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automatic
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ruff lint

pull/4663/head
Vladimir Mandic 2026-02-19 11:13:44 +01:00
parent e5c494f999
commit d65a2d1ebc
30 changed files with 59 additions and 73 deletions
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2
data/installer.json
View File

@ -18,4 +18,4 @@
"sdnext-kanvas": "79cae1944646e57cfbfb126a971a04e44e45d776",
"sdnext-modernui": "fc7cf10dcc3f17377b6a18c4cd0dbd2be5480f0b"
}
}
}

2
launch.py
View File

@ -287,7 +287,7 @@ def main():
installer.update_state()
else:
log.warning(f'Setup complete with errors: {installer.errors}')
log.warning(f'See log file for more details: {logger.log_file}')
log.warning(f'See log file for more details: {installer.log_file}')
installer.extensions_preload(parser) # adds additional args from extensions
args = installer.parse_args(parser)
log.info(f'Installer time: {init_summary()}')

1
modules/attention.py
View File

@ -1,7 +1,6 @@
from functools import wraps
import torch
from modules import rocm
from modules.logger import log
from modules.errors import log
from installer import install, installed

4
modules/caption/deepbooru.py
View File

@ -5,7 +5,7 @@ import torch
import numpy as np
from PIL import Image
from modules import modelloader, devices, shared, paths
from modules.logger import log
from modules.logger import log, console
re_special = re.compile(r'([\\()])')
load_lock = threading.Lock()
@ -276,7 +276,7 @@ def batch(
model.start()
# Progress bar
pbar = rp.Progress(rp.TextColumn('[cyan]DeepBooru:'), rp.BarColumn(), rp.MofNCompleteColumn(), rp.TaskProgressColumn(), rp.TimeRemainingColumn(), rp.TimeElapsedColumn(), rp.TextColumn('[cyan]{task.description}'), console=logger.console)
pbar = rp.Progress(rp.TextColumn('[cyan]DeepBooru:'), rp.BarColumn(), rp.MofNCompleteColumn(), rp.TaskProgressColumn(), rp.TimeRemainingColumn(), rp.TimeElapsedColumn(), rp.TextColumn('[cyan]{task.description}'), console=console)
with pbar:
task = pbar.add_task(total=len(image_files), description='starting...')

4
modules/caption/openclip.py
View File

@ -6,7 +6,7 @@ import re
import gradio as gr
from PIL import Image
from modules import devices, shared, errors
from modules.logger import log
from modules.logger import log, console
debug_enabled = os.environ.get('SD_CAPTION_DEBUG', None) is not None
@ -293,7 +293,7 @@ def caption_batch(batch_files, batch_folder, batch_str, clip_model, blip_model,
writer = BatchWriter(os.path.dirname(files[0]), mode=file_mode)
debug_log(f'CLIP batch: writing to "{os.path.dirname(files[0])}" mode="{file_mode}"')
import rich.progress as rp
pbar = rp.Progress(rp.TextColumn('[cyan]Caption:'), rp.BarColumn(), rp.MofNCompleteColumn(), rp.TaskProgressColumn(), rp.TimeRemainingColumn(), rp.TimeElapsedColumn(), rp.TextColumn('[cyan]{task.description}'), console=logger.console)
pbar = rp.Progress(rp.TextColumn('[cyan]Caption:'), rp.BarColumn(), rp.MofNCompleteColumn(), rp.TaskProgressColumn(), rp.TimeRemainingColumn(), rp.TimeElapsedColumn(), rp.TextColumn('[cyan]{task.description}'), console=console)
with pbar:
task = pbar.add_task(total=len(files), description='starting...')
for file in files:

