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refactor: add step before parsing to set data in parser

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- add constructor for MetadataSchema class
- remove showable and copyable from log output
- add functional hash cache (model hashing takes about 5 seconds, only required once per model, using hash lazy loading)
This commit is contained in:
Manuel Schmid
2024-02-02 01:25:47 +01:00
parent 796cf3c78d
commit e55870124b
3 changed files with 126 additions and 101 deletions
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modules/async_worker.py
+30 -48
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@@ -42,9 +42,10 @@ def worker():
from modules.private_logger import log
from extras.expansion import safe_str
from modules.util import remove_empty_str, HWC3, resize_image, \
get_image_shape_ceil, set_image_shape_ceil, get_shape_ceil, resample_image, erode_or_dilate, calculate_sha256
get_image_shape_ceil, set_image_shape_ceil, get_shape_ceil, resample_image, erode_or_dilate
from modules.upscaler import perform_upscale
from modules.flags import Performance, MetadataScheme, lora_count
from modules.flags import Performance, lora_count
from modules.metadata import get_metadata_parser, MetadataScheme
try:
async_gradio_app = shared.gradio_root
@@ -193,18 +194,6 @@ def worker():
modules.patch.negative_adm_scale = advanced_parameters.adm_scaler_negative = 1.0
modules.patch.adm_scaler_end = advanced_parameters.adm_scaler_end = 0.0
# TODO move hashing to metadata mapper as this slows down the generation process
base_model_path = os.path.join(modules.config.path_checkpoints, base_model_name)
base_model_hash = calculate_sha256(base_model_path)
refiner_model_path = os.path.join(modules.config.path_checkpoints, refiner_model_name)
refiner_model_hash = calculate_sha256(refiner_model_path) if refiner_model_name != 'None' else ''
lora_hashes = []
for (n, w) in loras:
lora_path = os.path.join(modules.config.path_loras, n) if n != 'None' else ''
lora_hashes.append(calculate_sha256(lora_path) if n != 'None' else '')
modules.patch.adaptive_cfg = advanced_parameters.adaptive_cfg
print(f'[Parameters] Adaptive CFG = {modules.patch.adaptive_cfg}')
@@ -777,61 +766,54 @@ def worker():
imgs = [inpaint_worker.current_task.post_process(x) for x in imgs]
for x in imgs:
d = [('Prompt', 'prompt', task['log_positive_prompt'], True, True),
('Full Positive Prompt', 'full_prompt', task['positive'], False, False),
('Negative Prompt', 'negative_prompt', task['log_negative_prompt'], True, True),
('Full Negative Prompt', 'full_negative_prompt', task['negative'], False, False),
('Fooocus V2 Expansion', 'prompt_expansion', task['expansion'], True, True),
('Styles', 'styles', str(raw_style_selections), True, True),
('Performance', 'performance', performance_selection.value, True, True),
('Steps', 'steps', steps, False, False),
('Resolution', 'resolution', str((width, height)), True, True),
('Guidance Scale', 'guidance_scale', guidance_scale, True, True),
('Sharpness', 'sharpness', sharpness, True, True),
d = [('Prompt', 'prompt', task['log_positive_prompt']),
('Negative Prompt', 'negative_prompt', task['log_negative_prompt']),
('Fooocus V2 Expansion', 'prompt_expansion', task['expansion']),
('Styles', 'styles', str(raw_style_selections)),
('Performance', 'performance', performance_selection.value),
('Resolution', 'resolution', str((width, height))),
('Guidance Scale', 'guidance_scale', guidance_scale),
('Sharpness', 'sharpness', sharpness),
('ADM Guidance', 'adm_guidance', str((
modules.patch.positive_adm_scale,
modules.patch.negative_adm_scale,
modules.patch.adm_scaler_end)), True, True),
('Base Model', 'base_model', base_model_name, True, True),
('Base Model Hash', 'base_model_hash', base_model_hash, False, False), # TODO move to metadata and use cache
('Refiner Model', 'refiner_model', refiner_model_name, True, True),
('Refiner Model Hash', 'refiner_model_hash', refiner_model_hash, False, False), # TODO move to metadata and use cache
('Refiner Switch', 'refiner_switch', refiner_switch, True, True)]
modules.patch.adm_scaler_end))),
('Base Model', 'base_model', base_model_name),
('Refiner Model', 'refiner_model', refiner_model_name),
('Refiner Switch', 'refiner_switch', refiner_switch)]
# TODO evaluate if this should always be added
if refiner_model_name != 'None':
if advanced_parameters.overwrite_switch > 0:
d.append(('Overwrite Switch', 'overwrite_switch', advanced_parameters.overwrite_switch, True, True))
d.append(('Overwrite Switch', 'overwrite_switch', advanced_parameters.overwrite_switch))
if refiner_swap_method != flags.refiner_swap_method:
d.append(('Refiner Swap Method', 'refiner_swap_method', refiner_swap_method, True, True))
d.append(('Refiner Swap Method', 'refiner_swap_method', refiner_swap_method))
if advanced_parameters.adaptive_cfg != modules.config.default_cfg_tsnr:
d.append(('CFG Mimicking from TSNR', 'adaptive_cfg', advanced_parameters.adaptive_cfg, True, True))
d.append(('CFG Mimicking from TSNR', 'adaptive_cfg', advanced_parameters.adaptive_cfg))
d.append(('Sampler', 'sampler', sampler_name, True, True))
d.append(('Scheduler', 'scheduler', scheduler_name, True, True))
d.append(('Seed', 'seed', task['task_seed'], True, True))
d.append(('Sampler', 'sampler', sampler_name))
d.append(('Scheduler', 'scheduler', scheduler_name))
d.append(('Seed', 'seed', task['task_seed']))
if advanced_parameters.freeu_enabled:
d.append(('FreeU', 'freeu', str((
advanced_parameters.freeu_b1,
advanced_parameters.freeu_b2,
advanced_parameters.freeu_s1,
advanced_parameters.freeu_s2)), True, True))
advanced_parameters.freeu_s2))))
metadata_parser = None
if save_metadata_to_images:
metadata_parser = modules.metadata.get_metadata_parser(metadata_scheme)
metadata_parser.set_data(task['positive'], task['negative'], steps, base_model_name, refiner_model_name, loras)
for li, (n, w) in enumerate(loras):
if n != 'None':
d.append((f'LoRA {li + 1}', f'lora_combined_{li + 1}', f'{n} : {w}', True, True))
d.append((f'LoRA {li + 1} Name', f'lora_name_{li + 1}', n, False, False))
d.append((f'LoRA {li + 1} Weight', f'lora_weight_{li + 1}', w, False, False))
# TODO move hashes to metadata handling
d.append((f'LoRA {li + 1} Hash', f'lora_hash_{li + 1}', lora_hashes[li], False, False))
d.append((f'LoRA {li + 1}', f'lora_combined_{li + 1}', f'{n} : {w}'))
d.append(('Version', 'version', 'Fooocus v' + fooocus_version.version, True, True))
d.append(('Version', 'version', 'Fooocus v' + fooocus_version.version))
if modules.config.metadata_created_by != '':
d.append(('Created By', 'created_by', modules.config.metadata_created_by, False, False))
log(x, d, save_metadata_to_images, metadata_scheme)
log(x, d, metadata_parser)
yield_result(async_task, imgs, do_not_show_finished_images=len(tasks) == 1)
except ldm_patched.modules.model_management.InterruptProcessingException as e: