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unified logger

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Vladimir Mandic
2026-02-19 09:46:42 +01:00
parent bfe014f5da
commit a3074baf8b
315 changed files with 2507 additions and 2116 deletions
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scripts/differential_diffusion.py
+7 -6
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@@ -1835,6 +1835,7 @@ import gradio as gr
import diffusers
from PIL import Image, ImageEnhance, ImageOps # pylint: disable=reimported
from modules import errors, shared, devices, scripts_manager, processing, sd_models, images
from modules import logger
from modules.image import convert
@@ -1900,15 +1901,15 @@ class Script(scripts_manager.Script):
if not enabled:
return
if shared.sd_model_type not in ['sdxl', 'sd', 'f1']:
shared.log.error(f'Differential-diffusion: incorrect base model: {shared.sd_model.__class__.__name__}')
logger.log.error(f'Differential-diffusion: incorrect base model: {shared.sd_model.__class__.__name__}')
return
if not hasattr(p, 'init_images') or len(p.init_images) == 0:
shared.log.error('Differential-diffusion: no input images')
logger.log.error('Differential-diffusion: no input images')
return
image_init, image_map, image_mask = self.depthmap(p.init_images[0], image, model, strength, invert)
if image_map is None:
shared.log.error('Differential-diffusion: no image map')
logger.log.error('Differential-diffusion: no image map')
return
orig_pipeline = shared.sd_model
@@ -1949,13 +1950,13 @@ class Script(scripts_manager.Script):
if shared.sd_model_type == 'sdxl':
p.task_args['original_image'] = image_init
if p.batch_size > 1:
shared.log.warning(f'Differential-diffusion: batch-size={p.batch_size} parallel processing not supported')
logger.log.warning(f'Differential-diffusion: batch-size={p.batch_size} parallel processing not supported')
p.batch_size = 1
shared.log.debug(f'Differential-diffusion: pipeline={pipe.__class__.__name__} strength={strength} model={model} auto={image is None}')
logger.log.debug(f'Differential-diffusion: pipeline={pipe.__class__.__name__} strength={strength} model={model} auto={image is None}')
shared.sd_model = pipe
sd_models.move_model(pipe.vae, devices.device, force=True)
except Exception as e:
shared.log.error(f'Differential-diffusion: pipeline creation failed: {e}')
logger.log.error(f'Differential-diffusion: pipeline creation failed: {e}')
errors.display(e, 'Differential-diffusion: pipeline creation failed')
shared.sd_model = orig_pipeline