4
modules/caption/vqa.py
View File

@ -9,7 +9,7 @@ import transformers
import transformers.dynamic_module_utils
from PIL import Image
from modules import shared, devices, errors, model_quant, sd_models, sd_models_compile, ui_symbols
from modules.logger import log
from modules.logger import log, console
from modules.caption import vqa_detection
@ -1530,7 +1530,7 @@ class VQA:
shared.opts.caption_offload = False
try:
import rich.progress as rp
pbar = rp.Progress(rp.TextColumn('[cyan]Caption:'), rp.BarColumn(), rp.MofNCompleteColumn(), rp.TaskProgressColumn(), rp.TimeRemainingColumn(), rp.TimeElapsedColumn(), rp.TextColumn('[cyan]{task.description}'), console=logger.console)
pbar = rp.Progress(rp.TextColumn('[cyan]Caption:'), rp.BarColumn(), rp.MofNCompleteColumn(), rp.TaskProgressColumn(), rp.TimeRemainingColumn(), rp.TimeElapsedColumn(), rp.TextColumn('[cyan]{task.description}'), console=console)
with pbar:
task = pbar.add_task(total=len(files), description='starting...')
for file in files:

4
modules/caption/waifudiffusion.py
View File

@ -8,7 +8,7 @@ import threading
import numpy as np
from PIL import Image
from modules import shared, devices, errors
from modules.logger import log
from modules.logger import log, console
# Debug logging - enable with SD_CAPTION_DEBUG environment variable
@ -492,7 +492,7 @@ def batch(
# Progress bar
import rich.progress as rp
pbar = rp.Progress(rp.TextColumn('[cyan]WaifuDiffusion:'), rp.BarColumn(), rp.MofNCompleteColumn(), rp.TaskProgressColumn(), rp.TimeRemainingColumn(), rp.TimeElapsedColumn(), rp.TextColumn('[cyan]{task.description}'), console=logger.console)
pbar = rp.Progress(rp.TextColumn('[cyan]WaifuDiffusion:'), rp.BarColumn(), rp.MofNCompleteColumn(), rp.TaskProgressColumn(), rp.TimeRemainingColumn(), rp.TimeElapsedColumn(), rp.TextColumn('[cyan]{task.description}'), console=console)
with pbar:
task = pbar.add_task(total=len(image_files), description='starting...')

6
modules/civitai/download_civitai.py
View File

@ -3,7 +3,7 @@ import json
import rich.progress as p
from PIL import Image
from modules import shared, errors, paths
from modules.logger import log
from modules.logger import log, console
pbar = None
@ -65,7 +65,7 @@ def download_civit_preview(model_path: str, preview_url: str):
img = None
jobid = shared.state.begin('Download CivitAI')
if pbar is None:
pbar = p.Progress(p.TextColumn('[cyan]Download'), p.DownloadColumn(), p.BarColumn(), p.TaskProgressColumn(), p.TimeRemainingColumn(), p.TimeElapsedColumn(), p.TransferSpeedColumn(), p.TextColumn('[yellow]{task.description}'), console=logger.console)
pbar = p.Progress(p.TextColumn('[cyan]Download'), p.DownloadColumn(), p.BarColumn(), p.TaskProgressColumn(), p.TimeRemainingColumn(), p.TimeElapsedColumn(), p.TransferSpeedColumn(), p.TextColumn('[yellow]{task.description}'), console=console)
try:
with open(preview_file, 'wb') as f:
with pbar:
@ -146,7 +146,7 @@ def download_civit_model_thread(model_name: str, model_url: str, model_path: str
written = starting_pos
global pbar # pylint: disable=global-statement
if pbar is None:
pbar = p.Progress(p.TextColumn('[cyan]{task.description}'), p.DownloadColumn(), p.BarColumn(), p.TaskProgressColumn(), p.TimeRemainingColumn(), p.TimeElapsedColumn(), p.TransferSpeedColumn(), p.TextColumn('[cyan]{task.fields[name]}'), console=logger.console)
pbar = p.Progress(p.TextColumn('[cyan]{task.description}'), p.DownloadColumn(), p.BarColumn(), p.TaskProgressColumn(), p.TimeRemainingColumn(), p.TimeElapsedColumn(), p.TransferSpeedColumn(), p.TextColumn('[cyan]{task.fields[name]}'), console=console)
with pbar:
task = pbar.add_task(description="Download starting", total=starting_pos+total_size, name=model_name)
try:

3
modules/cmd_args.py
View File

@ -206,6 +206,3 @@ def settings_args(opts, args):
opts.onchange(d, lambda d=d: setattr(args, d, getattr(opts, d)), call=False)
return args

1
modules/dml/__init__.py
View File

@ -1,4 +1,3 @@
from modules.logger import log
import platform
from typing import NamedTuple, Optional
from collections.abc import Callable

4
modules/framepack/framepack_worker.py
View File

@ -2,7 +2,7 @@ import time
import torch
import rich.progress as rp
from modules import shared, errors ,devices, sd_models, timer, memstats
from modules.logger import log
from modules.logger import log, console
from modules.framepack import framepack_vae # pylint: disable=wrong-import-order
from modules.framepack import framepack_hijack # pylint: disable=wrong-import-order
from modules.video_models.video_save import save_video # pylint: disable=wrong-import-order
@ -79,7 +79,7 @@ def worker(
image_encoder = shared.sd_model.image_processor
transformer = shared.sd_model.transformer
sd_models.apply_balanced_offload(shared.sd_model)
pbar = rp.Progress(rp.TextColumn('[cyan]Video'), rp.BarColumn(), rp.MofNCompleteColumn(), rp.TaskProgressColumn(), rp.TimeRemainingColumn(), rp.TimeElapsedColumn(), rp.TextColumn('[cyan]{task.description}'), console=logger.console)
pbar = rp.Progress(rp.TextColumn('[cyan]Video'), rp.BarColumn(), rp.MofNCompleteColumn(), rp.TaskProgressColumn(), rp.TimeRemainingColumn(), rp.TimeElapsedColumn(), rp.TextColumn('[cyan]{task.description}'), console=console)
task = pbar.add_task('starting', total=steps * len(latent_paddings))
t_last = time.time()
if not is_f1:

3
modules/hashes.py
View File

@ -3,7 +3,6 @@ import hashlib
import os.path
from rich import progress, errors
from installer import console
from modules.logger import log
from modules.json_helpers import readfile, writefile
from modules.paths import data_path
@ -83,7 +82,7 @@ def sha256(filename, title, use_addnet_hash=False):
if use_addnet_hash:
if progress_ok:
try:
with progress.open(filename, 'rb', description=f'[cyan]Calculating hash: [yellow]{filename}', auto_refresh=True, console=logger.console) as f:
with progress.open(filename, 'rb', description=f'[cyan]Calculating hash: [yellow]{filename}', auto_refresh=True, console=console) as f:
sha256_value = addnet_hash_safetensors(f)
except errors.LiveError:
log.warning('Hash: attempting to use function in a thread')

1
modules/infotext_utils.py
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@ -1,2 +1 @@
# a1111 compatibility module: unused

24
modules/loader.py
View File

@ -10,19 +10,6 @@ from modules import timer, errors
from modules.logger import log
try:
import math
cores = os.cpu_count()
affinity = len(os.sched_getaffinity(0)) # pylint: disable=no-member
threads = torch.get_num_threads()
if threads < (affinity / 2):
torch.set_num_threads(math.floor(affinity / 2))
threads = torch.get_num_threads()
log.debug(f'System: cores={cores} affinity={affinity} threads={threads}')
except Exception:
pass
initialized = False
errors.install()
logging.getLogger("DeepSpeed").disabled = True
@ -81,6 +68,17 @@ try:
except Exception:
log.warning('Loader: torch is not built with distributed support')
try:
import math
cores = os.cpu_count()
affinity = len(os.sched_getaffinity(0)) # pylint: disable=no-member
threads = torch.get_num_threads()
if threads < (affinity / 2):
torch.set_num_threads(math.floor(affinity / 2))
threads = torch.get_num_threads()
log.debug(f'System: cores={cores} affinity={affinity} threads={threads}')
except Exception:
pass
urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
warnings.filterwarnings(action="ignore", category=UserWarning, module="torchvision")

4
modules/lora/lora_extract.py
View File

@ -7,7 +7,7 @@ from safetensors.torch import save_file
import gradio as gr
from rich import progress as rp
from modules import shared, devices
from modules.logger import log
from modules.logger import log, console
from modules.ui_common import create_refresh_button
from modules.call_queue import wrap_gradio_gpu_call
@ -138,7 +138,7 @@ def make_lora(fn, maxrank, auto_rank, rank_ratio, modules, overwrite):
log.debug(f'LoRA extract: modules={modules} maxrank={maxrank} auto={auto_rank} ratio={rank_ratio} fn="{fn}"')
jobid = shared.state.begin('LoRA extract')
with rp.Progress(rp.TextColumn('[cyan]LoRA extract'), rp.BarColumn(), rp.TaskProgressColumn(), rp.TimeRemainingColumn(), rp.TimeElapsedColumn(), rp.TextColumn('[cyan]{task.description}'), console=logger.console) as progress:
with rp.Progress(rp.TextColumn('[cyan]LoRA extract'), rp.BarColumn(), rp.TaskProgressColumn(), rp.TimeRemainingColumn(), rp.TimeElapsedColumn(), rp.TextColumn('[cyan]{task.description}'), console=console) as progress:
if 'te' in modules and getattr(shared.sd_model, 'text_encoder', None) is not None:
modules = shared.sd_model.text_encoder.named_modules()

6
modules/lora/networks.py
View File

@ -5,7 +5,7 @@ from modules.errorlimiter import limit_errors
from modules.lora import lora_common as l
from modules.lora.lora_apply import network_apply_weights, network_apply_direct, network_backup_weights, network_calc_weights
from modules import shared, devices, sd_models
from modules.logger import log
from modules.logger import log, console
applied_layers: list[str] = []
@ -35,7 +35,7 @@ def network_activate(include=None, exclude=None):
modules[name] = list(component.named_modules())
total = sum(len(x) for x in modules.values())
if len(l.loaded_networks) > 0:
pbar = rp.Progress(rp.TextColumn('[cyan]Network: type=LoRA action=activate'), rp.BarColumn(), rp.TaskProgressColumn(), rp.TimeRemainingColumn(), rp.TimeElapsedColumn(), rp.TextColumn('[cyan]{task.description}'), console=logger.console)
pbar = rp.Progress(rp.TextColumn('[cyan]Network: type=LoRA action=activate'), rp.BarColumn(), rp.TaskProgressColumn(), rp.TimeRemainingColumn(), rp.TimeElapsedColumn(), rp.TextColumn('[cyan]{task.description}'), console=console)
task = pbar.add_task(description='' , total=total)
else:
task = None
@ -109,7 +109,7 @@ def network_deactivate(include=None, exclude=None):
active_components.append(name)
total = sum(len(x) for x in modules.values())
if len(l.previously_loaded_networks) > 0 and l.debug:
pbar = rp.Progress(rp.TextColumn('[cyan]Network: type=LoRA action=deactivate'), rp.BarColumn(), rp.TaskProgressColumn(), rp.TimeRemainingColumn(), rp.TimeElapsedColumn(), rp.TextColumn('[cyan]{task.description}'), console=logger.console)
pbar = rp.Progress(rp.TextColumn('[cyan]Network: type=LoRA action=deactivate'), rp.BarColumn(), rp.TaskProgressColumn(), rp.TimeRemainingColumn(), rp.TimeElapsedColumn(), rp.TextColumn('[cyan]{task.description}'), console=console)
task = pbar.add_task(description='', total=total)
else:
task = None

