Foreign-Mirrors/Fooocus
1
0
Fork 0
mirror of https://github.com/lllyasviel/Fooocus.git synced 2026-08-16 13:13:16 +02:00
Code Issues Packages Projects Releases Wiki Activity

Merge remote-tracking branch 'upstream/main'

Browse Source
This commit is contained in:
Manuel Schmid
2024-05-27 00:30:53 +02:00
parent 08877666ba dfff9b7dcf
commit 4361e7e629
7 changed files with 44 additions and 12 deletions
Download Patch File Download Diff File Expand all files Collapse all files
modules/async_worker.py
+6
View File
@@ -177,6 +177,7 @@ def worker():
adm_scaler_negative = args.pop()
adm_scaler_end = args.pop()
adaptive_cfg = args.pop()
clip_skip = args.pop()
sampler_name = args.pop()
scheduler_name = args.pop()
vae_name = args.pop()
@@ -305,6 +306,7 @@ def worker():
negative_prompt = translate2en(negative_prompt, 'negative prompt')
print(f'[Parameters] Adaptive CFG = {adaptive_cfg}')
print(f'[Parameters] CLIP Skip = {clip_skip}')
print(f'[Parameters] Sharpness = {sharpness}')
print(f'[Parameters] ControlNet Softness = {controlnet_softness}')
print(f'[Parameters] ADM Scale = '
@@ -478,6 +480,8 @@ def worker():
loras=loras, base_model_additional_loras=base_model_additional_loras,
use_synthetic_refiner=use_synthetic_refiner, vae_name=vae_name)
pipeline.set_clip_skip(clip_skip)
progressbar(async_task, 3, 'Processing prompts ...')
tasks = []
@@ -937,6 +941,8 @@ def worker():
d.append(
('CFG Mimicking from TSNR', 'adaptive_cfg', modules.patch.patch_settings[pid].adaptive_cfg))
if clip_skip > 1:
d.append(('CLIP Skip', 'clip_skip', clip_skip))
d.append(('Sampler', 'sampler', sampler_name))
d.append(('Scheduler', 'scheduler', scheduler_name))
d.append(('VAE', 'vae', vae_name))
modules/config.py
+6
View File
@@ -436,6 +436,11 @@ default_cfg_tsnr = get_config_item_or_set_default(
default_value=7.0,
validator=lambda x: isinstance(x, numbers.Number)
)
default_clip_skip = get_config_item_or_set_default(
key='default_clip_skip',
default_value=2,
validator=lambda x: isinstance(x, int) and 1 <= x <= modules.flags.clip_skip_max
)
default_overwrite_step = get_config_item_or_set_default(
key='default_overwrite_step',
default_value=-1,
@@ -518,6 +523,7 @@ possible_preset_keys = {
"default_cfg_scale": "guidance_scale",
"default_sample_sharpness": "sharpness",
"default_cfg_tsnr": "adaptive_cfg",
"default_clip_skip": "clip_skip",
"default_sampler": "sampler",
"default_scheduler": "scheduler",
"default_overwrite_step": "steps",
modules/default_pipeline.py
+11
View File
@@ -201,6 +201,17 @@ def clip_encode(texts, pool_top_k=1):
return [[torch.cat(cond_list, dim=1), {"pooled_output": pooled_acc}]]
@torch.no_grad()
@torch.inference_mode()
def set_clip_skip(clip_skip: int):
global final_clip
if final_clip is None:
return
final_clip.clip_layer(-abs(clip_skip))
return
@torch.no_grad()
@torch.inference_mode()
def clear_all_caches():
modules/flags.py
+2
View File
@@ -54,6 +54,8 @@ SAMPLER_NAMES = KSAMPLER_NAMES + list(SAMPLER_EXTRA.keys())
sampler_list = SAMPLER_NAMES
scheduler_list = SCHEDULER_NAMES
clip_skip_max = 12
default_vae = 'Default (model)'
refiner_swap_method = 'joint'
modules/meta_parser.py
+10 -8
View File
@@ -34,16 +34,17 @@ def load_parameter_button_click(raw_metadata: dict | str, is_generating: bool):
get_list('styles', 'Styles', loaded_parameter_dict, results)
get_str('performance', 'Performance', loaded_parameter_dict, results)
get_steps('steps', 'Steps', loaded_parameter_dict, results)
get_float('overwrite_switch', 'Overwrite Switch', loaded_parameter_dict, results)
get_number('overwrite_switch', 'Overwrite Switch', loaded_parameter_dict, results)
get_resolution('resolution', 'Resolution', loaded_parameter_dict, results)
get_float('guidance_scale', 'Guidance Scale', loaded_parameter_dict, results)
get_float('sharpness', 'Sharpness', loaded_parameter_dict, results)
get_number('guidance_scale', 'Guidance Scale', loaded_parameter_dict, results)
get_number('sharpness', 'Sharpness', loaded_parameter_dict, results)
get_adm_guidance('adm_guidance', 'ADM Guidance', loaded_parameter_dict, results)
get_str('refiner_swap_method', 'Refiner Swap Method', loaded_parameter_dict, results)
get_float('adaptive_cfg', 'CFG Mimicking from TSNR', loaded_parameter_dict, results)
get_number('adaptive_cfg', 'CFG Mimicking from TSNR', loaded_parameter_dict, results)
get_number('clip_skip', 'CLIP Skip', loaded_parameter_dict, results, cast_type=int)
get_str('base_model', 'Base Model', loaded_parameter_dict, results)
get_str('refiner_model', 'Refiner Model', loaded_parameter_dict, results)
get_float('refiner_switch', 'Refiner Switch', loaded_parameter_dict, results)
get_number('refiner_switch', 'Refiner Switch', loaded_parameter_dict, results)
get_str('sampler', 'Sampler', loaded_parameter_dict, results)
get_str('scheduler', 'Scheduler', loaded_parameter_dict, results)
get_str('vae', 'VAE', loaded_parameter_dict, results)
@@ -83,11 +84,11 @@ def get_list(key: str, fallback: str | None, source_dict: dict, results: list, d
results.append(gr.update())
def get_float(key: str, fallback: str | None, source_dict: dict, results: list, default=None):
def get_number(key: str, fallback: str | None, source_dict: dict, results: list, default=None, cast_type=float):
try:
h = source_dict.get(key, source_dict.get(fallback, default))
assert h is not None
h = float(h)
h = cast_type(h)
results.append(h)
except:
results.append(gr.update())
@@ -313,6 +314,7 @@ class A1111MetadataParser(MetadataParser):
'adm_guidance': 'ADM Guidance',
'refiner_swap_method': 'Refiner Swap Method',
'adaptive_cfg': 'Adaptive CFG',
'clip_skip': 'Clip skip',
'overwrite_switch': 'Overwrite Switch',
'freeu': 'FreeU',
'base_model': 'Model',
@@ -457,7 +459,7 @@ class A1111MetadataParser(MetadataParser):
self.fooocus_to_a1111['refiner_model_hash']: self.refiner_model_hash
}
for key in ['adaptive_cfg', 'overwrite_switch', 'refiner_swap_method', 'freeu']:
for key in ['adaptive_cfg', 'clip_skip', 'overwrite_switch', 'refiner_swap_method', 'freeu']:
if key in data:
generation_params[self.fooocus_to_a1111[key]] = data[key]