pre merge cleanup

launch.py

@@ -7,8 +7,6 @@ import shlex
 import platform
 import argparse
 import json
-import warnings
-from rich import print
 
 parser = argparse.ArgumentParser(add_help=False)
 parser.add_argument("--ui-settings-file", type=str, default='config.json')
@@ -17,6 +15,7 @@ args, _ = parser.parse_known_args(sys.argv)
 
 script_path = os.path.dirname(__file__)
 data_path = os.getcwd()
+
 dir_repos = "repositories"
 dir_extensions = "extensions"
 python = sys.executable
@@ -25,7 +24,6 @@ index_url = os.environ.get('INDEX_URL', "")
 stored_commit_hash = None
 skip_install = False
 
-warnings.filterwarnings(action="ignore", category=UserWarning)
 
 def check_python_version():
     is_windows = platform.system() == "Windows"
@@ -36,11 +34,26 @@ def check_python_version():
     if is_windows:
         supported_minors = [10]
     else:
-        supported_minors = [9, 10, 11]
+        supported_minors = [7, 8, 9, 10, 11]
 
     if not (major == 3 and minor in supported_minors):
         import modules.errors
-        modules.errors.print_error_explanation(f"Incompatible Python version: {major}.{minor}.{micro} required 3.9-3.11")
+
+        modules.errors.print_error_explanation(f"""
+INCOMPATIBLE PYTHON VERSION
+
+This program is tested with 3.10.6 Python, but you have {major}.{minor}.{micro}.
+If you encounter an error with "RuntimeError: Couldn't install torch." message,
+or any other error regarding unsuccessful package (library) installation,
+please downgrade (or upgrade) to the latest version of 3.10 Python
+and delete current Python and "venv" folder in WebUI's directory.
+
+You can download 3.10 Python from here: https://www.python.org/downloads/release/python-3109/
+
+{"Alternatively, use a binary release of WebUI: https://github.com/AUTOMATIC1111/stable-diffusion-webui/releases" if is_windows else ""}
+
+Use --skip-python-version-check to suppress this warning.
+""")
 
 
 def commit_hash():
@@ -167,6 +180,23 @@ def git_pull_recursive(dir):
                 print(f"Couldn't perform 'git pull' on repository in '{subdir}':\n{e.output.decode('utf-8').strip()}\n")
 
 
+def version_check(commit):
+    try:
+        import requests
+        commits = requests.get('https://api.github.com/repos/AUTOMATIC1111/stable-diffusion-webui/branches/master').json()
+        if commit != "<none>" and commits['commit']['sha'] != commit:
+            print("--------------------------------------------------------")
+            print("| You are not up to date with the most recent release. |")
+            print("| Consider running `git pull` to update.               |")
+            print("--------------------------------------------------------")
+        elif commits['commit']['sha'] == commit:
+            print("You are up to date with the most recent release.")
+        else:
+            print("Not a git clone, can't perform version check.")
+    except Exception as e:
+        print("version check failed", e)
+
+
 def run_extension_installer(extension_dir):
     path_installer = os.path.join(extension_dir, "install.py")
     if not os.path.isfile(path_installer):
@@ -176,9 +206,7 @@ def run_extension_installer(extension_dir):
         env = os.environ.copy()
         env['PYTHONPATH'] = os.path.abspath(".")
 
-        stdout = run(f'"{python}" "{path_installer}"', errdesc=f"Error running install.py for extension {extension_dir}", custom_env=env)
-        if stdout is not None:
-            print(stdout)
+        print(run(f'"{python}" "{path_installer}"', errdesc=f"Error running install.py for extension {extension_dir}", custom_env=env))
     except Exception as e:
         print(e, file=sys.stderr)
 
@@ -209,9 +237,11 @@ def run_extensions_installers(settings_file):
 def prepare_environment():
     global skip_install
 
+    torch_command = os.environ.get('TORCH_COMMAND', "pip install torch==1.13.1+cu117 torchvision==0.14.1+cu117 --extra-index-url https://download.pytorch.org/whl/cu117")
     requirements_file = os.environ.get('REQS_FILE', "requirements_versions.txt")
     commandline_args = os.environ.get('COMMANDLINE_ARGS', "")
 
+    xformers_package = os.environ.get('XFORMERS_PACKAGE', 'xformers==0.0.16rc425')
     gfpgan_package = os.environ.get('GFPGAN_PACKAGE', "git+https://github.com/TencentARC/GFPGAN.git@8d2447a2d918f8eba5a4a01463fd48e45126a379")
     clip_package = os.environ.get('CLIP_PACKAGE', "git+https://github.com/openai/CLIP.git@d50d76daa670286dd6cacf3bcd80b5e4823fc8e1")
     openclip_package = os.environ.get('OPENCLIP_PACKAGE', "git+https://github.com/mlfoundations/open_clip.git@bb6e834e9c70d9c27d0dc3ecedeebeaeb1ffad6b")
@@ -222,10 +252,9 @@ def prepare_environment():
     codeformer_repo = os.environ.get('CODEFORMER_REPO', 'https://github.com/sczhou/CodeFormer.git')
     blip_repo = os.environ.get('BLIP_REPO', 'https://github.com/salesforce/BLIP.git')
 
-    stable_diffusion_commit_hash = os.environ.get('STABLE_DIFFUSION_COMMIT_HASH', "fc1488421a2761937b9d54784194157882cbc3b1")
-    taming_transformers_commit_hash = os.environ.get('TAMING_TRANSFORMERS_COMMIT_HASH', "3ba01b241669f5ade541ce990f7650a3b8f65318")
-    # k_diffusion_commit_hash = os.environ.get('K_DIFFUSION_COMMIT_HASH', "5b3af030dd83e0297272d861c19477735d0317ec")
-    k_diffusion_commit_hash = os.environ.get('K_DIFFUSION_COMMIT_HASH', "b43db16749d51055f813255eea2fdf1def801919")
+    stable_diffusion_commit_hash = os.environ.get('STABLE_DIFFUSION_COMMIT_HASH', "47b6b607fdd31875c9279cd2f4f16b92e4ea958e")
+    taming_transformers_commit_hash = os.environ.get('TAMING_TRANSFORMERS_COMMIT_HASH', "24268930bf1dce879235a7fddd0b2355b84d7ea6")
+    k_diffusion_commit_hash = os.environ.get('K_DIFFUSION_COMMIT_HASH', "5b3af030dd83e0297272d861c19477735d0317ec")
     codeformer_commit_hash = os.environ.get('CODEFORMER_COMMIT_HASH', "c5b4593074ba6214284d6acd5f1719b6c5d739af")
     blip_commit_hash = os.environ.get('BLIP_COMMIT_HASH', "48211a1594f1321b00f14c9f7a5b4813144b2fb9")
 
@@ -233,8 +262,14 @@ def prepare_environment():
 
     sys.argv, _ = extract_arg(sys.argv, '-f')
     sys.argv, update_all_extensions = extract_arg(sys.argv, '--update-all-extensions')
+    sys.argv, skip_torch_cuda_test = extract_arg(sys.argv, '--skip-torch-cuda-test')
     sys.argv, skip_python_version_check = extract_arg(sys.argv, '--skip-python-version-check')
+    sys.argv, reinstall_xformers = extract_arg(sys.argv, '--reinstall-xformers')
+    sys.argv, reinstall_torch = extract_arg(sys.argv, '--reinstall-torch')
+    sys.argv, update_check = extract_arg(sys.argv, '--update-check')
+    sys.argv, run_tests, test_dir = extract_opt(sys.argv, '--tests')
     sys.argv, skip_install = extract_arg(sys.argv, '--skip-install')
+    xformers = '--xformers' in sys.argv
     ngrok = '--ngrok' in sys.argv
 
     if not skip_python_version_check:
@@ -242,6 +277,15 @@ def prepare_environment():
 
     commit = commit_hash()
 