1
modules/model_quant.py
View File

@ -8,7 +8,6 @@ import time
import diffusers
import transformers
from installer import installed, install, setup_logging
from modules.logger import log
ao = None

5
modules/modelloader.py
View File

@ -7,11 +7,10 @@ import contextlib
from urllib.parse import urlparse
import huggingface_hub as hf
from installer import install
from modules.logger import log
from modules.logger import log, console
from modules import shared, errors, files_cache
from modules.upscaler import Upscaler
from modules import paths
from modules.logger import log
loggedin = None
@ -304,7 +303,7 @@ def download_url_to_file(url: str, dst: str):
log.error(f'Error downloading: url={url} no usable temporary filename found')
return
try:
with Progress(TextColumn('[cyan]{task.description}'), BarColumn(), TaskProgressColumn(), TimeRemainingColumn(), TimeElapsedColumn(), console=logger.console) as progress:
with Progress(TextColumn('[cyan]{task.description}'), BarColumn(), TaskProgressColumn(), TimeRemainingColumn(), TimeElapsedColumn(), console=console) as progress:
task = progress.add_task(description="Downloading", total=file_size)
while True:
buffer = u.read(8192)

1
modules/onnx_impl/__init__.py
View File

@ -4,7 +4,6 @@ import numpy as np
import torch
import diffusers
from installer import installed, install
from modules.logger import log
initialized = False

1
modules/paths_internal.py
View File

@ -1,2 +1 @@
# no longer used, all paths are defined in paths.py

4
modules/postprocess/esrgan_model.py
View File

@ -4,7 +4,7 @@ from PIL import Image
from rich.progress import Progress, TextColumn, BarColumn, TaskProgressColumn, TimeRemainingColumn, TimeElapsedColumn
import modules.postprocess.esrgan_model_arch as arch
from modules import images, devices, shared
from modules.logger import log
from modules.logger import log, console
from modules.upscaler import Upscaler, UpscalerData, compile_upscaler
@ -197,7 +197,7 @@ def esrgan_upscale(model, img):
newtiles = []
scale_factor = 1
with Progress(TextColumn('[cyan]{task.description}'), BarColumn(), TaskProgressColumn(), TimeRemainingColumn(), TimeElapsedColumn(), console=logger.console) as progress:
with Progress(TextColumn('[cyan]{task.description}'), BarColumn(), TaskProgressColumn(), TimeRemainingColumn(), TimeElapsedColumn(), console=console) as progress:
total = 0
for _y, _h, row in grid.tiles:
total += len(row)

4
modules/postprocess/realesrgan_model_arch.py
View File

@ -9,7 +9,7 @@ from torch import nn
from torch.nn import functional as F
from rich.progress import Progress, TextColumn, BarColumn, TaskProgressColumn, TimeRemainingColumn, TimeElapsedColumn
from modules import devices, shared
from modules.logger import log
from modules.logger import log, console
from modules.upscaler import compile_upscaler
ROOT_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
@ -139,7 +139,7 @@ class RealESRGANer:
tiles_y = math.ceil(height / self.tile_size)
# loop over all tiles
with Progress(TextColumn('[cyan]{task.description}'), BarColumn(), TaskProgressColumn(), TimeRemainingColumn(), TimeElapsedColumn(), console=logger.console) as progress:
with Progress(TextColumn('[cyan]{task.description}'), BarColumn(), TaskProgressColumn(), TimeRemainingColumn(), TimeElapsedColumn(), console=console) as progress:
task = progress.add_task(description="Upscaling", total=tiles_y * tiles_x)
with torch.no_grad():
for y in range(tiles_y):

4
modules/postprocess/swinir_model.py
View File

@ -5,7 +5,7 @@ from rich.progress import Progress, TextColumn, BarColumn, TaskProgressColumn, T
from modules.postprocess.swinir_model_arch import SwinIR as net
from modules.postprocess.swinir_model_arch_v2 import Swin2SR as net2
from modules import devices, shared
from modules.logger import log
from modules.logger import log, console
from modules.upscaler import Upscaler, compile_upscaler
@ -123,7 +123,7 @@ def inference(img, model, tile, tile_overlap, window_size, scale):
E = torch.zeros(b, c, h * sf, w * sf, dtype=devices.dtype, device=devices.device).type_as(img)
W = torch.zeros_like(E, dtype=devices.dtype, device=devices.device)
with Progress(TextColumn('[cyan]{task.description}'), BarColumn(), TaskProgressColumn(), TimeRemainingColumn(), TimeElapsedColumn(), console=logger.console) as progress:
with Progress(TextColumn('[cyan]{task.description}'), BarColumn(), TaskProgressColumn(), TimeRemainingColumn(), TimeElapsedColumn(), console=console) as progress:
task = progress.add_task(description="Upscaling Initializing", total=len(h_idx_list) * len(w_idx_list))
for h_idx in h_idx_list:
if shared.state.interrupted:

5
modules/sd_hijack_hypertile.py
View File

@ -2,8 +2,8 @@
# based on: https://github.com/tfernd/HyperTile/tree/main/hyper_tile/utils.py + https://github.com/tfernd/HyperTile/tree/main/hyper_tile/hyper_tile.py
from __future__ import annotations
from typing import TYPE_CHECKING
from modules.logger import log
from collections.abc import Callable
from functools import wraps, cache
from contextlib import contextmanager, nullcontext
import random
@ -11,7 +11,8 @@ import math
import torch
import torch.nn as nn
from einops import rearrange
from modules.logger import log
if TYPE_CHECKING:
from collections.abc import Callable
# global variables to keep track of changing image size in multiple passes

1
modules/sd_models.py
View File

@ -12,7 +12,6 @@ import torch
import huggingface_hub as hf
from modules.logger import log
from modules import timer, paths, shared, shared_items, modelloader, devices, script_callbacks, sd_vae, sd_unet, errors, sd_models_compile, sd_detect, model_quant, sd_hijack_te, sd_hijack_accelerate, sd_hijack_safetensors, attention
from modules.logger import log
from modules.memstats import memory_stats
from modules.modeldata import model_data
from modules.sd_checkpoint import CheckpointInfo, select_checkpoint, list_models, checkpoint_titles, get_closest_checkpoint_match, update_model_hashes, write_metadata, checkpoints_list # pylint: disable=unused-import

4
modules/sd_models_utils.py
View File

@ -8,7 +8,7 @@ import torch
import safetensors.torch
from modules import paths, shared, errors
from modules.logger import log
from modules.logger import log, console
from modules.sd_checkpoint import CheckpointInfo # pylint: disable=unused-import
@ -68,7 +68,7 @@ def read_state_dict(checkpoint_file, map_location=None, what:str='model'): # pyl
return None
try:
pl_sd = None
with progress.open(checkpoint_file, 'rb', description=f'[cyan]Load {what}: [yellow]{checkpoint_file}', auto_refresh=True, console=logger.console) as f:
with progress.open(checkpoint_file, 'rb', description=f'[cyan]Load {what}: [yellow]{checkpoint_file}', auto_refresh=True, console=console) as f:
_, extension = os.path.splitext(checkpoint_file)
if extension.lower() == ".ckpt" and shared.opts.sd_disable_ckpt:
log.warning(f"Checkpoint loading disabled: {checkpoint_file}")

1
modules/sd_offload.py
View File

@ -8,7 +8,6 @@ import accelerate.hooks
import accelerate.utils.modeling
from modules.logger import log
from modules import shared, devices, errors, model_quant, sd_models
from modules.logger import log
from modules.timer import process as process_timer

