Merge pull request #17313 from WhizZest/fix-setuptools-version

Fix the issue of `pip install 'setuptools<70'` failing in cmd

.eslintrc.js

@@ -88,6 +88,7 @@ module.exports = {
         // imageviewer.js
         modalPrevImage: "readonly",
         modalNextImage: "readonly",
+        updateModalImageIfVisible: "readonly",
         // localStorage.js
         localSet: "readonly",
         localGet: "readonly",

README.md

@@ -133,7 +133,7 @@ If your system is very new, you need to install python3.11 or python3.10:
 # Ubuntu 24.04
 sudo add-apt-repository ppa:deadsnakes/ppa
 sudo apt update
-sudo apt install python3.11
+sudo apt install python3.11 python3.11-venv
 
 # Manjaro/Arch
 sudo pacman -S yay

html/footer.html

@@ -1,5 +1,5 @@
 <div>
-        <a href="{api_docs}">API</a>
+        <a href="{api_docs}" target="_blank">API</a>
          • 
         <a href="https://github.com/AUTOMATIC1111/stable-diffusion-webui">GitHub</a>
          • 

javascript/imageviewer.js

@@ -54,6 +54,7 @@ function updateOnBackgroundChange() {
         updateModalImage();
     }
 }
+const updateModalImageIfVisible = updateOnBackgroundChange;
 
 function modalImageSwitch(offset) {
     var galleryButtons = all_gallery_buttons();
@@ -164,6 +165,7 @@ function modalLivePreviewToggle(event) {
     const modalToggleLivePreview = gradioApp().getElementById("modal_toggle_live_preview");
     opts.js_live_preview_in_modal_lightbox = !opts.js_live_preview_in_modal_lightbox;
     modalToggleLivePreview.innerHTML = opts.js_live_preview_in_modal_lightbox ? "🗇" : "🗆";
+    updateModalImageIfVisible();
     event.stopPropagation();
 }
 

javascript/progressbar.js

@@ -190,7 +190,7 @@ function requestProgress(id_task, progressbarContainer, gallery, atEnd, onProgre
                         livePreview.className = 'livePreview';
                         gallery.insertBefore(livePreview, gallery.firstElementChild);
                     }
-
+                    updateModalImageIfVisible();
                     livePreview.appendChild(img);
                     if (livePreview.childElementCount > 2) {
                         livePreview.removeChild(livePreview.firstElementChild);

launch.py

@@ -6,6 +6,11 @@ git = launch_utils.git
 index_url = launch_utils.index_url
 dir_repos = launch_utils.dir_repos
 
+if args.uv:
+    from modules.uv_hook import patch
+    patch()
+
+
 commit_hash = launch_utils.commit_hash
 git_tag = launch_utils.git_tag
 

modules/cmd_args.py

@@ -126,3 +126,4 @@ parser.add_argument("--skip-load-model-at-start", action='store_true', help="if
 parser.add_argument("--unix-filenames-sanitization", action='store_true', help="allow any symbols except '/' in filenames. May conflict with your browser and file system")
 parser.add_argument("--filenames-max-length", type=int, default=128, help='maximal length of filenames of saved images. If you override it, it can conflict with your file system')
 parser.add_argument("--no-prompt-history", action='store_true', help="disable read prompt from last generation feature; settings this argument will not create '--data_path/params.txt' file")
+parser.add_argument("--uv", action='store_true', help="use the uv package manager")

modules/hashes.py

@@ -1,7 +1,7 @@
 import hashlib
 import os.path
 
-from modules import shared
+from modules import shared, errors
 import modules.cache
 
 dump_cache = modules.cache.dump_cache
@@ -32,7 +32,7 @@ def sha256_from_cache(filename, title, use_addnet_hash=False):
     cached_sha256 = hashes[title].get("sha256", None)
     cached_mtime = hashes[title].get("mtime", 0)
 
-    if ondisk_mtime > cached_mtime or cached_sha256 is None:
+    if ondisk_mtime != cached_mtime or cached_sha256 is None:
         return None
 
     return cached_sha256
@@ -82,3 +82,31 @@ def addnet_hash_safetensors(b):
 
     return hash_sha256.hexdigest()
 
+
+def partial_hash_from_cache(filename, *, ignore_cache: bool = False, digits: int = 8):
+    """old hash that only looks at a small part of the file and is prone to collisions
+    kept for compatibility, don't use this for new things
+    """
+    try:
+        filename = str(filename)
+        mtime = os.path.getmtime(filename)
+        hashes = cache('partial-hash')
+        cache_entry = hashes.get(filename, {})
+        cache_mtime = cache_entry.get("mtime", 0)
+        cache_hash = cache_entry.get("hash", None)
+        if mtime == cache_mtime and cache_hash and not ignore_cache:
+            return cache_hash[0:digits]
+
+        with open(filename, 'rb') as file:
+            m = hashlib.sha256()
+            file.seek(0x100000)
+            m.update(file.read(0x10000))
+            partial_hash = m.hexdigest()
+            hashes[filename] = {'mtime': mtime, 'hash': partial_hash}
+            return partial_hash[0:digits]
+
+    except FileNotFoundError:
+        pass
+    except Exception:
+        errors.report(f'Error calculating partial hash for {filename}', exc_info=True)
+    return 'NOFILE'

modules/images.py

@@ -409,6 +409,7 @@ class FilenameGenerator:
         'generation_number': lambda self: NOTHING_AND_SKIP_PREVIOUS_TEXT if (self.p.n_iter == 1 and self.p.batch_size == 1) or self.zip else self.p.iteration * self.p.batch_size + self.p.batch_index + 1,
         'hasprompt': lambda self, *args: self.hasprompt(*args),  # accepts formats:[hasprompt<prompt1|default><prompt2>..]
         'clip_skip': lambda self: opts.data["CLIP_stop_at_last_layers"],
+        'randn_source': lambda self: opts.data["randn_source"],
         'denoising': lambda self: self.p.denoising_strength if self.p and self.p.denoising_strength else NOTHING_AND_SKIP_PREVIOUS_TEXT,
         'user': lambda self: self.p.user,
         'vae_filename': lambda self: self.get_vae_filename(),

modules/launch_utils.py

@@ -313,9 +313,43 @@ def requirements_met(requirements_file):
     return True
 
 
+def get_cuda_comp_cap():
+    """
+    Returns float of CUDA Compute Capability using nvidia-smi
+    Returns 0.0 on error
+    CUDA Compute Capability
+    ref https://developer.nvidia.com/cuda-gpus
+    ref https://en.wikipedia.org/wiki/CUDA
+    Blackwell consumer GPUs should return 12.0 data-center GPUs should return 10.0
+    """
+    try:
+        return max(map(float, subprocess.check_output(['nvidia-smi', '--query-gpu=compute_cap', '--format=noheader,csv'], text=True).splitlines()))
+    except Exception as _:
+        return 0.0
+
+
+def early_access_blackwell_wheels():
+    """For Blackwell GPUs, use Early Access PyTorch Wheels provided by Nvidia"""
+    print('deprecated early_access_blackwell_wheels')
+    if all([
+            os.environ.get('TORCH_INDEX_URL') is None,
+            sys.version_info.major == 3,
+            sys.version_info.minor in (10, 11, 12),
+            platform.system() == "Windows",
+            get_cuda_comp_cap() >= 10,  # Blackwell
+    ]):
+        base_repo = 'https://huggingface.co/w-e-w/torch-2.6.0-cu128.nv/resolve/main/'
+        ea_whl = {
+            10: f'{base_repo}torch-2.6.0+cu128.nv-cp310-cp310-win_amd64.whl#sha256=fef3de7ce8f4642e405576008f384304ad0e44f7b06cc1aa45e0ab4b6e70490d {base_repo}torchvision-0.20.0a0+cu128.nv-cp310-cp310-win_amd64.whl#sha256=50841254f59f1db750e7348b90a8f4cd6befec217ab53cbb03780490b225abef',
+            11: f'{base_repo}torch-2.6.0+cu128.nv-cp311-cp311-win_amd64.whl#sha256=6665c36e6a7e79e7a2cb42bec190d376be9ca2859732ed29dd5b7b5a612d0d26 {base_repo}torchvision-0.20.0a0+cu128.nv-cp311-cp311-win_amd64.whl#sha256=bbc0ee4938e35fe5a30de3613bfcd2d8ef4eae334cf8d49db860668f0bb47083',
+            12: f'{base_repo}torch-2.6.0+cu128.nv-cp312-cp312-win_amd64.whl#sha256=a3197f72379d34b08c4a4bcf49ea262544a484e8702b8c46cbcd66356c89def6 {base_repo}torchvision-0.20.0a0+cu128.nv-cp312-cp312-win_amd64.whl#sha256=235e7be71ac4e75b0f8e817bae4796d7bac8a67146d2037ab96394f2bdc63e6c'
+        }
+        return f'pip install {ea_whl.get(sys.version_info.minor)}'
+
+
 def prepare_environment():
-    torch_index_url = os.environ.get('TORCH_INDEX_URL', "https://download.pytorch.org/whl/cu121")
+    torch_index_url = os.environ.get('TORCH_INDEX_URL', "https://download.pytorch.org/whl/cu128")
-    torch_command = os.environ.get('TORCH_COMMAND', f"pip install torch==2.1.2 torchvision==0.16.2 --extra-index-url {torch_index_url}")
+    torch_command = os.environ.get('TORCH_COMMAND', f"pip install torch==2.7.0 torchvision==0.22.0 --extra-index-url {torch_index_url}")
     if args.use_ipex:
         if platform.system() == "Windows":
             # The "Nuullll/intel-extension-for-pytorch" wheels were built from IPEX source for Intel Arc GPU: https://github.com/intel/intel-extension-for-pytorch/tree/xpu-main
@@ -339,12 +373,12 @@ def prepare_environment():
     requirements_file = os.environ.get('REQS_FILE', "requirements_versions.txt")
     requirements_file_for_npu = os.environ.get('REQS_FILE_FOR_NPU', "requirements_npu.txt")
 
-    xformers_package = os.environ.get('XFORMERS_PACKAGE', 'xformers==0.0.23.post1')
+    xformers_package = os.environ.get('XFORMERS_PACKAGE', 'xformers==0.0.30')
     clip_package = os.environ.get('CLIP_PACKAGE', "https://github.com/openai/CLIP/archive/d50d76daa670286dd6cacf3bcd80b5e4823fc8e1.zip")
     openclip_package = os.environ.get('OPENCLIP_PACKAGE', "https://github.com/mlfoundations/open_clip/archive/bb6e834e9c70d9c27d0dc3ecedeebeaeb1ffad6b.zip")
 
     assets_repo = os.environ.get('ASSETS_REPO', "https://github.com/AUTOMATIC1111/stable-diffusion-webui-assets.git")
-    stable_diffusion_repo = os.environ.get('STABLE_DIFFUSION_REPO', "https://github.com/Stability-AI/stablediffusion.git")
+    stable_diffusion_repo = os.environ.get('STABLE_DIFFUSION_REPO', "https://github.com/w-e-w/stablediffusion.git")
     stable_diffusion_xl_repo = os.environ.get('STABLE_DIFFUSION_XL_REPO', "https://github.com/Stability-AI/generative-models.git")
     k_diffusion_repo = os.environ.get('K_DIFFUSION_REPO', 'https://github.com/crowsonkb/k-diffusion.git')
     blip_repo = os.environ.get('BLIP_REPO', 'https://github.com/salesforce/BLIP.git')
@@ -388,8 +422,24 @@ def prepare_environment():
         )
     startup_timer.record("torch GPU test")
 
+    # Ensure build dependencies are installed before any package that might need them
+    def ensure_build_dependencies():
+        """Ensure essential build tools are available"""
+        if not is_installed("wheel"):
+            run_pip("install wheel", "wheel")
+        # Check setuptools version compatibility
+        try:
+            setuptools_version = run(f'"{python}" -c "import setuptools; print(setuptools.__version__)"', None, None).strip()
+            if setuptools_version >= "70":
+                run_pip("install setuptools==69.5.1", "setuptools")
+        except Exception:
+            # If setuptools check fails, install compatible version
+            run_pip("install setuptools==69.5.1", "setuptools")
+    # Install build dependencies early
+    ensure_build_dependencies()
+
     if not is_installed("clip"):
-        run_pip(f"install {clip_package}", "clip")
+        run_pip(f"install --no-build-isolation {clip_package}", "clip")
         startup_timer.record("install clip")
 
     if not is_installed("open_clip"):

modules/sd_hijack_optimizations.py

@@ -54,7 +54,7 @@ class SdOptimizationXformers(SdOptimization):
     priority = 100
 
     def is_available(self):
-        return shared.cmd_opts.force_enable_xformers or (shared.xformers_available and torch.cuda.is_available() and (6, 0) <= torch.cuda.get_device_capability(shared.device) <= (9, 0))
+        return shared.cmd_opts.force_enable_xformers or (shared.xformers_available and torch.cuda.is_available() and (6, 0) <= torch.cuda.get_device_capability(shared.device) <= (12, 0))
 
     def apply(self):
         ldm.modules.attention.CrossAttention.forward = xformers_attention_forward

modules/sd_models.py

@@ -13,6 +13,7 @@ from urllib import request
 import ldm.modules.midas as midas
 
 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, patches
+from modules.hashes import partial_hash_from_cache as model_hash  # noqa: F401 for backwards compatibility
 from modules.timer import Timer
 from modules.shared import opts
 import tomesd
@@ -87,7 +88,7 @@ class CheckpointInfo:
         self.name = name
         self.name_for_extra = os.path.splitext(os.path.basename(filename))[0]
         self.model_name = os.path.splitext(name.replace("/", "_").replace("\\", "_"))[0]
-        self.hash = model_hash(filename)
+        self.hash = hashes.partial_hash_from_cache(filename)
 
         self.sha256 = hashes.sha256_from_cache(self.filename, f"checkpoint/{name}")
         self.shorthash = self.sha256[0:10] if self.sha256 else None
@@ -200,21 +201,6 @@ def get_closet_checkpoint_match(search_string):
     return None
 
 
-def model_hash(filename):
-    """old hash that only looks at a small part of the file and is prone to collisions"""
-
-    try:
-        with open(filename, "rb") as file:
-            import hashlib
-            m = hashlib.sha256()
-
-            file.seek(0x100000)
-            m.update(file.read(0x10000))
-            return m.hexdigest()[0:8]
-    except FileNotFoundError:
-        return 'NOFILE'
-
-
 def select_checkpoint():
     """Raises `FileNotFoundError` if no checkpoints are found."""
     model_checkpoint = shared.opts.sd_model_checkpoint

modules/sd_schedulers.py

@@ -117,12 +117,15 @@ def ddim_scheduler(n, sigma_min, sigma_max, inner_model, device):
 
 
 def beta_scheduler(n, sigma_min, sigma_max, inner_model, device):
-    # From "Beta Sampling is All You Need" [arXiv:2407.12173] (Lee et. al, 2024) """
+    # From "Beta Sampling is All You Need" [arXiv:2407.12173] (Lee et. al, 2024)
     alpha = shared.opts.beta_dist_alpha
     beta = shared.opts.beta_dist_beta
-    timesteps = 1 - np.linspace(0, 1, n)
+    curve = [stats.beta.ppf(x, alpha, beta) for x in np.linspace(1, 0, n)]
-    timesteps = [stats.beta.ppf(x, alpha, beta) for x in timesteps]
+
-    sigmas = [sigma_min + (x * (sigma_max-sigma_min)) for x in timesteps]
+    start = inner_model.sigma_to_t(torch.tensor(sigma_max))
+    end = inner_model.sigma_to_t(torch.tensor(sigma_min))
+    timesteps = [end + x * (start - end) for x in curve]
+    sigmas = [inner_model.t_to_sigma(ts) for ts in timesteps]
     sigmas += [0.0]
     return torch.FloatTensor(sigmas).to(device)
 