+    print(f"Python {sys.version}")
+    print(f"Commit hash: {commit}")
+
+    if reinstall_torch or not is_installed("torch") or not is_installed("torchvision"):
+        run(f'"{python}" -m {torch_command}', "Installing torch and torchvision", "Couldn't install torch", live=True)
+
+    if not skip_torch_cuda_test:
+        run_python("import torch; assert torch.cuda.is_available(), 'Torch is not able to use GPU; add --skip-torch-cuda-test to COMMANDLINE_ARGS variable to disable this check'")
+
     if not is_installed("gfpgan"):
         run_pip(f"install {gfpgan_package}", "gfpgan")
 
@@ -251,6 +295,18 @@ def prepare_environment():
     if not is_installed("open_clip"):
         run_pip(f"install {openclip_package}", "open_clip")
 
+    if (not is_installed("xformers") or reinstall_xformers) and xformers:
+        if platform.system() == "Windows":
+            if platform.python_version().startswith("3.10"):
+                run_pip(f"install -U -I --no-deps {xformers_package}", "xformers")
+            else:
+                print("Installation of xformers is not supported in this version of Python.")
+                print("You can also check this and build manually: https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Xformers#building-xformers-on-windows-by-duckness")
+                if not is_installed("xformers"):
+                    exit(0)
+        elif platform.system() == "Linux":
+            run_pip(f"install {xformers_package}", "xformers")
+
     if not is_installed("pyngrok") and ngrok:
         run_pip("install pyngrok", "ngrok")
 
@@ -269,31 +325,50 @@ def prepare_environment():
         requirements_file = os.path.join(script_path, requirements_file)
     run_pip(f"install -r \"{requirements_file}\"", "requirements for Web UI")
 
-    if "--exit" in sys.argv:
-        exit(0)
-
     run_extensions_installers(settings_file=args.ui_settings_file)
 
+    if update_check:
+        version_check(commit)
+
     if update_all_extensions:
         git_pull_recursive(os.path.join(data_path, dir_extensions))
     
+    if "--exit" in sys.argv:
+        print("Exiting because of --exit argument")
+        exit(0)
+
+    if run_tests:
+        exitcode = tests(test_dir)
+        exit(exitcode)
+
+
+def tests(test_dir):
+    if "--api" not in sys.argv:
+        sys.argv.append("--api")
+    if "--ckpt" not in sys.argv:
+        sys.argv.append("--ckpt")
+        sys.argv.append(os.path.join(script_path, "test/test_files/empty.pt"))
+    if "--skip-torch-cuda-test" not in sys.argv:
+        sys.argv.append("--skip-torch-cuda-test")
+    if "--disable-nan-check" not in sys.argv:
+        sys.argv.append("--disable-nan-check")
+
+    print(f"Launching Web UI in another process for testing with arguments: {' '.join(sys.argv[1:])}")
+
+    os.environ['COMMANDLINE_ARGS'] = ""
+    with open(os.path.join(script_path, 'test/stdout.txt'), "w", encoding="utf8") as stdout, open(os.path.join(script_path, 'test/stderr.txt'), "w", encoding="utf8") as stderr:
+        proc = subprocess.Popen([sys.executable, *sys.argv], stdout=stdout, stderr=stderr)
+
+    import test.server_poll
+    exitcode = test.server_poll.run_tests(proc, test_dir)
+
+    print(f"Stopping Web UI process with id {proc.pid}")
+    proc.kill()
+    return exitcode
+
 
 def start():
-    print(f"Launching server with arguments: {' '.join(sys.argv[1:])}")
-
-    rich_installed = False
-    try:
-        from rich.pretty import install as pretty_install
-        from rich.traceback import install as traceback_install
-        from rich.console import Console
-        console = Console(log_time=True, log_time_format='%H:%M:%S-%f')
-        pretty_install(console=console)
-        traceback_install(console=console, extra_lines=1, width=console.width, word_wrap=False, indent_guides=False, show_locals=True, max_frames=2)
-        rich_installed = True
-    except:
-        import traceback
-        pass # if rich is not installed do nothing
-
+    print(f"Launching {'API server' if '--nowebui' in sys.argv else 'Web UI'} with arguments: {' '.join(sys.argv[1:])}")
     import webui
     if '--nowebui' in sys.argv:
         webui.api_only()

modules/sd_models.py

@@ -9,7 +9,6 @@ from omegaconf import OmegaConf
 from os import mkdir
 from urllib import request
 import ldm.modules.midas as midas
-import io
 
 from ldm.util import instantiate_from_config
 
@@ -18,9 +17,6 @@ from modules.paths import models_path
 from modules.sd_hijack_inpainting import do_inpainting_hijack
 from modules.timer import Timer
 
-import rich
-from rich import print
-
 model_dir = "Stable-diffusion"
 model_path = os.path.abspath(os.path.join(paths.models_path, model_dir))
 
@@ -238,18 +234,16 @@ def read_metadata_from_safetensors(filename):
         return res
 
 
-def read_state_dict(checkpoint_file):
-    if 'v1-5-pruned-emaonly.safetensors' in checkpoint_file:
-        pl_sd = safetensors.torch.load_file(checkpoint_file, device='cpu')
+def read_state_dict(checkpoint_file, print_global_state=False, map_location=None):
+    _, extension = os.path.splitext(checkpoint_file)
+    if extension.lower() == ".safetensors":
+        device = map_location or shared.weight_load_location or devices.get_optimal_device_name()
+        pl_sd = safetensors.torch.load_file(checkpoint_file, device=device)
     else:
-        _, extension = os.path.splitext(checkpoint_file)
-        with rich.progress.open(checkpoint_file, 'rb') as f:
-            if extension.lower() == ".safetensors":
-                buffer = f.read()
-                pl_sd = safetensors.torch.load(buffer)
-            else:
-                buffer = io.BytesIO(f.read())
-                pl_sd = torch.load(buffer, map_location='cpu')
+        pl_sd = torch.load(checkpoint_file, map_location=map_location or shared.weight_load_location)
+
+    if print_global_state and "global_step" in pl_sd:
+        print(f"Global Step: {pl_sd['global_step']}")
 
     sd = get_state_dict_from_checkpoint(pl_sd)
     return sd
@@ -261,12 +255,12 @@ def get_checkpoint_state_dict(checkpoint_info: CheckpointInfo, timer):
 
     if checkpoint_info in checkpoints_loaded:
         # use checkpoint cache
-        print(f"Loading weights from cache")
+        print(f"Loading weights [{sd_model_hash}] from cache")
         return checkpoints_loaded[checkpoint_info]
 
-    print(f"Loading weights from {checkpoint_info.filename}")
+    print(f"Loading weights [{sd_model_hash}] from {checkpoint_info.filename}")
     res = read_state_dict(checkpoint_info.filename)
-    timer.record("load weights")
+    timer.record("load weights from disk")
 
     return res
 
@@ -282,7 +276,7 @@ def load_model_weights(model, checkpoint_info: CheckpointInfo, state_dict, timer
 
     model.load_state_dict(state_dict, strict=False)
     del state_dict
-    timer.record("apply weights")
+    timer.record("apply weights to model")
 
     if shared.opts.sd_checkpoint_cache > 0:
         # cache newly loaded model
@@ -308,12 +302,15 @@ def load_model_weights(model, checkpoint_info: CheckpointInfo, state_dict, timer
         if depth_model:
             model.depth_model = depth_model
 
+        timer.record("apply half()")
+
     devices.dtype = torch.float32 if shared.cmd_opts.no_half else torch.float16
     devices.dtype_vae = torch.float32 if shared.cmd_opts.no_half or shared.cmd_opts.no_half_vae else torch.float16
     devices.dtype_unet = model.model.diffusion_model.dtype
     devices.unet_needs_upcast = shared.cmd_opts.upcast_sampling and devices.dtype == torch.float16 and devices.dtype_unet == torch.float16
 
     model.first_stage_model.to(devices.dtype_vae)
+    timer.record("apply dtype to VAE")
 
     # clean up cache if limit is reached
     while len(checkpoints_loaded) > shared.opts.sd_checkpoint_cache:
@@ -330,7 +327,7 @@ def load_model_weights(model, checkpoint_info: CheckpointInfo, state_dict, timer
     sd_vae.clear_loaded_vae()
     vae_file, vae_source = sd_vae.resolve_vae(checkpoint_info.filename)
     sd_vae.load_vae(model, vae_file, vae_source)
-    timer.record("load vae")
+    timer.record("load VAE")
 
 
 def enable_midas_autodownload():
@@ -443,7 +440,7 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None, time_taken_
     else:
         sd_model.to(shared.device)
 
-    timer.record("device move")
+    timer.record("move model to device")
 
     sd_hijack.model_hijack.hijack(sd_model)
 
@@ -497,7 +494,7 @@ def reload_model_weights(sd_model=None, info=None):
     if sd_model is None or checkpoint_config != sd_model.used_config:
         del sd_model
         checkpoints_loaded.clear()
-        load_model(checkpoint_info, already_loaded_state_dict=state_dict, time_taken_to_load_state_dict=timer.records["load weights"])
+        load_model(checkpoint_info, already_loaded_state_dict=state_dict, time_taken_to_load_state_dict=timer.records["load weights from disk"])
         return shared.sd_model
 
     try:
@@ -515,7 +512,7 @@ def reload_model_weights(sd_model=None, info=None):
 
         if not shared.cmd_opts.lowvram and not shared.cmd_opts.medvram:
             sd_model.to(devices.device)
-            timer.record("device move")
+            timer.record("move model to device")
 
     print(f"Weights loaded in {timer.summary()}.")
 

modules/shared.py

@@ -5,6 +5,7 @@ import os
 import sys
 import time
 
+from PIL import Image
 import gradio as gr
 import tqdm
 
@@ -14,7 +15,6 @@ import modules.styles
 import modules.devices as devices
 from modules import localization, extensions, script_loading, errors, ui_components, shared_items
 from modules.paths import models_path, script_path, data_path
-from rich import print
 
 
 demo = None
@@ -37,7 +37,7 @@ parser.add_argument("--no-half-vae", action='store_true', help="do not switch th
 parser.add_argument("--no-progressbar-hiding", action='store_true', help="do not hide progressbar in gradio UI (we hide it because it slows down ML if you have hardware acceleration in browser)")
 parser.add_argument("--max-batch-count", type=int, default=16, help="maximum batch count value for the UI")
 parser.add_argument("--embeddings-dir", type=str, default=os.path.join(data_path, 'embeddings'), help="embeddings directory for textual inversion (default: embeddings)")
-parser.add_argument("--textual-inversion-templates-dir", type=str, default=os.path.join(script_path, 'train/templates'), help="directory with textual inversion templates")
+parser.add_argument("--textual-inversion-templates-dir", type=str, default=os.path.join(script_path, 'textual_inversion_templates'), help="directory with textual inversion templates")
 parser.add_argument("--hypernetwork-dir", type=str, default=os.path.join(models_path, 'hypernetworks'), help="hypernetwork directory")
 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")
@@ -48,7 +48,6 @@ parser.add_argument("--always-batch-cond-uncond", action='store_true', help="dis
 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.")
-parser.add_argument("--profile", action='store_true', help="run profiler")
 parser.add_argument("--share", action='store_true', help="use share=True for gradio and make the UI accessible through their site")
 parser.add_argument("--ngrok", type=str, help="ngrok authtoken, alternative to gradio --share", default=None)
 parser.add_argument("--ngrok-region", type=str, help="The region in which ngrok should start.", default="us")
@@ -59,7 +58,7 @@ parser.add_argument("--esrgan-models-path", type=str, help="Path to directory wi
 parser.add_argument("--bsrgan-models-path", type=str, help="Path to directory with BSRGAN model file(s).", default=os.path.join(models_path, 'BSRGAN'))
 parser.add_argument("--realesrgan-models-path", type=str, help="Path to directory with RealESRGAN model file(s).", default=os.path.join(models_path, 'RealESRGAN'))
 parser.add_argument("--clip-models-path", type=str, help="Path to directory with CLIP model file(s).", default=None)
-parser.add_argument("--xformers", action='store_true', help="enable xformers for cross attention layers", default=True)
+parser.add_argument("--xformers", action='store_true', help="enable xformers for cross attention layers")
 parser.add_argument("--force-enable-xformers", action='store_true', help="enable xformers for cross attention layers regardless of whether the checking code thinks you can run it; do not make bug reports if this fails to work")
 parser.add_argument("--xformers-flash-attention", action='store_true', help="enable xformers with Flash Attention to improve reproducibility (supported for SD2.x or variant only)")
 parser.add_argument("--deepdanbooru", action='store_true', help="does not do anything")
@@ -70,10 +69,10 @@ parser.add_argument("--sub-quad-kv-chunk-size", type=int, help="kv chunk size fo
 parser.add_argument("--sub-quad-chunk-threshold", type=int, help="the percentage of VRAM threshold for the sub-quadratic cross-attention layer optimization to use chunking", default=None)
 parser.add_argument("--opt-split-attention-invokeai", action='store_true', help="force-enables InvokeAI's cross-attention layer optimization. By default, it's on when cuda is unavailable.")
 parser.add_argument("--opt-split-attention-v1", action='store_true', help="enable older version of split attention optimization that does not consume all the VRAM it can find")
-parser.add_argument("--opt-sdp-attention", action='store_true', help="enable scaled dot product cross-attention layer optimization; requires PyTorch 2.*", default=True)
+parser.add_argument("--opt-sdp-attention", action='store_true', help="enable scaled dot product cross-attention layer optimization; requires PyTorch 2.*")
 parser.add_argument("--opt-sdp-no-mem-attention", action='store_true', help="enable scaled dot product cross-attention layer optimization without memory efficient attention, makes image generation deterministic; requires PyTorch 2.*")
 parser.add_argument("--disable-opt-split-attention", action='store_true', help="force-disables cross-attention layer optimization")
-parser.add_argument("--disable-nan-check", action='store_true', help="do not check if produced images/latent spaces have nans; useful for running without a checkpoint in CI", default=True)
+parser.add_argument("--disable-nan-check", action='store_true', help="do not check if produced images/latent spaces have nans; useful for running without a checkpoint in CI")
 parser.add_argument("--use-cpu", nargs='+', help="use CPU as torch device for specified modules", default=[], type=str.lower)
 parser.add_argument("--listen", action='store_true', help="launch gradio with 0.0.0.0 as server name, allowing to respond to network requests")
 parser.add_argument("--port", type=int, help="launch gradio with given server port, you need root/admin rights for ports < 1024, defaults to 7860 if available", default=None)
@@ -90,13 +89,13 @@ parser.add_argument("--gradio-inpaint-tool", type=str, help="does not do anythin
 parser.add_argument("--opt-channelslast", action='store_true', help="change memory type for stable diffusion to channels last")
 parser.add_argument("--styles-file", type=str, help="filename to use for styles", default=os.path.join(data_path, 'styles.csv'))
 parser.add_argument("--autolaunch", action='store_true', help="open the webui URL in the system's default browser upon launch", default=False)
-parser.add_argument("--theme", type=str, help="launches the UI with light or dark theme", default='dark')
+parser.add_argument("--theme", type=str, help="launches the UI with light or dark theme", default=None)
 parser.add_argument("--use-textbox-seed", action='store_true', help="use textbox for seeds in UI (no up/down, but possible to input long seeds)", default=False)
-parser.add_argument("--disable-console-progressbars", action='store_true', help="do not output progressbars to console", default=True)
+parser.add_argument("--disable-console-progressbars", action='store_true', help="do not output progressbars to console", default=False)
 parser.add_argument("--enable-console-prompts", action='store_true', help="print prompts to console when generating with txt2img and img2img", default=False)
 parser.add_argument('--vae-path', type=str, help='Checkpoint to use as VAE; setting this argument disables all settings related to VAE', default=None)
-parser.add_argument("--disable-safe-unpickle", action='store_true', help="disable checking pytorch models for malicious code", default=True)
-parser.add_argument("--api", action='store_true', help="use api=True to launch the API together with the webui (use --nowebui instead for only the API)", default=True)
+parser.add_argument("--disable-safe-unpickle", action='store_true', help="disable checking pytorch models for malicious code", default=False)
+parser.add_argument("--api", action='store_true', help="use api=True to launch the API together with the webui (use --nowebui instead for only the API)")
 parser.add_argument("--api-auth", type=str, help='Set authentication for API like "username:password"; or comma-delimit multiple like "u1:p1,u2:p2,u3:p3"', default=None)
 parser.add_argument("--api-log", action='store_true', help="use api-log=True to enable logging of all API requests")
 parser.add_argument("--nowebui", action='store_true', help="use api=True to launch the API instead of the webui")
@@ -108,7 +107,7 @@ parser.add_argument("--cors-allow-origins-regex", type=str, help="Allowed CORS o
 parser.add_argument("--tls-keyfile", type=str, help="Partially enables TLS, requires --tls-certfile to fully function", default=None)
 parser.add_argument("--tls-certfile", type=str, help="Partially enables TLS, requires --tls-keyfile to fully function", default=None)
 parser.add_argument("--server-name", type=str, help="Sets hostname of server", default=None)
-parser.add_argument("--gradio-queue", action='store_true', help="Uses gradio queue; experimental option; breaks restart UI button", default=True)
+parser.add_argument("--gradio-queue", action='store_true', help="Uses gradio queue; experimental option; breaks restart UI button")
 parser.add_argument("--skip-version-check", action='store_true', help="Do not check versions of torch and xformers")
 parser.add_argument("--no-hashing", action='store_true', help="disable sha256 hashing of checkpoints to help loading performance", default=False)
 parser.add_argument("--no-download-sd-model", action='store_true', help="don't download SD1.5 model even if no model is found in --ckpt-dir", default=False)
@@ -153,6 +152,7 @@ devices.device, devices.device_interrogate, devices.device_gfpgan, devices.devic
     (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'])
 