4
pipelines/model_glm.py
View File

@ -3,7 +3,7 @@ import rich.progress as rp
import transformers
import diffusers
from modules import shared, devices, sd_models, model_quant, sd_hijack_te
from modules.logger import log
from modules.logger import log, console
from pipelines import generic
@ -34,7 +34,7 @@ class GLMTokenProgressProcessor(transformers.LogitsProcessor):
rp.MofNCompleteColumn(),
rp.TimeElapsedColumn(),
rp.TimeRemainingColumn(),
console=logger.console,
console=console,
)
self.pbar.start()
self.pbar_task = self.pbar.add_task(description='', total=self.total_tokens, speed='')

12
scripts/differential_diffusion.py
View File

@ -1901,15 +1901,15 @@ class Script(scripts_manager.Script):
if not enabled:
return
if shared.sd_model_type not in ['sdxl', 'sd', 'f1']:
sdnext_log.error(f'Differential-diffusion: incorrect base model: {shared.sd_model.__class__.__name__}')
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:
sdnext_log.error('Differential-diffusion: no input images')
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:
sdnext_log.error('Differential-diffusion: no image map')
log.error('Differential-diffusion: no image map')
return
orig_pipeline = shared.sd_model
@ -1950,13 +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:
sdnext_log.warning(f'Differential-diffusion: batch-size={p.batch_size} parallel processing not supported')
log.warning(f'Differential-diffusion: batch-size={p.batch_size} parallel processing not supported')
p.batch_size = 1
sdnext_log.debug(f'Differential-diffusion: pipeline={pipe.__class__.__name__} strength={strength} model={model} auto={image is None}')
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:
sdnext_log.error(f'Differential-diffusion: pipeline creation failed: {e}')
log.error(f'Differential-diffusion: pipeline creation failed: {e}')
errors.display(e, 'Differential-diffusion: pipeline creation failed')
shared.sd_model = orig_pipeline

12
scripts/softfill.py
View File

@ -1631,13 +1631,13 @@ class Script(scripts_manager.Script):
if not enabled:
return
if shared.sd_model_type not in ['sdxl']:
sdnext_log.error(f'SoftFill: incorrect base model: {shared.sd_model.__class__.__name__}')
log.error(f'SoftFill: incorrect base model: {shared.sd_model.__class__.__name__}')
return
if not hasattr(p, 'init_images') or len(p.init_images) == 0:
sdnext_log.error('SoftFill: no input image')
log.error('SoftFill: no input image')
return
if not hasattr(p, 'mask') or p.mask is None:
sdnext_log.error('SoftFill: no input mask')
log.error('SoftFill: no input mask')
return
try:
@ -1646,7 +1646,7 @@ class Script(scripts_manager.Script):
import noise as noise_module
pnoise2 = noise_module.pnoise2
except Exception as e:
sdnext_log.error(f'SoftFill: {e}')
log.error(f'SoftFill: {e}')
return
self.orig_pipeline = shared.sd_model
@ -1655,7 +1655,7 @@ class Script(scripts_manager.Script):
if shared.sd_model.__class__.__name__ not in sd_models.pipe_switch_task_exclude:
sd_models.pipe_switch_task_exclude.append(shared.sd_model.__class__.__name__)
except Exception as e:
sdnext_log.error(f'SoftFill: {e}')
log.error(f'SoftFill: {e}')
shared.sd_model = self.orig_pipeline
self.orig_pipeline = None
return
@ -1664,7 +1664,7 @@ class Script(scripts_manager.Script):
p.task_args['strength'] = strength
p.task_args['image'] = p.init_images[0]
p.task_args['mask'] = p.mask
sdnext_log.info(f'SoftFill: cls={shared.sd_model.__class__.__name__} {p.task_args}')
log.info(f'SoftFill: cls={shared.sd_model.__class__.__name__} {p.task_args}')
def after(self, p: processing.StableDiffusionProcessingImg2Img, *args, **kwargs): # pylint: disable=unused-argument
if self.orig_pipeline is not None: