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feat: add model hash support for a1111

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This commit is contained in:
Manuel Schmid
2024-01-15 22:11:46 +01:00
parent 191f8148e4
commit f7489cc9ef
2 changed files with 37 additions and 6 deletions
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modules/async_worker.py
+19 -6
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@@ -14,6 +14,7 @@ async_tasks = []
def worker():
global async_tasks
import os
import traceback
import math
import json
@@ -42,7 +43,7 @@ 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
get_image_shape_ceil, set_image_shape_ceil, get_shape_ceil, resample_image, erode_or_dilate, calculate_sha256, quote
from modules.upscaler import perform_upscale
try:
@@ -201,6 +202,17 @@ def worker():
modules.patch.adm_scaler_end = advanced_parameters.adm_scaler_end = 0.0
steps = 8
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)
print(lora_hashes_string)
modules.patch.adaptive_cfg = advanced_parameters.adaptive_cfg
print(f'[Parameters] Adaptive CFG = {modules.patch.adaptive_cfg}')
@@ -854,16 +866,17 @@ def worker():
"CFG scale": cfg_scale,
"Seed": task['task_seed'],
"Size": f"{width}x{height}",
#"Model hash": p.sd_model_hash if opts.add_model_hash_to_info else None,
"Model": base_model_name,
"Model hash": base_model_hash,
"Model": base_model_name.split('.')[0],
"Lora hashes": lora_hashes_string,
"Denoising strength": denoising_strength,
"Version": f'Fooocus v{fooocus_version.version}',
"User": 'mashb1t',
"User": 'mashb1t'
}
generation_params_text = ", ".join([k if k == v else f'{k}: {v}' for k, v in generation_params.items() if v is not None])
generation_params_text = ", ".join([k if k == v else f'{k}: {quote(v)}' for k, v in generation_params.items() if v is not None])
negative_prompt_text = f"\nNegative prompt: {raw_negative_prompt}" if raw_negative_prompt else ""
metadata_string = f"{raw_prompt}{raw_negative_prompt}\n{generation_params_text}".strip()
metadata_string = f"{raw_prompt}{negative_prompt_text}\n{generation_params_text}".strip()
for x in imgs:
d = [