 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
@@ -692,7 +692,7 @@ class TotalTQDM:
 
     def reset(self):
         self._tqdm = tqdm.tqdm(
-            desc="Total",
+            desc="Total progress",
             total=state.job_count * state.sampling_steps,
             position=1,
             file=progress_print_out
@@ -742,20 +742,3 @@ def html(filename):
             return file.read()
 
     return ""
-
-try:
-    from rich.pretty import install as pretty_install
-    from rich.traceback import install as traceback_install
-    from rich.console import Console
-    console = Console(log_time=True, log_time_format='%H:%M:%S-%f')
-    pretty_install(console=console)
-    traceback_install(console=console, extra_lines=1, width=console.width, word_wrap=False, indent_guides=False, show_locals=True, max_frames=2)
-except:
-    console = None
-    import traceback
-
-def exception():
-    if console is not None:
-        console.print_exception(show_locals=True, max_frames=10, extra_lines=1, suppress=[gr], word_wrap=False, width=min([console.width, 200]))
-    else:
-        print(traceback.format_exc(), file=sys.stderr)

modules/ui.py

@@ -8,6 +8,7 @@ import random
 import sys
 import tempfile
 import time
+import traceback
 from functools import partial, reduce
 import warnings
 
@@ -41,6 +42,8 @@ import modules.hypernetworks.ui
 from modules.generation_parameters_copypaste import image_from_url_text
 import modules.extras
 
+warnings.filterwarnings("default" if opts.show_warnings else "ignore", category=UserWarning)
+
 # 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()
 mimetypes.add_type('application/javascript', '.js')
@@ -183,18 +186,18 @@ def create_seed_inputs(target_interface):
         reuse_seed = gr.Button(reuse_symbol, elem_id=target_interface + '_reuse_seed')
 
         with gr.Group(elem_id=target_interface + '_subseed_show_box'):
-            seed_checkbox = gr.Checkbox(label='Extra', elem_id=target_interface + '_subseed_show', value=True)
+            seed_checkbox = gr.Checkbox(label='Extra', elem_id=target_interface + '_subseed_show', value=False)
 
     # Components to show/hide based on the 'Extra' checkbox
     seed_extras = []
 
-    with FormRow(visible=True, elem_id=target_interface + '_subseed_row') as seed_extra_row_1:
+    with FormRow(visible=False, elem_id=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=target_interface + '_subseed')
         subseed.style(container=False)
         random_subseed = gr.Button(random_symbol, elem_id=target_interface + '_random_subseed')
         reuse_subseed = gr.Button(reuse_symbol, elem_id=target_interface + '_reuse_subseed')
-        subseed_strength = gr.Slider(label='strength', value=0.0, minimum=0, maximum=1, step=0.01, elem_id=target_interface + '_subseed_strength')
+        subseed_strength = gr.Slider(label='Variation strength', value=0.0, minimum=0, maximum=1, step=0.01, elem_id=target_interface + '_subseed_strength')
 
     with FormRow(visible=False) as seed_extra_row_2:
         seed_extras.append(seed_extra_row_2)
@@ -473,27 +476,26 @@ def create_ui():
                     elif category == "dimensions":
                         with FormRow():
                             with gr.Column(elem_id="txt2img_column_size", scale=4):
-                                with FormRow(elem_id="txt2img_row_dimension"):
-                                    width = gr.Slider(minimum=128, maximum=2048, step=8, label="Width", value=512, elem_id="txt2img_width")
-                                    height = gr.Slider(minimum=128, maximum=2048, step=8, label="Height", value=512, elem_id="txt2img_height")
+                                width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="txt2img_width")
+                                height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="txt2img_height")
 
                             res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="txt2img_res_switch_btn")
                             if opts.dimensions_and_batch_together:
                                 with gr.Column(elem_id="txt2img_column_batch"):
-                                    with FormRow(elem_id="txt2img_row_batch"):
-                                        batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="txt2img_batch_count")
-                                        batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="txt2img_batch_size")
+                                    batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="txt2img_batch_count")
+                                    batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="txt2img_batch_size")
 
+                    elif category == "cfg":
+                        cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0, elem_id="txt2img_cfg_scale")
 
                     elif category == "seed":
                         seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs('txt2img')
 
                     elif category == "checkboxes":
                         with FormRow(elem_id="txt2img_checkboxes", variant="compact"):
-                            cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0, elem_id="txt2img_cfg_scale")
                             restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="txt2img_restore_faces")
                             tiling = gr.Checkbox(label='Tiling', value=False, elem_id="txt2img_tiling")
-                            enable_hr = gr.Checkbox(label='Hi-res tiling', value=False, elem_id="txt2img_enable_hr")
+                            enable_hr = gr.Checkbox(label='Hires. fix', value=False, elem_id="txt2img_enable_hr")
                             hr_final_resolution = FormHTML(value="", elem_id="txtimg_hr_finalres", label="Upscaled resolution", interactive=False)
 
                     elif category == "hires_fix":
@@ -743,7 +745,7 @@ def create_ui():
                     )
 
                 with FormRow():
-                    resize_mode = gr.Radio(label="Resize mode", elem_id="resize_mode", choices=["Just resize", "Crop and resize", "Resize and fill", "Latent upscale"], type="index", value="Just resize")
+                    resize_mode = gr.Radio(label="Resize mode", elem_id="resize_mode", choices=["Just resize", "Crop and resize", "Resize and fill", "Just resize (latent upscale)"], type="index", value="Just resize")
 
                 for category in ordered_ui_categories():
                     if category == "sampler":
@@ -752,16 +754,14 @@ def create_ui():
                     elif category == "dimensions":
                         with FormRow():
                             with gr.Column(elem_id="img2img_column_size", scale=4):
-                                with FormRow(elem_id="img2img_row_size"):
-                                    width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="img2img_width")
-                                    height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="img2img_height")
+                                width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="img2img_width")
+                                height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="img2img_height")
 
                             res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="img2img_res_switch_btn")
                             if opts.dimensions_and_batch_together:
                                 with gr.Column(elem_id="img2img_column_batch"):
-                                    with FormRow(elem_id="img2img_row_batch"):
-                                        batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="img2img_batch_count")
-                                        batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="img2img_batch_size")
+                                    batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="img2img_batch_count")
+                                    batch_size = gr.Slider(minimum=1, maximum=8, step=1, label='Batch size', value=1, elem_id="img2img_batch_size")
 
                     elif category == "cfg":
                         with FormGroup():
@@ -1006,6 +1006,48 @@ def create_ui():
         }
         return interp_descriptions[value]
 
+    with gr.Blocks(analytics_enabled=False) as modelmerger_interface:
+        with gr.Row().style(equal_height=False):
+            with gr.Column(variant='compact'):
+                interp_description = gr.HTML(value=update_interp_description("Weighted sum"), elem_id="modelmerger_interp_description")
+
+                with FormRow(elem_id="modelmerger_models"):
+                    primary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_primary_model_name", label="Primary model (A)")
+                    create_refresh_button(primary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_A")
+
+                    secondary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_secondary_model_name", label="Secondary model (B)")
+                    create_refresh_button(secondary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_B")
+
+                    tertiary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_tertiary_model_name", label="Tertiary model (C)")
+                    create_refresh_button(tertiary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_C")
+
+                custom_name = gr.Textbox(label="Custom Name (Optional)", elem_id="modelmerger_custom_name")
+                interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Multiplier (M) - set to 0 to get model A', value=0.3, elem_id="modelmerger_interp_amount")
+                interp_method = gr.Radio(choices=["No interpolation", "Weighted sum", "Add difference"], value="Weighted sum", label="Interpolation Method", elem_id="modelmerger_interp_method")
+                interp_method.change(fn=update_interp_description, inputs=[interp_method], outputs=[interp_description])
+
+                with FormRow():
+                    checkpoint_format = gr.Radio(choices=["ckpt", "safetensors"], value="ckpt", label="Checkpoint format", elem_id="modelmerger_checkpoint_format")
+                    save_as_half = gr.Checkbox(value=False, label="Save as float16", elem_id="modelmerger_save_as_half")
+
+                with FormRow():
+                    with gr.Column():
+                        config_source = gr.Radio(choices=["A, B or C", "B", "C", "Don't"], value="A, B or C", label="Copy config from", type="index", elem_id="modelmerger_config_method")
+
+                    with gr.Column():
+                        with FormRow():
+                            bake_in_vae = gr.Dropdown(choices=["None"] + list(sd_vae.vae_dict), value="None", label="Bake in VAE", elem_id="modelmerger_bake_in_vae")
+                            create_refresh_button(bake_in_vae, sd_vae.refresh_vae_list, lambda: {"choices": ["None"] + list(sd_vae.vae_dict)}, "modelmerger_refresh_bake_in_vae")
+
+                with FormRow():
+                    discard_weights = gr.Textbox(value="", label="Discard weights with matching name", elem_id="modelmerger_discard_weights")
+
+                with gr.Row():
+                    modelmerger_merge = gr.Button(elem_id="modelmerger_merge", value="Merge", variant='primary')
+
+            with gr.Column(variant='compact', elem_id="modelmerger_results_container"):
+                with gr.Group(elem_id="modelmerger_results_panel"):
+                    modelmerger_result = gr.HTML(elem_id="modelmerger_result", show_label=False)
 
     with gr.Blocks(analytics_enabled=False) as train_interface:
         with gr.Row().style(equal_height=False):
@@ -1014,49 +1056,6 @@ def create_ui():
         with gr.Row(variant="compact").style(equal_height=False):
             with gr.Tabs(elem_id="train_tabs"):
 
-                with gr.Tab(label="Merge models") as modelmerger_interface:
-                    with gr.Row().style(equal_height=False):
-                        with gr.Column(variant='compact'):
-                            interp_description = gr.HTML(value=update_interp_description("Weighted sum"), elem_id="modelmerger_interp_description")
-
-                            with FormRow(elem_id="modelmerger_models"):
-                                primary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_primary_model_name", label="Primary model (A)")
-                                create_refresh_button(primary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_A")
-
-                                secondary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_secondary_model_name", label="Secondary model (B)")
-                                create_refresh_button(secondary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_B")
-
-                                tertiary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_tertiary_model_name", label="Tertiary model (C)")
-                                create_refresh_button(tertiary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_C")
-
-                            custom_name = gr.Textbox(label="Custom Name (Optional)", elem_id="modelmerger_custom_name")
-                            interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Multiplier (M) - set to 0 to get model A', value=0.3, elem_id="modelmerger_interp_amount")
-                            interp_method = gr.Radio(choices=["No interpolation", "Weighted sum", "Add difference"], value="Weighted sum", label="Interpolation Method", elem_id="modelmerger_interp_method")
-                            interp_method.change(fn=update_interp_description, inputs=[interp_method], outputs=[interp_description])
-
-                            with FormRow():
-                                checkpoint_format = gr.Radio(choices=["ckpt", "safetensors"], value="ckpt", label="Checkpoint format", elem_id="modelmerger_checkpoint_format")
-                                save_as_half = gr.Checkbox(value=False, label="Save as float16", elem_id="modelmerger_save_as_half")
-
-                            with FormRow():
-                                with gr.Column():
-                                    config_source = gr.Radio(choices=["A, B or C", "B", "C", "Don't"], value="A, B or C", label="Copy config from", type="index", elem_id="modelmerger_config_method")
-
-                                with gr.Column():
-                                    with FormRow():
-                                        bake_in_vae = gr.Dropdown(choices=["None"] + list(sd_vae.vae_dict), value="None", label="Bake in VAE", elem_id="modelmerger_bake_in_vae")
-                                        create_refresh_button(bake_in_vae, sd_vae.refresh_vae_list, lambda: {"choices": ["None"] + list(sd_vae.vae_dict)}, "modelmerger_refresh_bake_in_vae")
-
-                            with FormRow():
-                                discard_weights = gr.Textbox(value="", label="Discard weights with matching name", elem_id="modelmerger_discard_weights")
-
-                            with gr.Row():
-                                modelmerger_merge = gr.Button(elem_id="modelmerger_merge", value="Merge", variant='primary')
-
-                        with gr.Column(variant='compact', elem_id="modelmerger_results_container"):
-                            with gr.Group(elem_id="modelmerger_results_panel"):
-                                modelmerger_result = gr.HTML(elem_id="modelmerger_result", show_label=False)
-
                 with gr.Tab(label="Create embedding"):
                     new_embedding_name = gr.Textbox(label="Name", elem_id="train_new_embedding_name")
                     initialization_text = gr.Textbox(label="Initialization text", value="*", elem_id="train_initialization_text")
@@ -1443,7 +1442,7 @@ def create_ui():
             with gr.Column(scale=6):
                 settings_submit = gr.Button(value="Apply settings", variant='primary', elem_id="settings_submit")
             with gr.Column():
-                restart_gradio = gr.Button(value='Reload UI', variant='primary', elem_id="settings_restart_gradio", visible=False)
+                restart_gradio = gr.Button(value='Reload UI', variant='primary', elem_id="settings_restart_gradio")
 
