diff --git a/modules/async_worker.py b/modules/async_worker.py index d7d9b9fd..9c16d6fc 100644 --- a/modules/async_worker.py +++ b/modules/async_worker.py @@ -462,8 +462,10 @@ def worker(): progressbar(async_task, 2, 'Loading models ...') - loras, prompt = parse_lora_references_from_prompt(prompt, loras, modules.config.default_max_lora_number) + lora_filenames = modules.util.remove_performance_lora(modules.config.lora_filenames, performance_selection) + loras, prompt = parse_lora_references_from_prompt(prompt, loras, modules.config.default_max_lora_number, lora_filenames=lora_filenames) loras += performance_loras + pipeline.refresh_everything(refiner_model_name=refiner_model_name, base_model_name=base_model_name, loras=loras, base_model_additional_loras=base_model_additional_loras, use_synthetic_refiner=use_synthetic_refiner, vae_name=vae_name) diff --git a/modules/config.py b/modules/config.py index cb651c5b..29a16d6d 100644 --- a/modules/config.py +++ b/modules/config.py @@ -548,25 +548,9 @@ with open(config_example_path, "w", encoding="utf-8") as json_file: model_filenames = [] lora_filenames = [] -lora_filenames_no_special = [] vae_filenames = [] wildcard_filenames = [] -sdxl_lcm_lora = 'sdxl_lcm_lora.safetensors' -sdxl_lightning_lora = 'sdxl_lightning_4step_lora.safetensors' -sdxl_hyper_sd_lora = 'sdxl_hyper_sd_4step_lora.safetensors' -loras_metadata_remove = [sdxl_lcm_lora, sdxl_lightning_lora, sdxl_hyper_sd_lora] - - -def remove_special_loras(lora_filenames): - global loras_metadata_remove - - loras_no_special = lora_filenames.copy() - for lora_to_remove in loras_metadata_remove: - if lora_to_remove in loras_no_special: - loras_no_special.remove(lora_to_remove) - return loras_no_special - def get_model_filenames(folder_paths, extensions=None, name_filter=None): if extensions is None: @@ -582,10 +566,9 @@ def get_model_filenames(folder_paths, extensions=None, name_filter=None): def update_files(): - global model_filenames, lora_filenames, lora_filenames_no_special, vae_filenames, wildcard_filenames, available_presets + global model_filenames, lora_filenames, vae_filenames, wildcard_filenames, available_presets model_filenames = get_model_filenames(paths_checkpoints) lora_filenames = get_model_filenames(paths_loras) - lora_filenames_no_special = remove_special_loras(lora_filenames) vae_filenames = get_model_filenames(path_vae) wildcard_filenames = get_files_from_folder(path_wildcards, ['.txt']) available_presets = get_presets() @@ -634,26 +617,27 @@ def downloading_sdxl_lcm_lora(): load_file_from_url( url='https://huggingface.co/lllyasviel/misc/resolve/main/sdxl_lcm_lora.safetensors', model_dir=paths_loras[0], - file_name=sdxl_lcm_lora + file_name=modules.flags.PerformanceLoRA.EXTREME_SPEED.value ) - return sdxl_lcm_lora + return modules.flags.PerformanceLoRA.EXTREME_SPEED.value + def downloading_sdxl_lightning_lora(): load_file_from_url( url='https://huggingface.co/mashb1t/misc/resolve/main/sdxl_lightning_4step_lora.safetensors', model_dir=paths_loras[0], - file_name=sdxl_lightning_lora + file_name=modules.flags.PerformanceLoRA.LIGHTNING.value ) - return sdxl_lightning_lora + return modules.flags.PerformanceLoRA.LIGHTNING.value def downloading_sdxl_hyper_sd_lora(): load_file_from_url( url='https://huggingface.co/mashb1t/misc/resolve/main/sdxl_hyper_sd_4step_lora.safetensors', model_dir=paths_loras[0], - file_name=sdxl_hyper_sd_lora + file_name=modules.flags.PerformanceLoRA.HYPER_SD.value ) - return sdxl_hyper_sd_lora + return modules.flags.PerformanceLoRA.HYPER_SD.value def downloading_controlnet_canny(): diff --git a/modules/flags.py b/modules/flags.py index e48052e1..25b0caae 100644 --- a/modules/flags.py +++ b/modules/flags.py @@ -48,7 +48,8 @@ SAMPLERS = KSAMPLER | SAMPLER_EXTRA KSAMPLER_NAMES = list(KSAMPLER.keys()) -SCHEDULER_NAMES = ["normal", "karras", "exponential", "sgm_uniform", "simple", "ddim_uniform", "lcm", "turbo", "align_your_steps", "tcd"] +SCHEDULER_NAMES = ["normal", "karras", "exponential", "sgm_uniform", "simple", "ddim_uniform", "lcm", "turbo", + "align_your_steps", "tcd"] SAMPLER_NAMES = KSAMPLER_NAMES + list(SAMPLER_EXTRA.keys()) sampler_list = SAMPLER_NAMES @@ -91,6 +92,7 @@ sdxl_aspect_ratios = [ '1664*576', '1728*576' ] + class MetadataScheme(Enum): FOOOCUS = 'fooocus' A1111 = 'a1111' @@ -115,6 +117,14 @@ class OutputFormat(Enum): return list(map(lambda c: c.value, cls)) +class PerformanceLoRA(Enum): + QUALITY = None + SPEED = None + EXTREME_SPEED = 'sdxl_lcm_lora.safetensors' + LIGHTNING = 'sdxl_lightning_4step_lora.safetensors' + HYPER_SD = 'sdxl_hyper_sd_4step_lora.safetensors' + + class Steps(IntEnum): QUALITY = 60 SPEED = 30 @@ -142,6 +152,10 @@ class Performance(Enum): def list(cls) -> list: return list(map(lambda c: c.value, cls)) + @classmethod + def by_steps(cls, steps: int | str): + return cls[Steps(int(steps)).name] + @classmethod def has_restricted_features(cls, x) -> bool: if isinstance(x, Performance): @@ -149,7 +163,10 @@ class Performance(Enum): return x in [cls.EXTREME_SPEED.value, cls.LIGHTNING.value, cls.HYPER_SD.value] def steps(self) -> int | None: - return Steps[self.name].value if Steps[self.name] else None + return Steps[self.name].value if self.name in Steps.__members__ else None def steps_uov(self) -> int | None: - return StepsUOV[self.name].value if Steps[self.name] else None + return StepsUOV[self.name].value if self.name in StepsUOV.__members__ else None + + def lora_filename(self) -> str | None: + return PerformanceLoRA[self.name].value if self.name in PerformanceLoRA.__members__ else None diff --git a/modules/meta_parser.py b/modules/meta_parser.py index 586e62da..0d509a19 100644 --- a/modules/meta_parser.py +++ b/modules/meta_parser.py @@ -32,7 +32,7 @@ def load_parameter_button_click(raw_metadata: dict | str, is_generating: bool): get_str('prompt', 'Prompt', loaded_parameter_dict, results) get_str('negative_prompt', 'Negative Prompt', loaded_parameter_dict, results) get_list('styles', 'Styles', loaded_parameter_dict, results) - get_str('performance', 'Performance', loaded_parameter_dict, results) + performance = get_str('performance', 'Performance', loaded_parameter_dict, results) get_steps('steps', 'Steps', loaded_parameter_dict, results) get_number('overwrite_switch', 'Overwrite Switch', loaded_parameter_dict, results) get_resolution('resolution', 'Resolution', loaded_parameter_dict, results) @@ -59,19 +59,27 @@ def load_parameter_button_click(raw_metadata: dict | str, is_generating: bool): get_freeu('freeu', 'FreeU', loaded_parameter_dict, results) + # prevent performance LoRAs to be added twice, by performance and by lora + performance_filename = None + if performance is not None and performance in Performance.list(): + performance = Performance(performance) + performance_filename = performance.lora_filename() + for i in range(modules.config.default_max_lora_number): - get_lora(f'lora_combined_{i + 1}', f'LoRA {i + 1}', loaded_parameter_dict, results) + get_lora(f'lora_combined_{i + 1}', f'LoRA {i + 1}', loaded_parameter_dict, results, performance_filename) return results -def get_str(key: str, fallback: str | None, source_dict: dict, results: list, default=None): +def get_str(key: str, fallback: str | None, source_dict: dict, results: list, default=None) -> str | None: try: h = source_dict.get(key, source_dict.get(fallback, default)) assert isinstance(h, str) results.append(h) + return h except: results.append(gr.update()) + return None def get_list(key: str, fallback: str | None, source_dict: dict, results: list, default=None): @@ -181,7 +189,7 @@ def get_freeu(key: str, fallback: str | None, source_dict: dict, results: list, results.append(gr.update()) -def get_lora(key: str, fallback: str | None, source_dict: dict, results: list): +def get_lora(key: str, fallback: str | None, source_dict: dict, results: list, performance_filename: str | None): try: split_data = source_dict.get(key, source_dict.get(fallback)).split(' : ') enabled = True @@ -193,6 +201,9 @@ def get_lora(key: str, fallback: str | None, source_dict: dict, results: list): name = split_data[1] weight = split_data[2] + if name == performance_filename: + raise Exception + weight = float(weight) results.append(enabled) results.append(name) @@ -248,7 +259,7 @@ class MetadataParser(ABC): self.full_prompt: str = '' self.raw_negative_prompt: str = '' self.full_negative_prompt: str = '' - self.steps: int = 30 + self.steps: int = Steps.SPEED.value self.base_model_name: str = '' self.base_model_hash: str = '' self.refiner_model_name: str = '' @@ -261,11 +272,11 @@ class MetadataParser(ABC): raise NotImplementedError @abstractmethod - def parse_json(self, metadata: dict | str) -> dict: + def to_json(self, metadata: dict | str) -> dict: raise NotImplementedError @abstractmethod - def parse_string(self, metadata: dict) -> str: + def to_string(self, metadata: dict) -> str: raise NotImplementedError def set_data(self, raw_prompt, full_prompt, raw_negative_prompt, full_negative_prompt, steps, base_model_name, @@ -328,7 +339,7 @@ class A1111MetadataParser(MetadataParser): 'version': 'Version' } - def parse_json(self, metadata: str) -> dict: + def to_json(self, metadata: str) -> dict: metadata_prompt = '' metadata_negative_prompt = '' @@ -382,9 +393,9 @@ class A1111MetadataParser(MetadataParser): data['styles'] = str(found_styles) # try to load performance based on steps, fallback for direct A1111 imports - if 'steps' in data and 'performance' not in data: + if 'steps' in data and 'performance' in data is None: try: - data['performance'] = Performance[Steps(int(data['steps'])).name].value + data['performance'] = Performance.by_steps(data['steps']).value except ValueError | KeyError: pass @@ -414,7 +425,7 @@ class A1111MetadataParser(MetadataParser): lora_split = lora.split(': ') lora_name = lora_split[0] lora_weight = lora_split[2] if len(lora_split) == 3 else lora_split[1] - for filename in modules.config.lora_filenames_no_special: + for filename in modules.config.lora_filenames: path = Path(filename) if lora_name == path.stem: data[f'lora_combined_{li + 1}'] = f'{filename} : {lora_weight}' @@ -422,7 +433,7 @@ class A1111MetadataParser(MetadataParser): return data - def parse_string(self, metadata: dict) -> str: + def to_string(self, metadata: dict) -> str: data = {k: v for _, k, v in metadata} width, height = eval(data['resolution']) @@ -502,14 +513,14 @@ class FooocusMetadataParser(MetadataParser): def get_scheme(self) -> MetadataScheme: return MetadataScheme.FOOOCUS - def parse_json(self, metadata: dict) -> dict: + def to_json(self, metadata: dict) -> dict: for key, value in metadata.items(): if value in ['', 'None']: continue if key in ['base_model', 'refiner_model']: metadata[key] = self.replace_value_with_filename(key, value, modules.config.model_filenames) elif key.startswith('lora_combined_'): - metadata[key] = self.replace_value_with_filename(key, value, modules.config.lora_filenames_no_special) + metadata[key] = self.replace_value_with_filename(key, value, modules.config.lora_filenames) elif key == 'vae': metadata[key] = self.replace_value_with_filename(key, value, modules.config.vae_filenames) else: @@ -517,7 +528,7 @@ class FooocusMetadataParser(MetadataParser): return metadata - def parse_string(self, metadata: list) -> str: + def to_string(self, metadata: list) -> str: for li, (label, key, value) in enumerate(metadata): # remove model folder paths from metadata if key.startswith('lora_combined_'): @@ -557,6 +568,8 @@ class FooocusMetadataParser(MetadataParser): elif value == path.stem: return filename + return None + def get_metadata_parser(metadata_scheme: MetadataScheme) -> MetadataParser: match metadata_scheme: diff --git a/modules/private_logger.py b/modules/private_logger.py index eb8f0cc5..6fdb680c 100644 --- a/modules/private_logger.py +++ b/modules/private_logger.py @@ -27,7 +27,7 @@ def log(img, metadata, metadata_parser: MetadataParser | None = None, output_for date_string, local_temp_filename, only_name = generate_temp_filename(folder=path_outputs, extension=output_format) os.makedirs(os.path.dirname(local_temp_filename), exist_ok=True) - parsed_parameters = metadata_parser.parse_string(metadata.copy()) if metadata_parser is not None else '' + parsed_parameters = metadata_parser.to_string(metadata.copy()) if metadata_parser is not None else '' image = Image.fromarray(img) if output_format == OutputFormat.PNG.value: diff --git a/modules/util.py b/modules/util.py index 8317dd50..5003f79a 100644 --- a/modules/util.py +++ b/modules/util.py @@ -16,6 +16,7 @@ from PIL import Image import modules.config import modules.sdxl_styles +from modules.flags import Performance LANCZOS = (Image.Resampling.LANCZOS if hasattr(Image, 'Resampling') else Image.LANCZOS) @@ -381,9 +382,6 @@ def get_file_from_folder_list(name, folders): return os.path.abspath(os.path.realpath(os.path.join(folders[0], name))) -def ordinal_suffix(number: int) -> str: - return 'th' if 10 <= number % 100 <= 20 else {1: 'st', 2: 'nd', 3: 'rd'}.get(number % 10, 'th') - def makedirs_with_log(path): try: @@ -397,10 +395,15 @@ def get_enabled_loras(loras: list, remove_none=True) -> list: def parse_lora_references_from_prompt(prompt: str, loras: List[Tuple[AnyStr, float]], loras_limit: int = 5, - skip_file_check=False, prompt_cleanup=True, deduplicate_loras=True) -> tuple[List[Tuple[AnyStr, float]], str]: + skip_file_check=False, prompt_cleanup=True, deduplicate_loras=True, + lora_filenames=None) -> tuple[List[Tuple[AnyStr, float]], str]: + if lora_filenames is None: + lora_filenames = [] + found_loras = [] prompt_without_loras = '' cleaned_prompt = '' + for token in prompt.split(','): matches = LORAS_PROMPT_PATTERN.findall(token) @@ -410,7 +413,7 @@ def parse_lora_references_from_prompt(prompt: str, loras: List[Tuple[AnyStr, flo for match in matches: lora_name = match[1] + '.safetensors' if not skip_file_check: - lora_name = get_filname_by_stem(match[1], modules.config.lora_filenames_no_special) + lora_name = get_filname_by_stem(match[1], lora_filenames) if lora_name is not None: found_loras.append((lora_name, float(match[2]))) token = token.replace(match[0], '') @@ -440,6 +443,22 @@ def parse_lora_references_from_prompt(prompt: str, loras: List[Tuple[AnyStr, flo return updated_loras[:loras_limit], cleaned_prompt +def remove_performance_lora(filenames: list, performance: Performance | None): + loras_without_performance = filenames.copy() + + if performance is None: + return loras_without_performance + + performance_lora = performance.lora_filename() + + for filename in filenames: + path = Path(filename) + if performance_lora == path.name: + loras_without_performance.remove(filename) + + return loras_without_performance + + def cleanup_prompt(prompt): prompt = re.sub(' +', ' ', prompt) prompt = re.sub(',+', ',', prompt) diff --git a/tests/test_utils.py b/tests/test_utils.py index 6fd550db..c1f49c13 100644 --- a/tests/test_utils.py +++ b/tests/test_utils.py @@ -1,5 +1,7 @@ +import os import unittest +import modules.flags from modules import util @@ -77,5 +79,59 @@ class TestUtils(unittest.TestCase): for test in test_cases: prompt, loras, loras_limit, skip_file_check = test["input"] expected = test["output"] - actual = util.parse_lora_references_from_prompt(prompt, loras, loras_limit=loras_limit, skip_file_check=skip_file_check) + actual = util.parse_lora_references_from_prompt(prompt, loras, loras_limit=loras_limit, + skip_file_check=skip_file_check) + self.assertEqual(expected, actual) + + def test_can_parse_tokens_and_strip_performance_lora(self): + lora_filenames = [ + 'hey-lora.safetensors', + modules.flags.PerformanceLoRA.EXTREME_SPEED.value, + modules.flags.PerformanceLoRA.LIGHTNING.value, + os.path.join('subfolder', modules.flags.PerformanceLoRA.HYPER_SD.value) + ] + + test_cases = [ + { + "input": ("some prompt, ", [], 5, True, modules.flags.Performance.QUALITY), + "output": ( + [('hey-lora.safetensors', 0.4)], + 'some prompt' + ), + }, + { + "input": ("some prompt, ", [], 5, True, modules.flags.Performance.SPEED), + "output": ( + [('hey-lora.safetensors', 0.4)], + 'some prompt' + ), + }, + { + "input": ("some prompt, , ", [], 5, True, modules.flags.Performance.EXTREME_SPEED), + "output": ( + [('hey-lora.safetensors', 0.4)], + 'some prompt' + ), + }, + { + "input": ("some prompt, , ", [], 5, True, modules.flags.Performance.LIGHTNING), + "output": ( + [('hey-lora.safetensors', 0.4)], + 'some prompt' + ), + }, + { + "input": ("some prompt, , ", [], 5, True, modules.flags.Performance.HYPER_SD), + "output": ( + [('hey-lora.safetensors', 0.4)], + 'some prompt' + ), + } + ] + + for test in test_cases: + prompt, loras, loras_limit, skip_file_check, performance = test["input"] + lora_filenames = modules.util.remove_performance_lora(lora_filenames, performance) + expected = test["output"] + actual = util.parse_lora_references_from_prompt(prompt, loras, loras_limit=loras_limit, lora_filenames=lora_filenames) self.assertEqual(expected, actual) diff --git a/webui.py b/webui.py index 0dd86350..6f08757d 100644 --- a/webui.py +++ b/webui.py @@ -461,8 +461,8 @@ with shared.gradio_root: interactive=not modules.config.default_black_out_nsfw, info='Disable preview during generation.') disable_intermediate_results = gr.Checkbox(label='Disable Intermediate Results', - value=modules.config.default_performance == flags.Performance.EXTREME_SPEED.value, - interactive=modules.config.default_performance != flags.Performance.EXTREME_SPEED.value, + value=flags.Performance.has_restricted_features(modules.config.default_performance), + interactive=not flags.Performance.has_restricted_features(modules.config.default_performance), info='Disable intermediate results during generation, only show final gallery.') disable_seed_increment = gr.Checkbox(label='Disable seed increment', info='Disable automatic seed increment when image number is > 1.', @@ -713,7 +713,7 @@ with shared.gradio_root: parsed_parameters = {} else: metadata_parser = modules.meta_parser.get_metadata_parser(metadata_scheme) - parsed_parameters = metadata_parser.parse_json(parameters) + parsed_parameters = metadata_parser.to_json(parameters) return modules.meta_parser.load_parameter_button_click(parsed_parameters, state_is_generating)