diff --git a/CHANGELOG.md b/CHANGELOG.md index a6e47d840..d87f6fcd1 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -5,6 +5,8 @@ - general: - caching of extra network information to enable much faster create/refresh operations thanks @midcoastal +- diffusers: + - redo "move model to cpu" logic to be more reliable ## Update for 2023-08-17 diff --git a/installer.py b/installer.py index 576f87018..d24610e00 100644 --- a/installer.py +++ b/installer.py @@ -288,12 +288,9 @@ def check_python(): log.debug(f'Git {git_version.replace("git version", "").strip()}') -# Intel hasn't released a corresponding torchvision wheel along with torch and -# ipex wheels, so we have to install official pytorch torchvision as a W/A. -# However, the latest torchvision explicitly requires torch version == 2.0.1, -# which is incompatible with the Intel torch version 2.0.0a0. This will cause -# intel torch to be uninstalled when pip scans the dependencies of torchvision. -# This function will check the torch version and force installing Intel torch +# Intel hasn't released a corresponding torchvision wheel along with torch and ipex wheels, so we have to install official pytorch torchvision as a W/A. +# However, the latest torchvision explicitly requires torch version == 2.0.1, which is incompatible with the Intel torch version 2.0.0a0. This will cause +# intel torch to be uninstalled when pip scans the dependencies of torchvision. This function will check the torch version and force installing Intel torch # 2.0.0a0 to avoid the underlying dll version error. # TODO(Disty or Nuullll) remove this W/A when Intel releases torchvision wheel for windows. def fix_ipex_win_torch(): @@ -306,8 +303,8 @@ def fix_ipex_win_torch(): log.warning(f'Incompatible torch version {installed_torch_ver} for ipex windows, reinstalling to {ipex_torch_ver}') torch_command = os.environ.get('TORCH_COMMAND', 'torch==2.0.0a0 intel_extension_for_pytorch==2.0.110+gitba7f6c1 -f https://developer.intel.com/ipex-whl-stable-xpu') install(torch_command) - import torch - import intel_extension_for_pytorch as ipex + import torch # pylint: disable=unused-import + import intel_extension_for_pytorch as ipex # pylint: disable=unused-import except Exception as e: log.warning(e) @@ -340,7 +337,6 @@ def check_torch(): log.info('AMD ROCm toolkit detected') os.environ.setdefault('PYTORCH_HIP_ALLOC_CONF', 'garbage_collection_threshold:0.8,max_split_size_mb:512') os.environ.setdefault('TENSORFLOW_PACKAGE', 'tensorflow-rocm') - try: command = subprocess.run('rocm_agent_enumerator', shell=True, check=False, stdout=subprocess.PIPE, stderr=subprocess.PIPE) amd_gpus = command.stdout.decode(encoding="utf8", errors="ignore").split('\n') @@ -350,31 +346,26 @@ def check_torch(): log.debug(f'Run rocm_agent_enumerator failed: {e}') amd_gpus = [] - # use the first available amd gpu by default - hip_visible_devices = [] + hip_visible_devices = [] # use the first available amd gpu by default for idx, gpu in enumerate(amd_gpus): if gpu in ['gfx1100', 'gfx1101', 'gfx1102']: hip_visible_devices.append((idx, gpu, 'navi3x')) break - # experimental navi 2x support - if gpu in ['gfx1030', 'gfx1031', 'gfx1032', 'gfx1034']: + if gpu in ['gfx1030', 'gfx1031', 'gfx1032', 'gfx1034']: # experimental navi 2x support hip_visible_devices.append((idx, gpu, 'navi2x')) break if len(hip_visible_devices) > 0: idx, gpu, arch = hip_visible_devices[0] log.debug(f'ROCm agent used by default: idx={idx} gpu={gpu} arch={arch}') - os.environ.setdefault('HIP_VISIBLE_DEVICES', str(idx)) if arch == 'navi3x': os.environ.setdefault('HSA_OVERRIDE_GFX_VERSION', '11.0.0') - # do not use tensorflow-rocm for navi 3x - if os.environ.get('TENSORFLOW_PACKAGE') == 'tensorflow-rocm': + if os.environ.get('TENSORFLOW_PACKAGE') == 'tensorflow-rocm': # do not use tensorflow-rocm for navi 3x os.environ['TENSORFLOW_PACKAGE'] = 'tensorflow==2.13.0' elif arch == 'navi2x': os.environ.setdefault('HSA_OVERRIDE_GFX_VERSION', '10.3.0') else: log.debug(f'HSA_OVERRIDE_GFX_VERSION auto config is skipped for {gpu}') - try: command = subprocess.run('hipconfig --version', shell=True, check=False, stdout=subprocess.PIPE, stderr=subprocess.PIPE) major_ver, minor_ver, *_ = command.stdout.decode(encoding="utf8", errors="ignore").split('.') @@ -383,13 +374,11 @@ def check_torch(): except Exception as e: log.debug(f'Run hipconfig failed: {e}') rocm_ver = None - if rocm_ver in ['5.5', '5.6']: # install torch nightly via torchvision to avoid wasting bandwidth when torchvision depends on torch from yesterday torch_command = os.environ.get('TORCH_COMMAND', f'torchvision --pre --index-url https://download.pytorch.org/whl/nightly/rocm{rocm_ver}') else: torch_command = os.environ.get('TORCH_COMMAND', 'torch==2.0.1 torchvision==0.15.2 --index-url https://download.pytorch.org/whl/rocm5.4.2') - xformers_package = os.environ.get('XFORMERS_PACKAGE', 'none') elif allow_ipex and (args.use_ipex or shutil.which('sycl-ls') is not None or shutil.which('sycl-ls.exe') is not None or os.environ.get('ONEAPI_ROOT') is not None or os.path.exists('/opt/intel/oneapi') or os.path.exists("C:/Program Files (x86)/Intel/oneAPI") or os.path.exists("C:/oneAPI")): args.use_ipex = True # pylint: disable=attribute-defined-outside-init diff --git a/modules/modelloader.py b/modules/modelloader.py index aa996eddf..5430f6364 100644 --- a/modules/modelloader.py +++ b/modules/modelloader.py @@ -14,14 +14,12 @@ def walk(top, onerror:callable=None): # A near-exact copy of `os.path.walk()`, trimmed slightly. Probably not nessesary for most people's collections, but makes a difference on really large datasets. nondirs = [] walk_dirs = [] - try: scandir_it = os.scandir(top) except OSError as error: if onerror is not None: onerror(error, top) return - with scandir_it: while True: try: @@ -49,6 +47,8 @@ def walk(top, onerror:callable=None): onerror(error, entry.path) # Recurse into sub-directories for new_path in walk_dirs: + if os.path.basename(new_path).startswith('models--'): + continue yield from walk(new_path, onerror) # Yield after recursion if going bottom up yield top, nondirs @@ -214,7 +214,7 @@ def directory_directories(dir:str, *, recursive:bool=True) -> dict[str,tuple[flo except Exception: pass del modelloader_directories[_dir] - for _dir, _files in walk(dir, lambda e, path: shared.log.error(f"Filesystem Walk Error: {e.__class__.__name__}({e}) -> {path}")): + for _dir, _files in walk(dir, lambda e, path: shared.log.debug(f"FS walk error: {e} {path}")): try: mtime = os.path.getmtime(_dir) if _dir not in modelloader_directories or mtime != modelloader_directories[_dir][0]: diff --git a/modules/processing_diffusers.py b/modules/processing_diffusers.py index fa14a480e..8d77a3623 100644 --- a/modules/processing_diffusers.py +++ b/modules/processing_diffusers.py @@ -51,6 +51,7 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro unet_device = model.unet.device model.unet.to(devices.cpu) devices.torch_gc() + model.vae.to(devices.device) latents.to(model.vae.device) decoded = model.vae.decode(latents / model.vae.config.scaling_factor, return_dict=False)[0] if shared.opts.diffusers_move_unet and not model.has_accelerate: @@ -117,13 +118,9 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro negative_pooled = None prompts, negative_prompts, prompts_2, negative_prompts_2 = fix_prompts(prompts, negative_prompts, prompts_2, negative_prompts_2) if shared.opts.prompt_attention in {'Compel parser', 'Full parser'}: - prompt_embed, pooled, negative_embed, negative_pooled = prompt_parser_diffusers.compel_encode_prompts(model, - prompts, - negative_prompts, - prompts_2, - negative_prompts_2, - is_refiner, - kwargs.pop("clip_skip", None)) + prompt_embed, pooled, negative_embed, negative_pooled = prompt_parser_diffusers.compel_encode_prompts(model, prompts, negative_prompts, + prompts_2, negative_prompts_2, + is_refiner, kwargs.pop("clip_skip", None)) if 'prompt' in possible: if hasattr(model, 'text_encoder') and 'prompt_embeds' in possible and prompt_embed is not None: args['prompt_embeds'] = prompt_embed @@ -261,7 +258,7 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro for i in range(len(decoded)): images.save_image(decoded[i], path=p.outpath_samples, basename="", seed=seeds[i], prompt=prompts[i], extension=shared.opts.samples_format, info=info, p=p, suffix="-before-refiner") - if (shared.opts.diffusers_move_base or shared.cmd_opts.medvram or shared.opts.diffusers_model_cpu_offload) and not (shared.cmd_opts.lowvram or shared.opts.diffusers_seq_cpu_offload): + if shared.opts.diffusers_move_base and not shared.sd_model.has_accelerate: shared.log.debug('Diffusers: Moving base model to CPU') shared.sd_model.to(devices.cpu) devices.torch_gc() diff --git a/modules/sd_models.py b/modules/sd_models.py index 03325d4a9..9bf65d77e 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -696,7 +696,7 @@ def load_diffuser(checkpoint_info=None, already_loaded_state_dict=None, timer=No if (shared.opts.diffusers_model_cpu_offload or shared.cmd_opts.medvram) and (shared.opts.diffusers_seq_cpu_offload or shared.cmd_opts.lowvram): shared.log.warning(f'Diffusers {op}: Model CPU offload (--medvram) and Sequential CPU offload (--lowvram) are not compatible') - shared.log.debug(f'Diffusers {op}: disable model CPU offload and --medvram') + shared.log.debug(f'Diffusers {op}: disabling model CPU offload and --medvram') shared.opts.diffusers_model_cpu_offload=False shared.cmd_opts.medvram=False @@ -706,11 +706,21 @@ def load_diffuser(checkpoint_info=None, already_loaded_state_dict=None, timer=No if hasattr(sd_model, "enable_model_cpu_offload"): if (shared.cmd_opts.medvram and devices.backend != "directml") or shared.opts.diffusers_model_cpu_offload: shared.log.debug(f'Diffusers {op}: enable model CPU offload') + if shared.opts.diffusers_move_base or shared.opts.diffusers_move_unet or shared.opts.diffusers_move_refiner: + shared.opts.diffusers_move_base = False + shared.opts.diffusers_move_unet = False + shared.opts.diffusers_move_refiner = False + shared.log.warning(f'Disabling {op} "Move model to CPU" since "Model CPU offload" is enabled') sd_model.enable_model_cpu_offload() sd_model.has_accelerate = True if hasattr(sd_model, "enable_sequential_cpu_offload"): if shared.cmd_opts.lowvram or shared.opts.diffusers_seq_cpu_offload: shared.log.debug(f'Diffusers {op}: enable sequential CPU offload') + if shared.opts.diffusers_move_base or shared.opts.diffusers_move_unet or shared.opts.diffusers_move_refiner: + shared.opts.diffusers_move_base = False + shared.opts.diffusers_move_unet = False + shared.opts.diffusers_move_refiner = False + shared.log.warning(f'Disabling {op} "Move model to CPU" since "Sequential CPU offload" is enabled') sd_model.enable_sequential_cpu_offload(device=devices.device) sd_model.has_accelerate = True if hasattr(sd_model, "enable_vae_slicing"): @@ -760,10 +770,11 @@ def load_diffuser(checkpoint_info=None, already_loaded_state_dict=None, timer=No else: if not refiner_enough_vram and not (shared.opts.diffusers_move_base and shared.opts.diffusers_move_refiner): shared.log.warning(f"Insufficient GPU memory, using system memory as fallback: free={free_vram} GB") - shared.log.debug('Enabled moving base model to CPU') - shared.log.debug('Enabled moving refiner model to CPU') - shared.opts.diffusers_move_base=True - shared.opts.diffusers_move_refiner=True + if not shared.opts.shared.opts.diffusers_seq_cpu_offload and not shared.opts.diffusers_model_cpu_offload: + shared.log.debug('Enabled moving base model to CPU') + shared.log.debug('Enabled moving refiner model to CPU') + shared.opts.diffusers_move_base=True + shared.opts.diffusers_move_refiner=True shared.log.debug('Moving base model to CPU') model_data.sd_model.to(devices.cpu) devices.torch_gc(force=True) diff --git a/modules/sd_vae.py b/modules/sd_vae.py index 317906001..07f3a6600 100644 --- a/modules/sd_vae.py +++ b/modules/sd_vae.py @@ -124,6 +124,9 @@ def resolve_vae(checkpoint_file): return vae_dict[basename], 'in VAE dir' else: vae_from_options = vae_dict.get(shared.opts.sd_vae, None) # 5th + if vae_from_options is not None: + return vae_from_options, 'specified in settings' + vae_from_options = vae_dict.get(shared.opts.sd_vae + '.safetensors', None) # 6th if vae_from_options is not None: return vae_from_options, 'specified in settings' shared.log.warning(f"VAE not found: {shared.opts.sd_vae}") @@ -188,10 +191,8 @@ def load_vae_diffusers(model_file, vae_file=None, vae_source="from unknown sourc pass else: diffusers_load_config['variant'] = shared.opts.diffusers_vae_load_variant - if shared.opts.diffusers_vae_upcast != 'default': diffusers_load_config['force_upcast'] = True if shared.opts.diffusers_vae_upcast == 'true' else False - shared.log.debug(f'Diffusers VAE load config: {diffusers_load_config}') try: import diffusers @@ -251,8 +252,11 @@ def reload_vae_weights(sd_model=None, vae_file=unspecified): load_vae(sd_model, vae_file, vae_source) sd_hijack.model_hijack.hijack(sd_model) script_callbacks.model_loaded_callback(sd_model) + if vae_file is not None: + shared.log.info(f"VAE weights loaded: {vae_file}") + # else: + # load_vae_diffusers(model_file, vae_file, vae_source) if not shared.cmd_opts.lowvram and not shared.cmd_opts.medvram and not sd_model.has_accelerate: sd_model.to(devices.device) - shared.log.info(f"VAE weights loaded: {vae_file}") return sd_model diff --git a/modules/shared.py b/modules/shared.py index b1fcb7de4..be39df145 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -268,7 +268,7 @@ def list_themes(): def disable_extensions(): - if opts.lora_disable: + if opts.lyco_patch_lora: if 'Lora' not in opts.disabled_extensions: opts.data['disabled_extensions'].append('Lora') else: @@ -403,8 +403,8 @@ options_templates.update(options_section(('diffusers', "Diffusers Settings"), { "diffusers_move_refiner": OptionInfo(True, "Move refiner model to CPU when not in use"), "diffusers_extract_ema": OptionInfo(True, "Use model EMA weights when possible"), "diffusers_generator_device": OptionInfo("default", "Generator device", gr.Radio, lambda: {"choices": ["default", "cpu"]}), - "diffusers_seq_cpu_offload": OptionInfo(False, "Enable sequential CPU offload"), - "diffusers_model_cpu_offload": OptionInfo(False, "Enable model CPU offload"), + "diffusers_model_cpu_offload": OptionInfo(False, "Enable model CPU offload (--medvram)"), + "diffusers_seq_cpu_offload": OptionInfo(False, "Enable sequential CPU offload (--lowvram)"), "diffusers_vae_upcast": OptionInfo("default", "VAE upcasting", gr.Radio, lambda: {"choices": ['default', 'true', 'false']}), "diffusers_vae_slicing": OptionInfo(True, "Enable VAE slicing"), "diffusers_vae_tiling": OptionInfo(False, "Enable VAE tiling"), @@ -627,7 +627,7 @@ options_templates.update(options_section(('extra_networks', "Extra Networks"), { "extra_networks_card_fit": OptionInfo("cover", "UI image contain method", gr.Radio, lambda: {"choices": ["contain", "cover", "fill"]}), "extra_network_skip_indexing": OptionInfo(False, "Do not automatically build extra network pages", gr.Checkbox), "lyco_patch_lora": OptionInfo(False, "Use LyCoris handler for all Lora types", gr.Checkbox), - "lora_disable": OptionInfo(False, "Disable built-in Lora handler", gr.Checkbox, { "visible": True }, onchange=disable_extensions), + # "lora_disable": OptionInfo(False, "Disable built-in Lora handler", gr.Checkbox, { "visible": True }, onchange=disable_extensions), "lora_functional": OptionInfo(False, "Use Kohya method for handling multiple Loras", gr.Checkbox), "extra_networks_add_text_separator": OptionInfo(" ", "Extra text to add before <...> when adding extra network to prompt", gr.Text, { "visible": False }), "extra_networks_default_multiplier": OptionInfo(1.0, "Multiplier for extra networks", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), diff --git a/modules/ui_extra_networks.py b/modules/ui_extra_networks.py index 7e42e453d..3ef1937b1 100644 --- a/modules/ui_extra_networks.py +++ b/modules/ui_extra_networks.py @@ -11,9 +11,6 @@ from PIL import Image from modules import shared, scripts, modelloader from modules.generation_parameters_copypaste import image_from_url_text from modules.ui_components import ToolButton -from logging import DEBUG -from time import time -from rich.progress import Progress, TextColumn, BarColumn, TaskProgressColumn, TimeRemainingColumn, TimeElapsedColumn, SpinnerColumn extra_pages = [] allowed_dirs = set() @@ -161,8 +158,8 @@ class ExtraNetworksPage: return f"
Extra network page not ready
Click refresh to try again
" subdirs = {} allowed_folders = [os.path.abspath(x) for x in self.allowed_directories_for_previews()] - for parentdir, dirs in {dir: modelloader.directory_directories(dir) for dir in allowed_folders}.items(): - for dir in dirs.keys(): + for parentdir, dirs in {dir: modelloader.directory_directories(dir) for dir in allowed_folders}.items(): # pylint: disable=redefined-builtin + for dir in dirs.keys(): # pylint: disable=redefined-builtin if shared.opts.diffusers_dir in dir: subdirs[os.path.basename(shared.opts.diffusers_dir)] = 1 if 'models--' in dir: @@ -191,23 +188,11 @@ class ExtraNetworksPage: shared.log.error(f'Extra networks error listing items: {self.__class__}') self.create_xyz_grid() htmls = [] - with Progress( - SpinnerColumn(), - TextColumn('[cyan]Creating Extra Network '+self.title+' HTML - {task.description}'), - BarColumn(), TaskProgressColumn(), TextColumn('({task.completed}/{task.total})'), - TimeRemainingColumn(), TimeElapsedColumn(), transient=not shared.log.isEnabledFor(DEBUG), expand=True - ) as progress: - task = progress.add_task(description='Initializing Items') - items = self.items - progress.update(task, total=len(items)) - __t = time() - __i = 0 - for item in items: - __i += 1 - self.metadata[item["name"]] = item.get("metadata", {}) - self.info[item["name"]] = self.find_info(item['filename']) - htmls.append(self.create_html_for_item(item, tabname)) - progress.update(task, advance=1, description=f"{round(__i/(shared.time.time()-__t))} item/s") + items = self.items + for item in items: + self.metadata[item["name"]] = item.get("metadata", {}) + self.info[item["name"]] = self.find_info(item['filename']) + htmls.append(self.create_html_for_item(item, tabname)) self.html += ''.join(htmls) if len(subdirs_html) > 0 or len(self.html) > 0: res = f"
{subdirs_html}
{self.html}
" @@ -262,7 +247,7 @@ class ExtraNetworksPage: def find_preview(self, path): preview_extensions = ["jpg", "jpeg", "png", "webp", "tiff", "jp2"] - dir = os.path.dirname(path) + dir = os.path.dirname(path) # pylint: disable=redefined-builtin paths = modelloader.directory_directories(dir, recursive=False) for file in [f'{path}.thumb.{ext}' for ext in preview_extensions]: # use thumbnail if exists if file in paths[dir][1] and os.path.exists(file): @@ -274,7 +259,7 @@ class ExtraNetworksPage: return self.link_preview('html/card-no-preview.png') def find_description(self, path): - dir = os.path.dirname(path) + dir = os.path.dirname(path) # pylint: disable=redefined-builtin paths = modelloader.directory_directories(dir, recursive=False) for file in [f"{path}.txt", f"{path}.description.txt"]: if file in paths[dir][1]: @@ -288,7 +273,7 @@ class ExtraNetworksPage: return None def find_info(self, path): - dir = os.path.dirname(path) + dir = os.path.dirname(path) # pylint: disable=redefined-builtin paths = modelloader.directory_directories(dir, recursive=False) basename, _ext = os.path.splitext(path) for file in [f"{path}.info", f"{path}.civitai.info", f"{basename}.info", f"{basename}.civitai.info"]: diff --git a/modules/ui_extra_networks_checkpoints.py b/modules/ui_extra_networks_checkpoints.py index 37bee332b..43f9c1907 100644 --- a/modules/ui_extra_networks_checkpoints.py +++ b/modules/ui_extra_networks_checkpoints.py @@ -16,6 +16,8 @@ class ExtraNetworksPageCheckpoints(ui_extra_networks.ExtraNetworksPage): checkpoint: sd_models.CheckpointInfo for name, checkpoint in sd_models.checkpoints_list.items(): path, _ext = os.path.splitext(checkpoint.filename) + if not os.path.exists(path) and sd_models.model_path not in path: + path = os.path.abspath(os.path.join(checkpoint.path, os.pardir, os.pardir)) yield { "name": checkpoint.name_for_extra, "filename": path, diff --git a/requirements.txt b/requirements.txt index 373984093..098ba25a4 100644 --- a/requirements.txt +++ b/requirements.txt @@ -46,7 +46,7 @@ requests==2.31.0 tqdm==4.65.0 accelerate==0.20.3 opencv-python-headless==4.7.0.72 -diffusers==0.19.3 +diffusers==0.20.0 einops==0.4.1 gradio==3.32.0 huggingface_hub==0.16.4 diff --git a/wiki b/wiki index 625f3d53f..fd5c18037 160000 --- a/wiki +++ b/wiki @@ -1 +1 @@ -Subproject commit 625f3d53f99babf329166268b4c4c0c4c209801b +Subproject commit fd5c18037d51aca2e7c7d72f1c0f9182fe9a37ed