         result = gr.HTML(elem_id="settings_result")
 
@@ -1534,11 +1533,11 @@ def create_ui():
         )
 
     interfaces = [
-        (txt2img_interface, "From Text", "txt2img"),
-        (img2img_interface, "From Image", "img2img"),
-        (extras_interface, "Process", "extras"),
-        (pnginfo_interface, "Image Info", "pnginfo"),
-        # (modelmerger_interface, "Checkpoint Merger", "modelmerger"),
+        (txt2img_interface, "txt2img", "txt2img"),
+        (img2img_interface, "img2img", "img2img"),
+        (extras_interface, "Extras", "extras"),
+        (pnginfo_interface, "PNG Info", "pnginfo"),
+        (modelmerger_interface, "Checkpoint Merger", "modelmerger"),
         (train_interface, "Train", "ti"),
     ]
 
@@ -1636,7 +1635,7 @@ def create_ui():
                 results = modules.extras.run_modelmerger(*args)
             except Exception as e:
                 print("Error loading/saving model file:", file=sys.stderr)
-                shared.exception()
+                print(traceback.format_exc(), file=sys.stderr)
                 modules.sd_models.list_models()  # to remove the potentially missing models from the list
                 return [*[gr.Dropdown.update(choices=modules.sd_models.checkpoint_tiles()) for _ in range(4)], f"Error merging checkpoints: {e}"]
             return results
@@ -1680,7 +1679,7 @@ def create_ui():
     except Exception:
         error_loading = True
         print("Error loading settings:", file=sys.stderr)
-        shared.exception()
+        print(traceback.format_exc(), file=sys.stderr)
 
     def loadsave(path, x):
         def apply_field(obj, field, condition=None, init_field=None):
@@ -1782,9 +1781,11 @@ if not hasattr(shared, 'GradioTemplateResponseOriginal'):
 
 def versions_html():
     import torch
-    from launch import commit_hash
+    import launch
 
     python_version = ".".join([str(x) for x in sys.version_info[0:3]])
+    commit = launch.commit_hash()
+    short_commit = commit[0:8]
 
     if shared.xformers_available:
         import xformers
@@ -1792,11 +1793,6 @@ def versions_html():
     else:
         xformers_version = "N/A"
 
-    try:
-        torch_version = torch.__long_version__
-    except:
-        torch_version = torch.__version__
-
     return f"""
 python: <span title="{sys.version}">{python_version}</span>
  • 
@@ -1806,7 +1802,7 @@ xformers: {xformers_version}
  • 
 gradio: {gr.__version__}
  • 
-commit: <a href="https://github.com/AUTOMATIC1111/stable-diffusion-webui/commit/{commit_hash()}">{commit_hash()[0:8]}</a>
+commit: <a href="https://github.com/AUTOMATIC1111/stable-diffusion-webui/commit/{commit}">{short_commit}</a>
  • 
 checkpoint: <a id="sd_checkpoint_hash">N/A</a>
 """

requirements.txt

@@ -1,46 +1,32 @@
-accelerate
-aenum
-basicsr
-bitsandbytes
 blendmodes
-clean-fid
-colormap
-diffusers
-easydev
-einops
-extcolors
-facexlib
-fastapi
-filetype
-font-roboto
+accelerate
+basicsr
 fonts
+font-roboto
 gfpgan
-GitPython
-gradio
-inflection
+gradio==3.16.2
 invisible-watermark
-jsonmerge
-kornia
-lark
-mediapipe
 numpy
 omegaconf
 opencv-contrib-python
+requests
 piexif
 Pillow
-psutil
-pyngrok
-pytorch_lightning
+pytorch_lightning==1.7.7
 realesrgan
-requests
-resize-right
-rich
-safetensors
-scikit-image
-timm
-toml
+scikit-image>=0.19
+timm==0.4.12
+transformers==4.25.1
 torch
+einops
+jsonmerge
+clean-fid
+resize-right
 torchdiffeq
+kornia
+lark
+inflection
+GitPython
 torchsde
-transformers
-voluptuous
+safetensors
+psutil

requirements_versions.txt

@@ -1,17 +1,30 @@
-accelerate==0.17.1
-clip_interrogator==0.6.0
-diffusers==0.14.0
-einops==0.4.1
-fastapi==0.94.0
+blendmodes==2022
+transformers==4.25.1
+accelerate==0.12.0
+basicsr==1.4.2
 gfpgan==1.3.8
-GitPython==3.1.31
 gradio==3.16.2
-numexpr==2.8.4
-omegaconf==2.3.0
-pandas==1.5.3
+numpy==1.23.3
 Pillow==9.4.0
-protobuf==3.20.3
-pytorch_lightning==1.9.4
 realesrgan==0.3.0
-safetensors==0.3.0
-transformers==4.27.1
+torch
+omegaconf==2.2.3
+pytorch_lightning==1.7.6
+scikit-image==0.19.2
+fonts
+font-roboto
+timm==0.6.7
+piexif==1.1.3
+einops==0.4.1
+jsonmerge==1.8.0
+clean-fid==0.1.29
+resize-right==0.0.2
+torchdiffeq==0.2.3
+kornia==0.6.7
+lark==1.1.2
+inflection==0.5.1
+GitPython==3.1.30
+torchsde==0.2.5
+safetensors==0.2.7
+httpcore<=0.15
+fastapi==0.94.0

scripts/postprocessing_upscale.py

@@ -20,7 +20,6 @@ class ScriptPostprocessingUpscale(scripts_postprocessing.ScriptPostprocessing):
         with gr.Tabs(elem_id="extras_resize_mode"):
             with gr.TabItem('Scale by', elem_id="extras_scale_by_tab") as tab_scale_by:
                 upscaling_resize = gr.Slider(minimum=1.0, maximum=8.0, step=0.05, label="Resize", value=4, elem_id="extras_upscaling_resize")
-                extras_upscaler_1 = gr.Dropdown(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name)
 
             with gr.TabItem('Scale to', elem_id="extras_scale_to_tab") as tab_scale_to:
                 with FormRow():
@@ -28,6 +27,9 @@ class ScriptPostprocessingUpscale(scripts_postprocessing.ScriptPostprocessing):
                     upscaling_resize_h = gr.Number(label="Height", value=512, precision=0, elem_id="extras_upscaling_resize_h")
                     upscaling_crop = gr.Checkbox(label='Crop to fit', value=True, elem_id="extras_upscaling_crop")
 
+        with FormRow():
+            extras_upscaler_1 = gr.Dropdown(label='Upscaler 1', elem_id="extras_upscaler_1", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name)
+
         with FormRow():
             extras_upscaler_2 = gr.Dropdown(label='Upscaler 2', elem_id="extras_upscaler_2", choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name)
             extras_upscaler_2_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Upscaler 2 visibility", value=0.0, elem_id="extras_upscaler_2_visibility")

style.css

@@ -58,6 +58,9 @@
     margin-right: 0;
 }
 
+.performance .vram {
+}
+
 #txt2img_generate, #img2img_generate {
     min-height: 4.5em;
 }
@@ -302,6 +305,9 @@ input[type="range"]{
   margin-bottom: -0.75em;
 }
 
+#txt2img_negative_prompt, #img2img_negative_prompt{
+}
+
 /* gradio 3.8 adds opacity to progressbar which makes it blink; disable it here */
 .transition.opacity-20 {
   opacity: 1 !important;
@@ -804,6 +810,9 @@ footer {
     overflow: visible;
 }
 
+.gr-compact > *{
+}
+
 .gr-compact .gr-block, .gr-compact .gr-form{
     border: none;
     box-shadow: none;
@@ -822,6 +831,9 @@ footer {
     border: none;
 }
 
+[id*='img2img_copy_to_'] > button {
+}
+
 [id*='img2img_label_copy_to_'] {
     font-size: 1.0em;
     font-weight: bold;

webui.py

@@ -4,12 +4,10 @@ import time
 import importlib
 import signal
 import re
-import warnings
 from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.middleware.gzip import GZipMiddleware
 from packaging import version
-from rich import print
 
 import logging
 logging.getLogger("xformers").addFilter(lambda record: 'A matching Triton is not available' not in record.getMessage())
@@ -19,12 +17,13 @@ from modules import paths, timer, import_hook, errors
 startup_timer = timer.Timer()
 
 import torch
-import pytorch_lightning # pytorch_lightning should be imported after torch, but it re-enables warnings on import so import once to disable them
-warnings.filterwarnings(action="ignore", category=DeprecationWarning, module="pytorch_lightning")
 startup_timer.record("import torch")
 
 import gradio
+startup_timer.record("import gradio")
+
 import ldm.modules.encoders.modules
+startup_timer.record("import ldm")
 
 from modules import extra_networks, ui_extra_networks_checkpoints
 from modules import extra_networks_hypernet, ui_extra_networks_hypernets, ui_extra_networks_textual_inversion
@@ -35,7 +34,7 @@ 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, devices, sd_samplers, upscaler, extensions, ui_tempdir, ui_extra_networks
+from modules import shared, devices, sd_samplers, upscaler, extensions, localization, ui_tempdir, ui_extra_networks
 import modules.codeformer_model as codeformer
 import modules.face_restoration
 import modules.gfpgan_model as gfpgan
@@ -56,7 +55,7 @@ from modules import modelloader
 from modules.shared import cmd_opts
 import modules.hypernetworks.hypernetwork
 
-startup_timer.record("import libraries")
+startup_timer.record("other imports")
 
 
 if cmd_opts.server_name:
@@ -65,18 +64,42 @@ else:
     server_name = "0.0.0.0" if cmd_opts.listen else None
 
 
+def check_versions():
+    if shared.cmd_opts.skip_version_check:
+        return
+
+    expected_torch_version = "1.13.1"
+
+    if version.parse(torch.__version__) < version.parse(expected_torch_version):
+        errors.print_error_explanation(f"""
+You are running torch {torch.__version__}.
+The program is tested to work with torch {expected_torch_version}.
+To reinstall the desired version, run with commandline flag --reinstall-torch.
+Beware that this will cause a lot of large files to be downloaded, as well as
+there are reports of issues with training tab on the latest version.
+
+Use --skip-version-check commandline argument to disable this check.
+        """.strip())
+
+    expected_xformers_version = "0.0.16rc425"
+    if shared.xformers_available:
+        import xformers
+
+        if version.parse(xformers.__version__) < version.parse(expected_xformers_version):
+            errors.print_error_explanation(f"""
+You are running xformers {xformers.__version__}.
+The program is tested to work with xformers {expected_xformers_version}.
+To reinstall the desired version, run with commandline flag --reinstall-xformers.
+
+Use --skip-version-check commandline argument to disable this check.
+            """.strip())
+
+
 def initialize():
-    if torch.cuda.is_available():
-        if torch.version.cuda: cuda_version = f'CUDA {torch.version.cuda} cuDNN {torch.backends.cudnn.version()}'
-        elif torch.version.hip: cuda_version = f'HIP {torch.version.hip}'
-        else: cuda_version = ''
-        print(f'Torch {getattr(torch, "__long_version__", torch.__version__)} {cuda_version}')
-        for device in [torch.cuda.device(i) for i in range(torch.cuda.device_count())]:
-            print(f'GPU {torch.cuda.get_device_name(device)} VRAM {round(torch.cuda.get_device_properties(device).total_memory / 1024 / 1024)} Arch {torch.cuda.get_device_capability(device)} Cores {torch.cuda.get_device_properties(device).multi_processor_count}')
-    else:
-        print(f'Torch {getattr(torch, "__long_version__", torch.__version__)} running on CPU')
+    check_versions()
 
     extensions.list_extensions()
+    localization.list_localizations(cmd_opts.localizations_dir)
     startup_timer.record("list extensions")
 
     if cmd_opts.ui_debug_mode:
@@ -86,7 +109,7 @@ def initialize():
 
     modelloader.cleanup_models()
     modules.sd_models.setup_model()
-    startup_timer.record("list models")
+    startup_timer.record("list SD models")
 
     codeformer.setup_model(cmd_opts.codeformer_models_path)
     startup_timer.record("setup codeformer")
@@ -109,6 +132,18 @@ def initialize():
     modules.textual_inversion.textual_inversion.list_textual_inversion_templates()
     startup_timer.record("refresh textual inversion templates")
 
+    try:
+        modules.sd_models.load_model()
+    except Exception as e:
+        errors.display(e, "loading stable diffusion model")
+        print("", file=sys.stderr)
+        print("Stable diffusion model failed to load, exiting", file=sys.stderr)
+        exit(1)
+    startup_timer.record("load SD checkpoint")
+
+    shared.opts.data["sd_model_checkpoint"] = shared.sd_model.sd_checkpoint_info.title
+
+    shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights()))
     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("temp_dir", ui_tempdir.on_tmpdir_changed)
@@ -141,32 +176,16 @@ def initialize():
         startup_timer.record("TLS")
 
     # make the program just exit at ctrl+c without waiting for anything
-    def sigint_handler(_sig, _frame):
-        print('Exiting')
+    def sigint_handler(sig, frame):
+        print(f'Interrupted with signal {sig} in {frame}')
         os._exit(0)
 
     signal.signal(signal.SIGINT, sigint_handler)
 
 
-def load_model():
-    shared.state.begin()
-    shared.state.job = 'load model'
-    try:
-        modules.sd_models.load_model()
-    except Exception as e:
-        errors.display(e, "loading stable diffusion model")
-        print("", file=sys.stderr)
-        print("Stable diffusion model failed to load, exiting", file=sys.stderr)
-        exit(1)
-    shared.opts.data["sd_model_checkpoint"] = shared.sd_model.sd_checkpoint_info.title
-    shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights()))
-    shared.state.end()
-    startup_timer.record("load checkpoint")
-
-
 def setup_middleware(app):
     app.middleware_stack = None # reset current middleware to allow modifying user provided list
-    app.add_middleware(GZipMiddleware, minimum_size=1024)
+    app.add_middleware(GZipMiddleware, minimum_size=1000)
     if cmd_opts.cors_allow_origins and cmd_opts.cors_allow_origins_regex:
         app.add_middleware(CORSMiddleware, allow_origins=cmd_opts.cors_allow_origins.split(','), allow_origin_regex=cmd_opts.cors_allow_origins_regex, allow_methods=['*'], allow_credentials=True, allow_headers=['*'])
     elif cmd_opts.cors_allow_origins:
@@ -182,9 +201,19 @@ def create_api(app):
     return api
 