modules/shared_options.py

@@ -407,8 +407,8 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters"
     'uni_pc_lower_order_final': OptionInfo(True, "UniPC lower order final", infotext='UniPC lower order final'),
     'sd_noise_schedule': OptionInfo("Default", "Noise schedule for sampling", gr.Radio, {"choices": ["Default", "Zero Terminal SNR"]}, infotext="Noise Schedule").info("for use with zero terminal SNR trained models"),
     'skip_early_cond': OptionInfo(0.0, "Ignore negative prompt during early sampling", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}, infotext="Skip Early CFG").info("disables CFG on a proportion of steps at the beginning of generation; 0=skip none; 1=skip all; can both improve sample diversity/quality and speed up sampling; XYZ plot: Skip Early CFG"),
-    'beta_dist_alpha': OptionInfo(0.6, "Beta scheduler - alpha", gr.Slider, {"minimum": 0.01, "maximum": 1.0, "step": 0.01}, infotext='Beta scheduler alpha').info('Default = 0.6; the alpha parameter of the beta distribution used in Beta sampling'),
+    'beta_dist_alpha': OptionInfo(0.6, "Beta scheduler - alpha", gr.Slider, {"minimum": 0.01, "maximum": 5.0, "step": 0.01}, infotext='Beta scheduler alpha').info('Default = 0.6; the alpha parameter of the beta distribution used in Beta sampling'),
-    'beta_dist_beta': OptionInfo(0.6, "Beta scheduler - beta", gr.Slider, {"minimum": 0.01, "maximum": 1.0, "step": 0.01}, infotext='Beta scheduler beta').info('Default = 0.6; the beta parameter of the beta distribution used in Beta sampling'),
+    'beta_dist_beta': OptionInfo(0.6, "Beta scheduler - beta", gr.Slider, {"minimum": 0.01, "maximum": 5.0, "step": 0.01}, infotext='Beta scheduler beta').info('Default = 0.6; the beta parameter of the beta distribution used in Beta sampling'),
 }))
 
 options_templates.update(options_section(('postprocessing', "Postprocessing", "postprocessing"), {

modules/util.py

@@ -1,3 +1,4 @@
+from __future__ import annotations
 import os
 import re
 

modules/uv_hook.py

@@ -0,0 +1,50 @@
+import sys
+import copy
+import shlex
+import subprocess
+from functools import wraps
+
+BAD_FLAGS = ("--prefer-binary", '-I', '--ignore-installed')
+
+
+def patch():
+    if hasattr(subprocess, "__original_run"):
+        return
+
+    print("using uv")
+    try:
+        subprocess.run(['uv', '-V'])
+    except FileNotFoundError:
+        subprocess.run([sys.executable, '-m', 'pip', 'install', 'uv'])
+
+    subprocess.__original_run = subprocess.run
+
+    @wraps(subprocess.__original_run)
+    def patched_run(*args, **kwargs):
+        _kwargs = copy.copy(kwargs)
+        if args:
+            command, *_args = args
+        else:
+            command, _args = _kwargs.pop("args", ""), ()
+
+        if isinstance(command, str):
+            command = shlex.split(command)
+        else:
+            command = [arg.strip() for arg in command]
+
+        if not isinstance(command, list) or "pip" not in command:
+            return subprocess.__original_run(*args, **kwargs)
+
+        cmd = command[command.index("pip") + 1:]
+
+        cmd = [arg for arg in cmd if arg not in BAD_FLAGS]
+
+        modified_command = ["uv", "pip", *cmd]
+
+        cmd_str = shlex.join([*modified_command, *_args])
+        result = subprocess.__original_run(cmd_str, **_kwargs)
+        if result.returncode != 0:
+            return subprocess.__original_run(*args, **kwargs)
+        return result
+
+    subprocess.run = patched_run

script.js

@@ -182,7 +182,7 @@ document.addEventListener('keydown', function(e) {
         const lightboxModal = document.querySelector('#lightboxModal');
         if (!globalPopup || globalPopup.style.display === 'none') {
             if (document.activeElement === lightboxModal) return;
-            if (interruptButton.style.display === 'block') {
+            if (interruptButton?.style.display === 'block') {
                 interruptButton.click();
                 e.preventDefault();
             }

style.css

@@ -480,8 +480,10 @@ div.toprow-compact-tools{
 }
 
 #settings_result{
-    height: 1.4em;
+    min-height: 1.4em;
     margin: 0 1.2em;
+    max-height: calc(var(--text-md) * var(--line-sm) * 5);
+    overflow-y: auto;
 }
 
 table.popup-table{
@@ -600,6 +602,7 @@ table.popup-table .link{
     background: var(--background-fill-primary);
     width: 100%;
     height: 100%;
+    pointer-events: none;
 }
 
 .livePreview img{

webui.sh

@@ -127,7 +127,7 @@ then
 fi
 
 # Check prerequisites
-gpu_info=$(lspci 2>/dev/null | grep -E "VGA|Display")
+gpu_info=$(lspci 2>/dev/null | grep -E "VGA|Display|CMP")
 case "$gpu_info" in
     *"Navi 1"*)
         export HSA_OVERRIDE_GFX_VERSION=10.3.0