/modules/images.py +++ b/modules/images.py @@ -653,7 +653,7 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i # WebP and JPG formats have maximum dimension limits of 16383 and 65535 respectively. switch to PNG which has a much higher limit if (image.height > 65535 or image.width > 65535) and extension.lower() in ("jpg", "jpeg") or (image.height > 16383 or image.width > 16383) and extension.lower() == "webp": print('Image dimensions too large; saving as PNG') - extension = ".png" + extension = "png" if save_to_dirs is None: save_to_dirs = (grid and opts.grid_save_to_dirs) or (not grid and opts.save_to_dirs and not no_prompt) diff --git a/modules/processing.py b/modules/processing.py index 76557dd7f..c22da4169 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -569,7 +569,7 @@ class Processed: self.all_negative_prompts = all_negative_prompts or p.all_negative_prompts or [self.negative_prompt] self.all_seeds = all_seeds or p.all_seeds or [self.seed] self.all_subseeds = all_subseeds or p.all_subseeds or [self.subseed] - self.infotexts = infotexts or [info] + self.infotexts = infotexts or [info] * len(images_list) self.version = program_version() def js(self): diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py index 7f9e328d0..0269f1f5b 100644 --- a/modules/sd_hijack_optimizations.py +++ b/modules/sd_hijack_optimizations.py @@ -486,7 +486,8 @@ def xformers_attention_forward(self, x, context=None, mask=None, **kwargs): k_in = self.to_k(context_k) v_in = self.to_v(context_v) - q, k, v = (rearrange(t, 'b n (h d) -> b n h d', h=h) for t in (q_in, k_in, v_in)) + q, k, v = (t.reshape(t.shape[0], t.shape[1], h, -1) for t in (q_in, k_in, v_in)) + del q_in, k_in, v_in dtype = q.dtype @@ -497,7 +498,8 @@ def xformers_attention_forward(self, x, context=None, mask=None, **kwargs): out = out.to(dtype) - out = rearrange(out, 'b n h d -> b n (h d)', h=h) + b, n, h, d = out.shape + out = out.reshape(b, n, h * d) return self.to_out(out) diff --git a/modules/sd_schedulers.py b/modules/sd_schedulers.py index 99a6f7be2..0c09af8d0 100644 --- a/modules/sd_schedulers.py +++ b/modules/sd_schedulers.py @@ -4,6 +4,9 @@ import torch import k_diffusion +import numpy as np + +from modules import shared @dataclasses.dataclass class Scheduler: @@ -30,6 +33,33 @@ def sgm_uniform(n, sigma_min, sigma_max, inner_model, device): sigs += [0.0] return torch.FloatTensor(sigs).to(device) +def get_align_your_steps_sigmas(n, sigma_min, sigma_max, device='cpu'): + # https://research.nvidia.com/labs/toronto-ai/AlignYourSteps/howto.html + def loglinear_interp(t_steps, num_steps): + """ + Performs log-linear interpolation of a given array of decreasing numbers. + """ + xs = np.linspace(0, 1, len(t_steps)) + ys = np.log(t_steps[::-1]) + + new_xs = np.linspace(0, 1, num_steps) + new_ys = np.interp(new_xs, xs, ys) + + interped_ys = np.exp(new_ys)[::-1].copy() + return interped_ys + + if shared.sd_model.is_sdxl: + sigmas = [14.615, 6.315, 3.771, 2.181, 1.342, 0.862, 0.555, 0.380, 0.234, 0.113, 0.029] + else: + # Default to SD 1.5 sigmas. + sigmas = [14.615, 6.475, 3.861, 2.697, 1.886, 1.396, 0.963, 0.652, 0.399, 0.152, 0.029] + + if n != len(sigmas): + sigmas = np.append(loglinear_interp(sigmas, n), [0.0]) + else: + sigmas.append(0.0) + + return torch.FloatTensor(sigmas).to(device) def kl_optimal(n, sigma_min, sigma_max, device): alpha_min = torch.arctan(torch.tensor(sigma_min, device=device)) @@ -47,6 +77,7 @@ schedulers = [ Scheduler('polyexponential', 'Polyexponential', k_diffusion.sampling.get_sigmas_polyexponential, default_rho=1.0), Scheduler('sgm_uniform', 'SGM Uniform', sgm_uniform, need_inner_model=True, aliases=["SGMUniform"]), Scheduler('kl_optimal', 'KL Optimal', kl_optimal), + Scheduler('align_your_steps', 'Align Your Steps', get_align_your_steps_sigmas), ] schedulers_map = {**{x.name: x for x in schedulers}, **{x.label: x for x in schedulers}} diff --git a/requirements_versions.txt b/requirements_versions.txt index 3df74f3d6..3037a395b 100644 --- a/requirements_versions.txt +++ b/requirements_versions.txt @@ -1,3 +1,4 @@ +setuptools==69.5.1 # temp fix for compatibility with some old packages GitPython==3.1.32 Pillow==9.5.0 accelerate==0.21.0