 
+def wait_on_server(demo=None):
+    while 1:
+        time.sleep(0.5)
+        if shared.state.need_restart:
+            shared.state.need_restart = False
+            time.sleep(0.5)
+            demo.close()
+            time.sleep(0.5)
+            break
+
+
 def api_only():
     initialize()
-    load_model()
 
     app = FastAPI()
     setup_middleware(app)
@@ -200,71 +229,105 @@ def webui():
     launch_api = cmd_opts.api
     initialize()
 
-    if shared.opts.clean_temp_dir_at_start:
-        ui_tempdir.cleanup_tmpdr()
-        startup_timer.record("cleanup temp dir")
+    while 1:
+        if shared.opts.clean_temp_dir_at_start:
+            ui_tempdir.cleanup_tmpdr()
+            startup_timer.record("cleanup temp dir")
 
-    modules.script_callbacks.before_ui_callback()
-    startup_timer.record("scripts before_ui_callback")
+        modules.script_callbacks.before_ui_callback()
+        startup_timer.record("scripts before_ui_callback")
 
-    shared.demo = modules.ui.create_ui()
-    startup_timer.record("create ui")
+        shared.demo = modules.ui.create_ui()
+        startup_timer.record("create ui")
 
-    if cmd_opts.gradio_queue:
-        shared.demo.queue(16)
+        if cmd_opts.gradio_queue:
+            shared.demo.queue(64)
 
-    gradio_auth_creds = []
-    if cmd_opts.gradio_auth:
-        gradio_auth_creds += [x.strip() for x in cmd_opts.gradio_auth.strip('"').replace('\n', '').split(',') if x.strip()]
-    if cmd_opts.gradio_auth_path:
-        with open(cmd_opts.gradio_auth_path, 'r', encoding="utf8") as file:
-            for line in file.readlines():
-                gradio_auth_creds += [x.strip() for x in line.split(',') if x.strip()]
+        gradio_auth_creds = []
+        if cmd_opts.gradio_auth:
+            gradio_auth_creds += [x.strip() for x in cmd_opts.gradio_auth.strip('"').replace('\n', '').split(',') if x.strip()]
+        if cmd_opts.gradio_auth_path:
+            with open(cmd_opts.gradio_auth_path, 'r', encoding="utf8") as file:
+                for line in file.readlines():
+                    gradio_auth_creds += [x.strip() for x in line.split(',') if x.strip()]
 
-    app, _local_url, _share_url = shared.demo.launch(
-        share=cmd_opts.share,
-        server_name=server_name,
-        server_port=cmd_opts.port,
-        ssl_keyfile=cmd_opts.tls_keyfile,
-        ssl_certfile=cmd_opts.tls_certfile,
-        debug=cmd_opts.gradio_debug,
-        auth=[tuple(cred.split(':')) for cred in gradio_auth_creds] if gradio_auth_creds else None,
-        inbrowser=cmd_opts.autolaunch,
-        prevent_thread_lock=True,
-        favicon_path='automatic.ico',
-    )
-    for dep in shared.demo.dependencies:
-        dep['show_progress'] = False  # disable gradio css animation on component update
+        app, local_url, share_url = shared.demo.launch(
+            share=cmd_opts.share,
+            server_name=server_name,
+            server_port=cmd_opts.port,
+            ssl_keyfile=cmd_opts.tls_keyfile,
+            ssl_certfile=cmd_opts.tls_certfile,
+            debug=cmd_opts.gradio_debug,
+            auth=[tuple(cred.split(':')) for cred in gradio_auth_creds] if gradio_auth_creds else None,
+            inbrowser=cmd_opts.autolaunch,
+            prevent_thread_lock=True
+        )
+        # after initial launch, disable --autolaunch for subsequent restarts
+        cmd_opts.autolaunch = False
 
-    # app is instance of FastAPI server
-    # shared.demo.server is instance of gradio class which inherits from uvicorn.Server
-    # shared.demo.config is instance of uvicorn.Config
-    # shared.demo.app is instance of ASGIApp
+        startup_timer.record("gradio launch")
 
-    cmd_opts.autolaunch = False
+        # gradio uses a very open CORS policy via app.user_middleware, which makes it possible for
+        # an attacker to trick the user into opening a malicious HTML page, which makes a request to the
+        # running web ui and do whatever the attacker wants, including installing an extension and
+        # running its code. We disable this here. Suggested by RyotaK.
+        app.user_middleware = [x for x in app.user_middleware if x.cls.__name__ != 'CORSMiddleware']
 
-    startup_timer.record("gradio launch")
+        setup_middleware(app)
 
-    app.user_middleware = [x for x in app.user_middleware if x.cls.__name__ != 'CORSMiddleware']
+        modules.progress.setup_progress_api(app)
 
-    setup_middleware(app)
+        if launch_api:
+            create_api(app)
 
-    modules.progress.setup_progress_api(app)
+        ui_extra_networks.add_pages_to_demo(app)
 
-    if launch_api:
-        create_api(app)
+        modules.script_callbacks.app_started_callback(shared.demo, app)
+        startup_timer.record("scripts app_started_callback")
 
-    ui_extra_networks.add_pages_to_demo(app)
+        print(f"Startup time: {startup_timer.summary()}.")
 
-    modules.script_callbacks.app_started_callback(shared.demo, app)
-    startup_timer.record("scripts app_started_callback")
+        wait_on_server(shared.demo)
+        print('Restarting UI...')
 
-    load_model()
+        startup_timer.reset()
 
-    print(f"Startup time: {startup_timer.summary()}.")
+        sd_samplers.set_samplers()
 
-    while True:
-        time.sleep(0.1)
+        modules.script_callbacks.script_unloaded_callback()
+        extensions.list_extensions()
+        startup_timer.record("list extensions")
+
+        localization.list_localizations(cmd_opts.localizations_dir)
+
+        modelloader.forbid_loaded_nonbuiltin_upscalers()
+        modules.scripts.reload_scripts()
+        startup_timer.record("load scripts")
+
+        modules.script_callbacks.model_loaded_callback(shared.sd_model)
+        startup_timer.record("model loaded callback")
+
+        modelloader.load_upscalers()
+        startup_timer.record("load upscalers")
+
+        for module in [module for name, module in sys.modules.items() if name.startswith("modules.ui")]:
+            importlib.reload(module)
+        startup_timer.record("reload script modules")
+
+        modules.sd_models.list_models()
+        startup_timer.record("list SD models")
+
+        shared.reload_hypernetworks()
+        startup_timer.record("reload hypernetworks")
+
+        ui_extra_networks.intialize()
+        ui_extra_networks.register_page(ui_extra_networks_textual_inversion.ExtraNetworksPageTextualInversion())
+        ui_extra_networks.register_page(ui_extra_networks_hypernets.ExtraNetworksPageHypernetworks())
+        ui_extra_networks.register_page(ui_extra_networks_checkpoints.ExtraNetworksPageCheckpoints())
+
+        extra_networks.initialize()
+        extra_networks.register_extra_network(extra_networks_hypernet.ExtraNetworkHypernet())
+        startup_timer.record("initialize extra networks")
 
 
 if __name__ == "__main__":