From 79d261b7d47e75a93f38e04608508102dded6a6c Mon Sep 17 00:00:00 2001 From: high_byte Date: Wed, 15 Mar 2023 19:44:30 +0200 Subject: disable gradio analytics globally --- launch.py | 1 + 1 file changed, 1 insertion(+) (limited to 'launch.py') diff --git a/launch.py b/launch.py index 0868f8a9..2b2d3128 100644 --- a/launch.py +++ b/launch.py @@ -16,6 +16,7 @@ index_url = os.environ.get('INDEX_URL', "") stored_commit_hash = None skip_install = False +os.environ['GRADIO_ANALYTICS_ENABLED'] = 'False' def check_python_version(): is_windows = platform.system() == "Windows" -- cgit v1.2.3 From b9a66b02d0b8ca1c3364d9410198530682fd2f6c Mon Sep 17 00:00:00 2001 From: nonnonstop <42905588+nonnonstop@users.noreply.github.com> Date: Sun, 19 Mar 2023 01:17:04 +0900 Subject: Fix problem of install.py when data-dir is specified --- launch.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) (limited to 'launch.py') diff --git a/launch.py b/launch.py index b943fed2..95311d33 100644 --- a/launch.py +++ b/launch.py @@ -14,7 +14,7 @@ parser.add_argument("--data-dir", type=str, default=os.path.dirname(os.path.real args, _ = parser.parse_known_args(sys.argv) script_path = os.path.dirname(__file__) -data_path = os.getcwd() +data_path = args.data_dir dir_repos = "repositories" dir_extensions = "extensions" @@ -231,7 +231,7 @@ def run_extensions_installers(settings_file): return for dirname_extension in list_extensions(settings_file): - run_extension_installer(os.path.join(dir_extensions, dirname_extension)) + run_extension_installer(os.path.join(data_path, dir_extensions, dirname_extension)) def prepare_environment(): -- cgit v1.2.3 From c1294d849a50b9b2995aa257adbb918837c4b384 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 25 Mar 2023 12:21:18 +0300 Subject: make it possible for user to enable gradio analytics by setting GRADIO_ANALYTICS_ENABLED=True --- launch.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) (limited to 'launch.py') diff --git a/launch.py b/launch.py index 0397ca06..5f836d22 100644 --- a/launch.py +++ b/launch.py @@ -24,7 +24,8 @@ index_url = os.environ.get('INDEX_URL', "") stored_commit_hash = None skip_install = False -os.environ['GRADIO_ANALYTICS_ENABLED'] = 'False' +if 'GRADIO_ANALYTICS_ENABLED' not in os.environ: + os.environ['GRADIO_ANALYTICS_ENABLED'] = 'False' def check_python_version(): is_windows = platform.system() == "Windows" -- cgit v1.2.3 From 8c801362b43013a628c58f0c1276e076ee48227d Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sat, 25 Mar 2023 16:05:12 +0300 Subject: split commandline args into its own file make launch.py use the same command line argument parser as the main program --- launch.py | 77 ++---- modules/cmd_args.py | 673 +--------------------------------------------- modules/extensions.py | 16 +- modules/paths.py | 11 +- modules/paths_internal.py | 22 ++ modules/shared.py | 107 +------- 6 files changed, 73 insertions(+), 833 deletions(-) create mode 100644 modules/paths_internal.py (limited to 'launch.py') diff --git a/launch.py b/launch.py index 5f836d22..c41ae82d 100644 --- a/launch.py +++ b/launch.py @@ -5,28 +5,27 @@ import sys import importlib.util import shlex import platform -import argparse import json -parser = argparse.ArgumentParser(add_help=False) -parser.add_argument("--ui-settings-file", type=str, default='config.json') -parser.add_argument("--data-dir", type=str, default=os.path.dirname(os.path.realpath(__file__))) -args, _ = parser.parse_known_args(sys.argv) +from modules import cmd_args +from modules.paths_internal import script_path, extensions_dir -script_path = os.path.dirname(__file__) -data_path = args.data_dir +commandline_args = os.environ.get('COMMANDLINE_ARGS', "") +sys.argv += shlex.split(commandline_args) + +args, _ = cmd_args.parser.parse_known_args() -dir_repos = "repositories" -dir_extensions = "extensions" python = sys.executable git = os.environ.get('GIT', "git") index_url = os.environ.get('INDEX_URL', "") stored_commit_hash = None skip_install = False +dir_repos = "repositories" if 'GRADIO_ANALYTICS_ENABLED' not in os.environ: os.environ['GRADIO_ANALYTICS_ENABLED'] = 'False' + def check_python_version(): is_windows = platform.system() == "Windows" major = sys.version_info.major @@ -72,23 +71,6 @@ def commit_hash(): return stored_commit_hash -def extract_arg(args, name): - return [x for x in args if x != name], name in args - - -def extract_opt(args, name): - opt = None - is_present = False - if name in args: - is_present = True - idx = args.index(name) - del args[idx] - if idx < len(args) and args[idx][0] != "-": - opt = args[idx] - del args[idx] - return args, is_present, opt - - def run(command, desc=None, errdesc=None, custom_env=None, live=False): if desc is not None: print(desc) @@ -225,15 +207,15 @@ def list_extensions(settings_file): disabled_extensions = set(settings.get('disabled_extensions', [])) - return [x for x in os.listdir(os.path.join(data_path, dir_extensions)) if x not in disabled_extensions] + return [x for x in os.listdir(extensions_dir) if x not in disabled_extensions] def run_extensions_installers(settings_file): - if not os.path.isdir(dir_extensions): + if not os.path.isdir(extensions_dir): return for dirname_extension in list_extensions(settings_file): - run_extension_installer(os.path.join(data_path, dir_extensions, dirname_extension)) + run_extension_installer(os.path.join(extensions_dir, dirname_extension)) def prepare_environment(): @@ -241,7 +223,6 @@ def prepare_environment(): 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") @@ -260,21 +241,7 @@ def prepare_environment(): codeformer_commit_hash = os.environ.get('CODEFORMER_COMMIT_HASH', "c5b4593074ba6214284d6acd5f1719b6c5d739af") blip_commit_hash = os.environ.get('BLIP_COMMIT_HASH', "48211a1594f1321b00f14c9f7a5b4813144b2fb9") - sys.argv += shlex.split(commandline_args) - - 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: + if not args.skip_python_version_check: check_python_version() commit = commit_hash() @@ -282,10 +249,10 @@ def prepare_environment(): print(f"Python {sys.version}") print(f"Commit hash: {commit}") - if reinstall_torch or not is_installed("torch") or not is_installed("torchvision"): + if args.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: + if not args.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"): @@ -297,7 +264,7 @@ 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 (not is_installed("xformers") or args.reinstall_xformers) and args.xformers: if platform.system() == "Windows": if platform.python_version().startswith("3.10"): run_pip(f"install -U -I --no-deps {xformers_package}", "xformers") @@ -309,7 +276,7 @@ def prepare_environment(): elif platform.system() == "Linux": run_pip(f"install {xformers_package}", "xformers") - if not is_installed("pyngrok") and ngrok: + if not is_installed("pyngrok") and args.ngrok: run_pip("install pyngrok", "ngrok") os.makedirs(os.path.join(script_path, dir_repos), exist_ok=True) @@ -329,18 +296,18 @@ def prepare_environment(): run_extensions_installers(settings_file=args.ui_settings_file) - if update_check: + if args.update_check: version_check(commit) - if update_all_extensions: - git_pull_recursive(os.path.join(data_path, dir_extensions)) + if args.update_all_extensions: + git_pull_recursive(extensions_dir) if "--exit" in sys.argv: print("Exiting because of --exit argument") exit(0) - if run_tests: - exitcode = tests(test_dir) + if args.tests and not args.no_tests: + exitcode = tests(args.tests) exit(exitcode) @@ -354,6 +321,8 @@ def tests(test_dir): sys.argv.append("--skip-torch-cuda-test") if "--disable-nan-check" not in sys.argv: sys.argv.append("--disable-nan-check") + if "--no-tests" not in sys.argv: + sys.argv.append("--no-tests") print(f"Launching Web UI in another process for testing with arguments: {' '.join(sys.argv[1:])}") diff --git a/modules/cmd_args.py b/modules/cmd_args.py index 73ce77d4..0af87251 100644 --- a/modules/cmd_args.py +++ b/modules/cmd_args.py @@ -1,31 +1,19 @@ import argparse -import datetime -import json import os -import sys -import time - -from PIL import Image -import gradio as gr -import tqdm - -import modules.interrogate -import modules.memmon -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 - - -demo = None - -sd_configs_path = os.path.join(script_path, "configs") -sd_default_config = os.path.join(sd_configs_path, "v1-inference.yaml") -sd_model_file = os.path.join(script_path, 'model.ckpt') -default_sd_model_file = sd_model_file +from modules.paths_internal import models_path, script_path, data_path, extensions_dir, extensions_builtin_dir, sd_default_config, sd_model_file parser = argparse.ArgumentParser() -parser.add_argument("--data-dir", type=str, default=os.path.dirname(os.path.dirname(os.path.realpath(__file__))), help="base path where all user data is stored",) + +parser.add_argument("--update-all-extensions", action='store_true', help="launch.py argument: download updates for all extensions when starting the program") +parser.add_argument("--skip-python-version-check", action='store_true', help="launch.py argument: do not check python version") +parser.add_argument("--skip-torch-cuda-test", action='store_true', help="launch.py argument: do not check if CUDA is able to work properly") +parser.add_argument("--reinstall-xformers", action='store_true', help="launch.py argument: install the appropriate version of xformers even if you have some version already installed") +parser.add_argument("--reinstall-torch", action='store_true', help="launch.py argument: install the appropriate version of torch even if you have some version already installed") +parser.add_argument("--update-check", action='store_true', help="launch.py argument: chck for updates at startup") +parser.add_argument("--tests", type=str, default=None, help="launch.py argument: run tests in the specified directory") +parser.add_argument("--no-tests", action='store_true', help="launch.py argument: do not run tests even if --tests option is specified") +parser.add_argument("--skip-install", action='store_true', help="launch.py argument: skip installation of packages") +parser.add_argument("--data-dir", type=str, default=os.path.dirname(os.path.dirname(os.path.realpath(__file__))), help="base path where all user data is stored") parser.add_argument("--config", type=str, default=sd_default_config, help="path to config which constructs model",) parser.add_argument("--ckpt", type=str, default=sd_model_file, help="path to checkpoint of stable diffusion model; if specified, this checkpoint will be added to the list of checkpoints and loaded",) parser.add_argument("--ckpt-dir", type=str, default=None, help="Path to directory with stable diffusion checkpoints") @@ -112,640 +100,3 @@ parser.add_argument("--no-gradio-queue", action='store_true', help="Disables gra 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) - - -script_loading.preload_extensions(extensions.extensions_dir, parser) -script_loading.preload_extensions(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", -} - -ui_reorder_categories = [ - "inpaint", - "sampler", - "checkboxes", - "hires_fix", - "dimensions", - "cfg", - "seed", - "batch", - "override_settings", - "scripts", -] - -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']) - -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 - need_restart = False - server_start = None - - def skip(self): - self.skipped = True - - def interrupt(self): - self.interrupted = True - - 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): - 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() - - devices.torch_gc() - - def end(self): - 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 - 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 - - 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): - self.default = default - self.label = label - self.component = component - self.component_args = component_args - self.onchange = onchange - self.section = section - self.refresh = refresh - - -def options_section(section_identifier, options_dict): - for k, v in options_dict.items(): - 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), - "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)"), - "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}), - - "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, "If the saved image file size is above the limit, or its either width or height are above the limit, save a downscaled copy as JPG"), - "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, in megapixels", gr.Number), - - "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"), - "do_not_add_watermark": OptionInfo(False, "Do not add watermark to images"), - - "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"), - -})) - -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), -})) - -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), - "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. 0 = no tiling.", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}), - "ESRGAN_tile_overlap": OptionInfo(8, "Tile overlap, in pixels for ESRGAN upscalers. Low values = visible seam.", gr.Slider, {"minimum": 0, "maximum": 48, "step": 1}), - "realesrgan_enabled_models": OptionInfo(["R-ESRGAN 4x+", "R-ESRGAN 4x+ Anime6B"], "Select which Real-ESRGAN models to show in the web UI. (Requires restart)", 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 parameter; 0 = maximum effect; 1 = minimum effect", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}), - "face_restoration_unload": OptionInfo(False, "Move face restoration model from VRAM into RAM after processing"), -})) - -options_templates.update(options_section(('system', "System"), { - "show_warnings": OptionInfo(False, "Show warnings in console."), - "memmon_poll_rate": OptionInfo(8, "VRAM usage polls per second during generation. Set to 0 to disable.", gr.Slider, {"minimum": 0, "maximum": 40, "step": 1}), - "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."), -})) - -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_checkpoint_cache": OptionInfo(0, "Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}), - "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), - "sd_vae_as_default": OptionInfo(True, "Ignore selected VAE for stable diffusion checkpoints that have their own .vae.pt next to them"), - "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 (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_emphasis": OptionInfo(True, "Emphasis: 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, "Increase coherency by padding from the last comma within n tokens when using more than 75 tokens", gr.Slider, {"minimum": 0, "maximum": 74, "step": 1 }), - "CLIP_stop_at_last_layers": OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}), - "upcast_attn": OptionInfo(False, "Upcast cross attention layer to float32"), -})) - -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)."), -})) - -options_templates.update(options_section(('interrogate', "Interrogate Options"), { - "interrogate_keep_models_in_memory": OptionInfo(False, "Interrogate: keep models in VRAM"), - "interrogate_return_ranks": OptionInfo(False, "Interrogate: include ranks of model tags matches in results (Has no effect on caption-based interrogators)."), - "interrogate_clip_num_beams": OptionInfo(1, "Interrogate: num_beams for BLIP", gr.Slider, {"minimum": 1, "maximum": 16, "step": 1}), - "interrogate_clip_min_length": OptionInfo(24, "Interrogate: minimum description length (excluding artists, etc..)", gr.Slider, {"minimum": 1, "maximum": 128, "step": 1}), - "interrogate_clip_max_length": OptionInfo(48, "Interrogate: 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 (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, "Interrogate: deepbooru score threshold", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}), - "deepbooru_sort_alpha": OptionInfo(True, "Interrogate: deepbooru sort alphabetically"), - "deepbooru_use_spaces": OptionInfo(False, "use spaces for tags in deepbooru"), - "deepbooru_escape": OptionInfo(True, "escape (\\) brackets in deepbooru (so they are used as literal brackets and not for emphasis)"), - "deepbooru_filter_tags": OptionInfo("", "filter out those tags from deepbooru output (separated by comma)"), -})) - -options_templates.update(options_section(('extra_networks', "Extra Networks"), { - "extra_networks_default_view": OptionInfo("cards", "Default view for Extra Networks", gr.Dropdown, {"choices": ["cards", "thumbs"]}), - "extra_networks_default_multiplier": OptionInfo(1.0, "Multiplier for extra networks", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), - "extra_networks_card_width": OptionInfo(0, "Card width for Extra Networks (px)"), - "extra_networks_card_height": OptionInfo(0, "Card height for Extra Networks (px)"), - "extra_networks_add_text_separator": OptionInfo(" ", "Extra text to add before <...> when adding extra network to prompt"), - "sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": [""] + [x for x in hypernetworks.keys()]}, refresh=reload_hypernetworks), -})) - -options_templates.update(options_section(('ui', "User interface"), { - "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"), - "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"), - "disable_weights_auto_swap": OptionInfo(True, "When reading generation parameters from text into UI (from PNG info or pasted text), do not change the selected model/checkpoint."), - "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"), - "font": OptionInfo("", "Font for image grids that have text"), - "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"), - "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"), - "dimensions_and_batch_together": OptionInfo(True, "Show Width/Height and Batch sliders in same row"), - "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}), - "quicksettings": OptionInfo("sd_model_checkpoint", "Quicksettings list"), - "hidden_tabs": OptionInfo([], "Hidden UI tabs (requires restart)", ui_components.DropdownMulti, lambda: {"choices": [x for x in tab_names]}), - "ui_reorder": OptionInfo(", ".join(ui_reorder_categories), "txt2img/img2img UI item order"), - "ui_extra_networks_tab_reorder": OptionInfo("", "Extra networks tab order"), - "localization": OptionInfo("None", "Localization (requires restart)", gr.Dropdown, lambda: {"choices": ["None"] + list(localization.localizations.keys())}, refresh=lambda: localization.list_localizations(cmd_opts.localizations_dir)), -})) - -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"), - "show_progress_grid": OptionInfo(True, "Show previews of all images generated in a batch as a grid"), - "show_progress_every_n_steps": OptionInfo(10, "Show new live preview image every N sampling steps. Set to -1 to show after completion of batch.", gr.Slider, {"minimum": -1, "maximum": 32, "step": 1}), - "show_progress_type": OptionInfo("Approx NN", "Image creation progress preview mode", gr.Radio, {"choices": ["Full", "Approx NN", "Approx cheap"]}), - "live_preview_content": OptionInfo("Prompt", "Live preview subject", gr.Radio, {"choices": ["Combined", "Prompt", "Negative prompt"]}), - "live_preview_refresh_period": OptionInfo(1000, "Progressbar/preview update period, in milliseconds") -})) - -options_templates.update(options_section(('sampler-params', "Sampler parameters"), { - "hide_samplers": OptionInfo([], "Hide samplers in user interface (requires restart)", gr.CheckboxGroup, lambda: {"choices": [x.name for x in list_samplers()]}), - "eta_ddim": OptionInfo(0.0, "eta (noise multiplier) for DDIM", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), - "eta_ancestral": OptionInfo(1.0, "eta (noise multiplier) for ancestral samplers", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), - "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_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), - 'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}), - 'always_discard_next_to_last_sigma': OptionInfo(False, "Always discard next-to-last sigma"), - '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 (must be < sampling steps)", gr.Slider, {"minimum": 1, "maximum": 50, "step": 1}), - '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 those extensions"), - "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) - 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 - - 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) - - 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, self.data_labels.get(k).default) for k in self.data_labels.keys()} - 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 k, item in settings_items: - if item.section not in section_ids: - section_ids[item.section] = len(section_ids) - - self.data_labels = {k: v for k, v in 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) - -settings_components = None -"""assinged from ui.py, a mapping on setting anmes 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 = [] - -sd_model = None - -clip_model = None - -progress_print_out = sys.stdout - - -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 listfiles(dirname): - filenames = [os.path.join(dirname, x) for x in sorted(os.listdir(dirname)) 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 "" diff --git a/modules/extensions.py b/modules/extensions.py index ed4b58fe..8107a933 100644 --- a/modules/extensions.py +++ b/modules/extensions.py @@ -8,11 +8,9 @@ import git from modules import paths, shared extensions = [] -extensions_dir = os.path.join(paths.data_path, "extensions") -extensions_builtin_dir = os.path.join(paths.script_path, "extensions-builtin") -if not os.path.exists(extensions_dir): - os.makedirs(extensions_dir) +if not os.path.exists(paths.extensions_dir): + os.makedirs(paths.extensions_dir) def active(): return [x for x in extensions if x.enabled] @@ -86,11 +84,11 @@ class Extension: def list_extensions(): extensions.clear() - if not os.path.isdir(extensions_dir): + if not os.path.isdir(paths.extensions_dir): return - paths = [] - for dirname in [extensions_dir, extensions_builtin_dir]: + extension_paths = [] + for dirname in [paths.extensions_dir, paths.extensions_builtin_dir]: if not os.path.isdir(dirname): return @@ -99,9 +97,9 @@ def list_extensions(): if not os.path.isdir(path): continue - paths.append((extension_dirname, path, dirname == extensions_builtin_dir)) + extension_paths.append((extension_dirname, path, dirname == paths.extensions_builtin_dir)) - for dirname, path, is_builtin in paths: + for dirname, path, is_builtin in extension_paths: extension = Extension(name=dirname, path=path, enabled=dirname not in shared.opts.disabled_extensions, is_builtin=is_builtin) extensions.append(extension) diff --git a/modules/paths.py b/modules/paths.py index d991cc71..0e1e00e7 100644 --- a/modules/paths.py +++ b/modules/paths.py @@ -1,16 +1,9 @@ -import argparse import os import sys -import modules.safe +from modules.paths_internal import models_path, script_path, data_path, extensions_dir, extensions_builtin_dir -script_path = os.path.dirname(os.path.dirname(os.path.realpath(__file__))) +import modules.safe -# Parse the --data-dir flag first so we can use it as a base for our other argument default values -parser = argparse.ArgumentParser(add_help=False) -parser.add_argument("--data-dir", type=str, default=os.path.dirname(os.path.dirname(os.path.realpath(__file__))), help="base path where all user data is stored",) -cmd_opts_pre = parser.parse_known_args()[0] -data_path = cmd_opts_pre.data_dir -models_path = os.path.join(data_path, "models") # data_path = cmd_opts_pre.data sys.path.insert(0, script_path) diff --git a/modules/paths_internal.py b/modules/paths_internal.py new file mode 100644 index 00000000..926ec3bb --- /dev/null +++ b/modules/paths_internal.py @@ -0,0 +1,22 @@ +"""this module defines internal paths used by program and is safe to import before dependencies are installed in launch.py""" + +import argparse +import os + +script_path = os.path.dirname(os.path.dirname(os.path.realpath(__file__))) + +sd_configs_path = os.path.join(script_path, "configs") +sd_default_config = os.path.join(sd_configs_path, "v1-inference.yaml") +sd_model_file = os.path.join(script_path, 'model.ckpt') +default_sd_model_file = sd_model_file + +# Parse the --data-dir flag first so we can use it as a base for our other argument default values +parser_pre = argparse.ArgumentParser(add_help=False) +parser_pre.add_argument("--data-dir", type=str, default=os.path.dirname(os.path.dirname(os.path.realpath(__file__))), help="base path where all user data is stored",) +cmd_opts_pre = parser_pre.parse_known_args()[0] + +data_path = cmd_opts_pre.data_dir + +models_path = os.path.join(data_path, "models") +extensions_dir = os.path.join(data_path, "extensions") +extensions_builtin_dir = os.path.join(script_path, "extensions-builtin") diff --git a/modules/shared.py b/modules/shared.py index 73ce77d4..11be3985 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -13,115 +13,22 @@ import modules.interrogate import modules.memmon 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 modules import localization, script_loading, errors, ui_components, shared_items, cmd_args +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 demo = None -sd_configs_path = os.path.join(script_path, "configs") -sd_default_config = os.path.join(sd_configs_path, "v1-inference.yaml") -sd_model_file = os.path.join(script_path, 'model.ckpt') -default_sd_model_file = sd_model_file - -parser = argparse.ArgumentParser() -parser.add_argument("--data-dir", type=str, default=os.path.dirname(os.path.dirname(os.path.realpath(__file__))), help="base path where all user data is stored",) -parser.add_argument("--config", type=str, default=sd_default_config, help="path to config which constructs model",) -parser.add_argument("--ckpt", type=str, default=sd_model_file, help="path to checkpoint of stable diffusion model; if specified, this checkpoint will be added to the list of checkpoints and loaded",) -parser.add_argument("--ckpt-dir", type=str, default=None, help="Path to directory with stable diffusion checkpoints") -parser.add_argument("--vae-dir", type=str, default=None, help="Path to directory with VAE files") -parser.add_argument("--gfpgan-dir", type=str, help="GFPGAN directory", default=('./src/gfpgan' if os.path.exists('./src/gfpgan') else './GFPGAN')) -parser.add_argument("--gfpgan-model", type=str, help="GFPGAN model file name", default=None) -parser.add_argument("--no-half", action='store_true', help="do not switch the model to 16-bit floats") -parser.add_argument("--no-half-vae", action='store_true', help="do not switch the VAE model to 16-bit floats") -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, '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") -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("--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("--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") -parser.add_argument("--enable-insecure-extension-access", action='store_true', help="enable extensions tab regardless of other options") -parser.add_argument("--codeformer-models-path", type=str, help="Path to directory with codeformer model file(s).", default=os.path.join(models_path, 'Codeformer')) -parser.add_argument("--gfpgan-models-path", type=str, help="Path to directory with GFPGAN model file(s).", default=os.path.join(models_path, 'GFPGAN')) -parser.add_argument("--esrgan-models-path", type=str, help="Path to directory with ESRGAN model file(s).", default=os.path.join(models_path, 'ESRGAN')) -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") -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") -parser.add_argument("--opt-split-attention", action='store_true', help="force-enables Doggettx's cross-attention layer optimization. By default, it's on for torch cuda.") -parser.add_argument("--opt-sub-quad-attention", action='store_true', help="enable memory efficient sub-quadratic cross-attention layer optimization") -parser.add_argument("--sub-quad-q-chunk-size", type=int, help="query chunk size for the sub-quadratic cross-attention layer optimization to use", default=1024) -parser.add_argument("--sub-quad-kv-chunk-size", type=int, help="kv chunk size for the sub-quadratic cross-attention layer optimization to use", default=None) -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.*") -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") -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) -parser.add_argument("--show-negative-prompt", action='store_true', help="does not do anything", default=False) -parser.add_argument("--ui-config-file", type=str, help="filename to use for ui configuration", default=os.path.join(data_path, 'ui-config.json')) -parser.add_argument("--hide-ui-dir-config", action='store_true', help="hide directory configuration from webui", default=False) -parser.add_argument("--freeze-settings", action='store_true', help="disable editing settings", default=False) -parser.add_argument("--ui-settings-file", type=str, help="filename to use for ui settings", default=os.path.join(data_path, 'config.json')) -parser.add_argument("--gradio-debug", action='store_true', help="launch gradio with --debug option") -parser.add_argument("--gradio-auth", type=str, help='set gradio authentication like "username:password"; or comma-delimit multiple like "u1:p1,u2:p2,u3:p3"', default=None) -parser.add_argument("--gradio-auth-path", type=str, help='set gradio authentication file path ex. "/path/to/auth/file" same auth format as --gradio-auth', default=None) -parser.add_argument("--gradio-img2img-tool", type=str, help='does not do anything') -parser.add_argument("--gradio-inpaint-tool", type=str, help="does not do anything") -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=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=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=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") -parser.add_argument("--ui-debug-mode", action='store_true', help="Don't load model to quickly launch UI") -parser.add_argument("--device-id", type=str, help="Select the default CUDA device to use (export CUDA_VISIBLE_DEVICES=0,1,etc might be needed before)", default=None) -parser.add_argument("--administrator", action='store_true', help="Administrator rights", default=False) -parser.add_argument("--cors-allow-origins", type=str, help="Allowed CORS origin(s) in the form of a comma-separated list (no spaces)", default=None) -parser.add_argument("--cors-allow-origins-regex", type=str, help="Allowed CORS origin(s) in the form of a single regular expression", default=None) -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="does not do anything", default=True) -parser.add_argument("--no-gradio-queue", action='store_true', help="Disables gradio queue; causes the webpage to use http requests instead of websockets; was the defaul in earlier versions") -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) - - -script_loading.preload_extensions(extensions.extensions_dir, parser) -script_loading.preload_extensions(extensions.extensions_builtin_dir, parser) +parser = cmd_args.parser + +script_loading.preload_extensions(extensions_dir, parser) +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", -- cgit v1.2.3 From 8a34671fe91e142bce9e5556cca2258b3be9dd6e Mon Sep 17 00:00:00 2001 From: MrCheeze Date: Fri, 24 Mar 2023 22:48:16 -0400 Subject: Add support for the Variations models (unclip-h and unclip-l) --- launch.py | 2 +- models/karlo/ViT-L-14_stats.th | Bin 0 -> 7079 bytes modules/lowvram.py | 10 ++++++---- modules/processing.py | 41 +++++++++++++++++++++++++++----------- modules/sd_models.py | 5 +++++ modules/sd_models_config.py | 7 +++++++ modules/sd_samplers_compvis.py | 31 +++++++++++++++++++++------- modules/sd_samplers_kdiffusion.py | 19 ++++++++++++------ 8 files changed, 85 insertions(+), 30 deletions(-) create mode 100644 models/karlo/ViT-L-14_stats.th (limited to 'launch.py') diff --git a/launch.py b/launch.py index b943fed2..e70df7ba 100644 --- a/launch.py +++ b/launch.py @@ -252,7 +252,7 @@ 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', "47b6b607fdd31875c9279cd2f4f16b92e4ea958e") + stable_diffusion_commit_hash = os.environ.get('STABLE_DIFFUSION_COMMIT_HASH', "cf1d67a6fd5ea1aa600c4df58e5b47da45f6bdbf") 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") diff --git a/models/karlo/ViT-L-14_stats.th b/models/karlo/ViT-L-14_stats.th new file mode 100644 index 00000000..a6a06e94 Binary files /dev/null and b/models/karlo/ViT-L-14_stats.th differ diff --git a/modules/lowvram.py b/modules/lowvram.py index 042a0254..e254cc13 100644 --- a/modules/lowvram.py +++ b/modules/lowvram.py @@ -55,12 +55,12 @@ def setup_for_low_vram(sd_model, use_medvram): if hasattr(sd_model.cond_stage_model, 'model'): sd_model.cond_stage_model.transformer = sd_model.cond_stage_model.model - # remove four big modules, cond, first_stage, depth (if applicable), and unet from the model and then + # remove several big modules: cond, first_stage, depth/embedder (if applicable), and unet from the model and then # send the model to GPU. Then put modules back. the modules will be in CPU. - stored = sd_model.cond_stage_model.transformer, sd_model.first_stage_model, getattr(sd_model, 'depth_model', None), sd_model.model - sd_model.cond_stage_model.transformer, sd_model.first_stage_model, sd_model.depth_model, sd_model.model = None, None, None, None + stored = sd_model.cond_stage_model.transformer, sd_model.first_stage_model, getattr(sd_model, 'depth_model', None), getattr(sd_model, 'embedder', None), sd_model.model + sd_model.cond_stage_model.transformer, sd_model.first_stage_model, sd_model.depth_model, sd_model.embedder, sd_model.model = None, None, None, None, None sd_model.to(devices.device) - sd_model.cond_stage_model.transformer, sd_model.first_stage_model, sd_model.depth_model, sd_model.model = stored + sd_model.cond_stage_model.transformer, sd_model.first_stage_model, sd_model.depth_model, sd_model.embedder, sd_model.model = stored # register hooks for those the first three models sd_model.cond_stage_model.transformer.register_forward_pre_hook(send_me_to_gpu) @@ -69,6 +69,8 @@ def setup_for_low_vram(sd_model, use_medvram): sd_model.first_stage_model.decode = first_stage_model_decode_wrap if sd_model.depth_model: sd_model.depth_model.register_forward_pre_hook(send_me_to_gpu) + if sd_model.embedder: + sd_model.embedder.register_forward_pre_hook(send_me_to_gpu) parents[sd_model.cond_stage_model.transformer] = sd_model.cond_stage_model if hasattr(sd_model.cond_stage_model, 'model'): diff --git a/modules/processing.py b/modules/processing.py index 59717b4c..1451811c 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -78,21 +78,27 @@ def apply_overlay(image, paste_loc, index, overlays): def txt2img_image_conditioning(sd_model, x, width, height): - if sd_model.model.conditioning_key not in {'hybrid', 'concat'}: - # Dummy zero conditioning if we're not using inpainting model. - # Still takes up a bit of memory, but no encoder call. - # Pretty sure we can just make this a 1x1 image since its not going to be used besides its batch size. - return x.new_zeros(x.shape[0], 5, 1, 1, dtype=x.dtype, device=x.device) + if sd_model.model.conditioning_key in {'hybrid', 'concat'}: # Inpainting models - # The "masked-image" in this case will just be all zeros since the entire image is masked. - image_conditioning = torch.zeros(x.shape[0], 3, height, width, device=x.device) - image_conditioning = sd_model.get_first_stage_encoding(sd_model.encode_first_stage(image_conditioning)) + # The "masked-image" in this case will just be all zeros since the entire image is masked. + image_conditioning = torch.zeros(x.shape[0], 3, height, width, device=x.device) + image_conditioning = sd_model.get_first_stage_encoding(sd_model.encode_first_stage(image_conditioning)) - # Add the fake full 1s mask to the first dimension. - image_conditioning = torch.nn.functional.pad(image_conditioning, (0, 0, 0, 0, 1, 0), value=1.0) - image_conditioning = image_conditioning.to(x.dtype) + # Add the fake full 1s mask to the first dimension. + image_conditioning = torch.nn.functional.pad(image_conditioning, (0, 0, 0, 0, 1, 0), value=1.0) + image_conditioning = image_conditioning.to(x.dtype) - return image_conditioning + return image_conditioning + + elif sd_model.model.conditioning_key == "crossattn-adm": # UnCLIP models + + return x.new_zeros(x.shape[0], 2*sd_model.noise_augmentor.time_embed.dim, dtype=x.dtype, device=x.device) + + else: + # Dummy zero conditioning if we're not using inpainting or unclip models. + # Still takes up a bit of memory, but no encoder call. + # Pretty sure we can just make this a 1x1 image since its not going to be used besides its batch size. + return x.new_zeros(x.shape[0], 5, 1, 1, dtype=x.dtype, device=x.device) class StableDiffusionProcessing: @@ -190,6 +196,14 @@ class StableDiffusionProcessing: return conditioning_image + def unclip_image_conditioning(self, source_image): + c_adm = self.sd_model.embedder(source_image) + if self.sd_model.noise_augmentor is not None: + noise_level = 0 # TODO: Allow other noise levels? + c_adm, noise_level_emb = self.sd_model.noise_augmentor(c_adm, noise_level=repeat(torch.tensor([noise_level]).to(c_adm.device), '1 -> b', b=c_adm.shape[0])) + c_adm = torch.cat((c_adm, noise_level_emb), 1) + return c_adm + def inpainting_image_conditioning(self, source_image, latent_image, image_mask=None): self.is_using_inpainting_conditioning = True @@ -241,6 +255,9 @@ class StableDiffusionProcessing: if self.sampler.conditioning_key in {'hybrid', 'concat'}: return self.inpainting_image_conditioning(source_image, latent_image, image_mask=image_mask) + if self.sampler.conditioning_key == "crossattn-adm": + return self.unclip_image_conditioning(source_image) + # Dummy zero conditioning if we're not using inpainting or depth model. return latent_image.new_zeros(latent_image.shape[0], 5, 1, 1) diff --git a/modules/sd_models.py b/modules/sd_models.py index f0cb1240..c1a80d82 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -383,6 +383,11 @@ def repair_config(sd_config): elif shared.cmd_opts.upcast_sampling: sd_config.model.params.unet_config.params.use_fp16 = True + # For UnCLIP-L, override the hardcoded karlo directory + if hasattr(sd_config.model.params, "noise_aug_config") and hasattr(sd_config.model.params.noise_aug_config.params, "clip_stats_path"): + karlo_path = os.path.join(paths.models_path, 'karlo') + sd_config.model.params.noise_aug_config.params.clip_stats_path = sd_config.model.params.noise_aug_config.params.clip_stats_path.replace("checkpoints/karlo_models", karlo_path) + sd1_clip_weight = 'cond_stage_model.transformer.text_model.embeddings.token_embedding.weight' sd2_clip_weight = 'cond_stage_model.model.transformer.resblocks.0.attn.in_proj_weight' diff --git a/modules/sd_models_config.py b/modules/sd_models_config.py index 91c21700..9398f528 100644 --- a/modules/sd_models_config.py +++ b/modules/sd_models_config.py @@ -14,6 +14,8 @@ config_sd2 = os.path.join(sd_repo_configs_path, "v2-inference.yaml") config_sd2v = os.path.join(sd_repo_configs_path, "v2-inference-v.yaml") config_sd2_inpainting = os.path.join(sd_repo_configs_path, "v2-inpainting-inference.yaml") config_depth_model = os.path.join(sd_repo_configs_path, "v2-midas-inference.yaml") +config_unclip = os.path.join(sd_repo_configs_path, "v2-1-stable-unclip-l-inference.yaml") +config_unopenclip = os.path.join(sd_repo_configs_path, "v2-1-stable-unclip-h-inference.yaml") config_inpainting = os.path.join(sd_configs_path, "v1-inpainting-inference.yaml") config_instruct_pix2pix = os.path.join(sd_configs_path, "instruct-pix2pix.yaml") config_alt_diffusion = os.path.join(sd_configs_path, "alt-diffusion-inference.yaml") @@ -65,9 +67,14 @@ def is_using_v_parameterization_for_sd2(state_dict): def guess_model_config_from_state_dict(sd, filename): sd2_cond_proj_weight = sd.get('cond_stage_model.model.transformer.resblocks.0.attn.in_proj_weight', None) diffusion_model_input = sd.get('model.diffusion_model.input_blocks.0.0.weight', None) + sd2_variations_weight = sd.get('embedder.model.ln_final.weight', None) if sd.get('depth_model.model.pretrained.act_postprocess3.0.project.0.bias', None) is not None: return config_depth_model + elif sd2_variations_weight is not None and sd2_variations_weight.shape[0] == 768: + return config_unclip + elif sd2_variations_weight is not None and sd2_variations_weight.shape[0] == 1024: + return config_unopenclip if sd2_cond_proj_weight is not None and sd2_cond_proj_weight.shape[1] == 1024: if diffusion_model_input.shape[1] == 9: diff --git a/modules/sd_samplers_compvis.py b/modules/sd_samplers_compvis.py index 083da18c..bfcc5574 100644 --- a/modules/sd_samplers_compvis.py +++ b/modules/sd_samplers_compvis.py @@ -70,8 +70,13 @@ class VanillaStableDiffusionSampler: # Have to unwrap the inpainting conditioning here to perform pre-processing image_conditioning = None + uc_image_conditioning = None if isinstance(cond, dict): - image_conditioning = cond["c_concat"][0] + if self.conditioning_key == "crossattn-adm": + image_conditioning = cond["c_adm"] + uc_image_conditioning = unconditional_conditioning["c_adm"] + else: + image_conditioning = cond["c_concat"][0] cond = cond["c_crossattn"][0] unconditional_conditioning = unconditional_conditioning["c_crossattn"][0] @@ -98,8 +103,12 @@ class VanillaStableDiffusionSampler: # Wrap the image conditioning back up since the DDIM code can accept the dict directly. # Note that they need to be lists because it just concatenates them later. if image_conditioning is not None: - cond = {"c_concat": [image_conditioning], "c_crossattn": [cond]} - unconditional_conditioning = {"c_concat": [image_conditioning], "c_crossattn": [unconditional_conditioning]} + if self.conditioning_key == "crossattn-adm": + cond = {"c_adm": image_conditioning, "c_crossattn": [cond]} + unconditional_conditioning = {"c_adm": uc_image_conditioning, "c_crossattn": [unconditional_conditioning]} + else: + cond = {"c_concat": [image_conditioning], "c_crossattn": [cond]} + unconditional_conditioning = {"c_concat": [image_conditioning], "c_crossattn": [unconditional_conditioning]} return x, ts, cond, unconditional_conditioning @@ -176,8 +185,12 @@ class VanillaStableDiffusionSampler: # Wrap the conditioning models with additional image conditioning for inpainting model if image_conditioning is not None: - conditioning = {"c_concat": [image_conditioning], "c_crossattn": [conditioning]} - unconditional_conditioning = {"c_concat": [image_conditioning], "c_crossattn": [unconditional_conditioning]} + if self.conditioning_key == "crossattn-adm": + conditioning = {"c_adm": image_conditioning, "c_crossattn": [conditioning]} + unconditional_conditioning = {"c_adm": torch.zeros_like(image_conditioning), "c_crossattn": [unconditional_conditioning]} + else: + conditioning = {"c_concat": [image_conditioning], "c_crossattn": [conditioning]} + unconditional_conditioning = {"c_concat": [image_conditioning], "c_crossattn": [unconditional_conditioning]} samples = self.launch_sampling(t_enc + 1, lambda: self.sampler.decode(x1, conditioning, t_enc, unconditional_guidance_scale=p.cfg_scale, unconditional_conditioning=unconditional_conditioning)) @@ -195,8 +208,12 @@ class VanillaStableDiffusionSampler: # Wrap the conditioning models with additional image conditioning for inpainting model # dummy_for_plms is needed because PLMS code checks the first item in the dict to have the right shape if image_conditioning is not None: - conditioning = {"dummy_for_plms": np.zeros((conditioning.shape[0],)), "c_crossattn": [conditioning], "c_concat": [image_conditioning]} - unconditional_conditioning = {"c_crossattn": [unconditional_conditioning], "c_concat": [image_conditioning]} + if self.conditioning_key == "crossattn-adm": + conditioning = {"dummy_for_plms": np.zeros((conditioning.shape[0],)), "c_crossattn": [conditioning], "c_adm": image_conditioning} + unconditional_conditioning = {"c_crossattn": [unconditional_conditioning], "c_adm": torch.zeros_like(image_conditioning)} + else: + conditioning = {"dummy_for_plms": np.zeros((conditioning.shape[0],)), "c_crossattn": [conditioning], "c_concat": [image_conditioning]} + unconditional_conditioning = {"c_crossattn": [unconditional_conditioning], "c_concat": [image_conditioning]} samples_ddim = self.launch_sampling(steps, lambda: self.sampler.sample(S=steps, conditioning=conditioning, batch_size=int(x.shape[0]), shape=x[0].shape, verbose=False, unconditional_guidance_scale=p.cfg_scale, unconditional_conditioning=unconditional_conditioning, x_T=x, eta=self.eta)[0]) diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index 93f0e55a..e9f08518 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -92,14 +92,21 @@ class CFGDenoiser(torch.nn.Module): batch_size = len(conds_list) repeats = [len(conds_list[i]) for i in range(batch_size)] + if shared.sd_model.model.conditioning_key == "crossattn-adm": + image_uncond = torch.zeros_like(image_cond) + make_condition_dict = lambda c_crossattn, c_adm: {"c_crossattn": c_crossattn, "c_adm": c_adm} + else: + image_uncond = image_cond + make_condition_dict = lambda c_crossattn, c_concat: {"c_crossattn": c_crossattn, "c_concat": [c_concat]} + if not is_edit_model: x_in = torch.cat([torch.stack([x[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [x]) sigma_in = torch.cat([torch.stack([sigma[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [sigma]) - image_cond_in = torch.cat([torch.stack([image_cond[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [image_cond]) + image_cond_in = torch.cat([torch.stack([image_cond[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [image_uncond]) else: x_in = torch.cat([torch.stack([x[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [x] + [x]) sigma_in = torch.cat([torch.stack([sigma[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [sigma] + [sigma]) - image_cond_in = torch.cat([torch.stack([image_cond[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [image_cond] + [torch.zeros_like(self.init_latent)]) + image_cond_in = torch.cat([torch.stack([image_cond[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [image_uncond] + [torch.zeros_like(self.init_latent)]) denoiser_params = CFGDenoiserParams(x_in, image_cond_in, sigma_in, state.sampling_step, state.sampling_steps, tensor, uncond) cfg_denoiser_callback(denoiser_params) @@ -116,13 +123,13 @@ class CFGDenoiser(torch.nn.Module): cond_in = torch.cat([tensor, uncond, uncond]) if shared.batch_cond_uncond: - x_out = self.inner_model(x_in, sigma_in, cond={"c_crossattn": [cond_in], "c_concat": [image_cond_in]}) + 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) for batch_offset in range(0, x_out.shape[0], batch_size): a = batch_offset b = a + batch_size - x_out[a:b] = self.inner_model(x_in[a:b], sigma_in[a:b], cond={"c_crossattn": [cond_in[a:b]], "c_concat": [image_cond_in[a:b]]}) + x_out[a:b] = self.inner_model(x_in[a:b], sigma_in[a:b], cond=make_condition_dict([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 @@ -135,9 +142,9 @@ class CFGDenoiser(torch.nn.Module): else: c_crossattn = torch.cat([tensor[a:b]], uncond) - x_out[a:b] = self.inner_model(x_in[a:b], sigma_in[a:b], cond={"c_crossattn": c_crossattn, "c_concat": [image_cond_in[a:b]]}) + x_out[a:b] = self.inner_model(x_in[a:b], sigma_in[a:b], cond=make_condition_dict(c_crossattn, image_cond_in[a:b])) - x_out[-uncond.shape[0]:] = self.inner_model(x_in[-uncond.shape[0]:], sigma_in[-uncond.shape[0]:], cond={"c_crossattn": [uncond], "c_concat": [image_cond_in[-uncond.shape[0]:]]}) + x_out[-uncond.shape[0]:] = self.inner_model(x_in[-uncond.shape[0]:], sigma_in[-uncond.shape[0]:], cond=make_condition_dict([uncond], image_cond_in[-uncond.shape[0]:])) denoised_params = CFGDenoisedParams(x_out, state.sampling_step, state.sampling_steps) cfg_denoised_callback(denoised_params) -- cgit v1.2.3 From 2a4d3d21242dcc8b2b9cef85aa8f4227e855dc96 Mon Sep 17 00:00:00 2001 From: space-nuko <24979496+space-nuko@users.noreply.github.com> Date: Mon, 27 Mar 2023 12:04:45 -0400 Subject: Add temporary "disable all extensions" option for debugging use --- launch.py | 4 ++++ modules/extensions.py | 4 ++++ modules/shared.py | 3 ++- 3 files changed, 10 insertions(+), 1 deletion(-) (limited to 'launch.py') diff --git a/launch.py b/launch.py index c41ae82d..1321b77a 100644 --- a/launch.py +++ b/launch.py @@ -206,6 +206,10 @@ def list_extensions(settings_file): print(e, file=sys.stderr) disabled_extensions = set(settings.get('disabled_extensions', [])) + disable_all_extensions = settings.get('disable_all_extensions', False) + + if disable_all_extensions: + return [] return [x for x in os.listdir(extensions_dir) if x not in disabled_extensions] diff --git a/modules/extensions.py b/modules/extensions.py index 0d34b89a..1493e8c8 100644 --- a/modules/extensions.py +++ b/modules/extensions.py @@ -97,6 +97,10 @@ def list_extensions(): if not os.path.isdir(extensions_dir): return + if shared.opts.disable_all_extensions: + print("*** \"Disable all extensions\" option was set, will not load any extensions ***") + return + extension_paths = [] for dirname in [extensions_dir, extensions_builtin_dir]: if not os.path.isdir(dirname): diff --git a/modules/shared.py b/modules/shared.py index 3ad0862b..c79ec67b 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -422,7 +422,8 @@ options_templates.update(options_section(('postprocessing', "Postprocessing"), { })) options_templates.update(options_section((None, "Hidden options"), { - "disabled_extensions": OptionInfo([], "Disable those extensions"), + "disabled_extensions": OptionInfo([], "Disable these extensions"), + "disable_all_extensions": OptionInfo(False, "Disable all extensions (preserves the list of disabled extensions)"), "sd_checkpoint_hash": OptionInfo("", "SHA256 hash of the current checkpoint"), })) -- cgit v1.2.3 From fc8e1008ea93f98554907f25aaf52f24ce661847 Mon Sep 17 00:00:00 2001 From: space-nuko <24979496+space-nuko@users.noreply.github.com> Date: Mon, 27 Mar 2023 12:44:49 -0400 Subject: Make disable configurable between builtin/extra extensions --- javascript/extensions.js | 6 +++--- launch.py | 4 ---- modules/extensions.py | 13 +++++++++---- modules/shared.py | 2 +- modules/ui_extensions.py | 21 +++++++++++++++++---- 5 files changed, 30 insertions(+), 16 deletions(-) (limited to 'launch.py') diff --git a/javascript/extensions.js b/javascript/extensions.js index c593cd2e..72924a28 100644 --- a/javascript/extensions.js +++ b/javascript/extensions.js @@ -1,5 +1,5 @@ -function extensions_apply(_, _){ +function extensions_apply(_, _, disable_all){ var disable = [] var update = [] @@ -13,10 +13,10 @@ function extensions_apply(_, _){ restart_reload() - return [JSON.stringify(disable), JSON.stringify(update)] + return [JSON.stringify(disable), JSON.stringify(update), disable_all] } -function extensions_check(){ +function extensions_check(_, _){ var disable = [] gradioApp().querySelectorAll('#extensions input[type="checkbox"]').forEach(function(x){ diff --git a/launch.py b/launch.py index 1321b77a..c41ae82d 100644 --- a/launch.py +++ b/launch.py @@ -206,10 +206,6 @@ def list_extensions(settings_file): print(e, file=sys.stderr) disabled_extensions = set(settings.get('disabled_extensions', [])) - disable_all_extensions = settings.get('disable_all_extensions', False) - - if disable_all_extensions: - return [] return [x for x in os.listdir(extensions_dir) if x not in disabled_extensions] diff --git a/modules/extensions.py b/modules/extensions.py index 1493e8c8..3a7a0372 100644 --- a/modules/extensions.py +++ b/modules/extensions.py @@ -15,7 +15,12 @@ if not os.path.exists(extensions_dir): def active(): - return [x for x in extensions if x.enabled] + if shared.opts.disable_all_extensions == "all": + return [] + elif shared.opts.disable_all_extensions == "extra": + return [x for x in extensions if x.enabled and x.is_builtin] + else: + return [x for x in extensions if x.enabled] class Extension: @@ -97,9 +102,10 @@ def list_extensions(): if not os.path.isdir(extensions_dir): return - if shared.opts.disable_all_extensions: + if shared.opts.disable_all_extensions == "all": print("*** \"Disable all extensions\" option was set, will not load any extensions ***") - return + elif shared.opts.disable_all_extensions == "extra": + print("*** \"Disable all extensions\" option was set, will only load built-in extensions ***") extension_paths = [] for dirname in [extensions_dir, extensions_builtin_dir]: @@ -116,4 +122,3 @@ def list_extensions(): for dirname, path, is_builtin in extension_paths: extension = Extension(name=dirname, path=path, enabled=dirname not in shared.opts.disabled_extensions, is_builtin=is_builtin) extensions.append(extension) - diff --git a/modules/shared.py b/modules/shared.py index c79ec67b..5fd0eecb 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -423,7 +423,7 @@ options_templates.update(options_section(('postprocessing', "Postprocessing"), { options_templates.update(options_section((None, "Hidden options"), { "disabled_extensions": OptionInfo([], "Disable these extensions"), - "disable_all_extensions": OptionInfo(False, "Disable all extensions (preserves the list of disabled extensions)"), + "disable_all_extensions": OptionInfo("none", "Disable all extensions (preserves the list of disabled extensions)", gr.Radio, {"choices": ["none", "extra", "all"]}), "sd_checkpoint_hash": OptionInfo("", "SHA256 hash of the current checkpoint"), })) diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py index b4a0d6ec..efd6cda2 100644 --- a/modules/ui_extensions.py +++ b/modules/ui_extensions.py @@ -21,7 +21,7 @@ def check_access(): assert not shared.cmd_opts.disable_extension_access, "extension access disabled because of command line flags" -def apply_and_restart(disable_list, update_list): +def apply_and_restart(disable_list, update_list, disable_all): check_access() disabled = json.loads(disable_list) @@ -43,6 +43,7 @@ def apply_and_restart(disable_list, update_list): print(traceback.format_exc(), file=sys.stderr) shared.opts.disabled_extensions = disabled + shared.opts.disable_all_extensions = disable_all shared.opts.save(shared.config_filename) shared.state.interrupt() @@ -99,9 +100,13 @@ def extension_table(): else: ext_status = ext.status + style = "" + if shared.opts.disable_all_extensions == "extra" and not ext.is_builtin or shared.opts.disable_all_extensions == "all": + style = ' style="color: var(--primary-400)"' + code += f""" - + {html.escape(ext.name)} {remote} {ext.version} {ext_status} @@ -294,16 +299,24 @@ def create_ui(): with gr.Row(elem_id="extensions_installed_top"): apply = gr.Button(value="Apply and restart UI", 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) - info = gr.HTML() + html = "" + if shared.opts.disable_all_extensions != "none": + html = """ + + "Disable all extensions" was set, change it to "none" to load all extensions again + + """ + info = gr.HTML(html) extensions_table = gr.HTML(lambda: extension_table()) apply.click( fn=apply_and_restart, _js="extensions_apply", - inputs=[extensions_disabled_list, extensions_update_list], + inputs=[extensions_disabled_list, extensions_update_list, extensions_disable_all], outputs=[], ) -- cgit v1.2.3 From 56f62d3851ff08dc1574a9ff2a05271f3730f3f7 Mon Sep 17 00:00:00 2001 From: space-nuko <24979496+space-nuko@users.noreply.github.com> Date: Mon, 27 Mar 2023 17:23:20 -0400 Subject: Skip extension installers if all disabled --- launch.py | 4 ++++ 1 file changed, 4 insertions(+) (limited to 'launch.py') diff --git a/launch.py b/launch.py index c41ae82d..2e3cd4c4 100644 --- a/launch.py +++ b/launch.py @@ -206,6 +206,10 @@ def list_extensions(settings_file): print(e, file=sys.stderr) disabled_extensions = set(settings.get('disabled_extensions', [])) + disable_all_extensions = settings.get('disable_all_extensions', 'none') + + if disable_all_extensions != 'none': + return [] return [x for x in os.listdir(extensions_dir) if x not in disabled_extensions] -- cgit v1.2.3