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Merge branch 'feature/optimize-performance-lora-filtering-in-metadata'

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# Conflicts:
#	modules/flags.py
#	modules/util.py
#	webui.py
This commit is contained in:
Manuel Schmid
2024-05-30 15:21:04 +02:00
parent f5863d878e 83ef32a88b
commit 5768330142
8 changed files with 142 additions and 48 deletions
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modules/meta_parser.py
+28 -15
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@@ -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)
@@ -247,7 +258,7 @@ 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 = ''
@@ -260,11 +271,11 @@ 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,
@@ -327,7 +338,7 @@ class A1111MetadataParser(MetadataParser):
'version': 'Version'
}
def parse_json(self, metadata: str) -> dict:
def to_json(self, metadata: str) -> dict:
metadata_prompt = ''
metadata_negative_prompt = ''
@@ -381,9 +392,9 @@ 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
@@ -413,7 +424,7 @@ 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}'
@@ -421,7 +432,7 @@ 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'])
@@ -501,14 +512,14 @@ 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:
@@ -516,7 +527,7 @@ 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_'):
@@ -556,6 +567,8 @@ class FooocusMetadataParser(MetadataParser):
elif value == path.stem:
return filename
return None
def get_metadata_parser(metadata_scheme: MetadataScheme) -> MetadataParser:
match metadata_scheme: