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feat: map basic information for scheme A1111

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This commit is contained in:
Manuel Schmid
2024-01-28 18:04:40 +01:00
parent ee21c2b6bc
commit e19596c2df
3 changed files with 128 additions and 27 deletions
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modules/async_worker.py
+14 -11
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@@ -203,16 +203,16 @@ def worker():
modules.patch.adm_scaler_end = advanced_parameters.adm_scaler_end = 0.0
steps = 8
if save_metadata_to_images:
base_model_path = os.path.join(modules.config.path_checkpoints, base_model_name)
base_model_hash = calculate_sha256(base_model_path)[0:10]
base_model_path = os.path.join(modules.config.path_checkpoints, base_model_name)
base_model_hash = calculate_sha256(base_model_path)[0:10]
lora_hashes = []
for (n, w) in loras:
if n != 'None':
lora_path = os.path.join(modules.config.path_loras, n)
lora_hashes.append(f'{n.split(".")[0]}: {calculate_sha256(lora_path)[0:10]}')
lora_hashes_string = ", ".join(lora_hashes)
refiner_model_path = os.path.join(modules.config.path_checkpoints, refiner_model_name)
refiner_model_hash = calculate_sha256(refiner_model_path)[0:10] 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)[0:10] if n != 'None' else '')
modules.patch.adaptive_cfg = advanced_parameters.adaptive_cfg
print(f'[Parameters] Adaptive CFG = {modules.patch.adaptive_cfg}')
@@ -812,7 +812,9 @@ def worker():
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),
('Refiner Model', 'refiner_model', refiner_model_name, True, True),
('Refiner Model Hash', 'refiner_model_hash', refiner_model_hash, False, False),
('Refiner Switch', 'refiner_switch', refiner_switch, True, True),
('Sampler', 'sampler', sampler_name, True, True),
('Scheduler', 'scheduler', scheduler_name, True, True),
@@ -821,8 +823,9 @@ def worker():
for li, (n, w) in enumerate(loras):
if n != 'None':
d.append((f'LoRA {li + 1}', f'lora{li + 1}_combined', f'{n} : {w}', True, True))
# d.append((f'LoRA {li + 1} Name', f'lora{li + 1}_name', n, False, False))
# d.append((f'LoRA {li + 1} Weight', f'lora{li + 1}_weight', n, False, False))
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))
d.append((f'LoRA {li + 1} Hash', f'lora_hash_{li + 1}', lora_hashes[li], False, False))
d.append(('Version', 'version', 'v' + fooocus_version.version, True, True))
log(x, d, save_metadata_to_images, metadata_scheme)