imports cleanup for ruff

extensions-builtin/Lora/lora.py

@@ -1,4 +1,3 @@
-import glob
 import os
 import re
 import torch

extensions-builtin/ScuNET/scripts/scunet_model.py

@@ -13,7 +13,6 @@ import modules.upscaler
 from modules import devices, modelloader
 from scunet_model_arch import SCUNet as net
 from modules.shared import opts
-from modules import images
 
 
 class UpscalerScuNET(modules.upscaler.Upscaler):

extensions-builtin/SwinIR/scripts/swinir_model.py

@@ -1,4 +1,3 @@
-import contextlib
 import os
 
 import numpy as np
@@ -8,7 +7,7 @@ from basicsr.utils.download_util import load_file_from_url
 from tqdm import tqdm
 
 from modules import modelloader, devices, script_callbacks, shared
-from modules.shared import cmd_opts, opts, state
+from modules.shared import opts, state
 from swinir_model_arch import SwinIR as net
 from swinir_model_arch_v2 import Swin2SR as net2
 from modules.upscaler import Upscaler, UpscalerData

modules/codeformer/codeformer_arch.py

@@ -1,14 +1,12 @@
 # this file is copied from CodeFormer repository. Please see comment in modules/codeformer_model.py
 
 import math
-import numpy as np
 import torch
 from torch import nn, Tensor
 import torch.nn.functional as F
-from typing import Optional, List
+from typing import Optional
 
 from modules.codeformer.vqgan_arch import VQAutoEncoder, ResBlock
-from basicsr.utils import get_root_logger
 from basicsr.utils.registry import ARCH_REGISTRY
 
 def calc_mean_std(feat, eps=1e-5):

modules/codeformer/vqgan_arch.py

@@ -5,11 +5,9 @@ VQGAN code, adapted from the original created by the Unleashing Transformers aut
 https://github.com/samb-t/unleashing-transformers/blob/master/models/vqgan.py
 
 '''
-import numpy as np
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
-import copy
 from basicsr.utils import get_root_logger
 from basicsr.utils.registry import ARCH_REGISTRY
 

modules/codeformer_model.py

@@ -33,11 +33,9 @@ def setup_model(dirname):
     try:
         from torchvision.transforms.functional import normalize
         from modules.codeformer.codeformer_arch import CodeFormer
-        from basicsr.utils.download_util import load_file_from_url
+        from basicsr.utils import img2tensor, tensor2img
-        from basicsr.utils import imwrite, img2tensor, tensor2img
         from facelib.utils.face_restoration_helper import FaceRestoreHelper
         from facelib.detection.retinaface import retinaface
-        from modules.shared import cmd_opts
 
         net_class = CodeFormer
 

modules/config_states.py

@@ -14,7 +14,7 @@ from collections import OrderedDict
 import git
 
 from modules import shared, extensions
-from modules.paths_internal import extensions_dir, extensions_builtin_dir, script_path, config_states_dir
+from modules.paths_internal import script_path, config_states_dir
 
 
 all_config_states = OrderedDict()

modules/esrgan_model.py

@@ -6,7 +6,7 @@ from PIL import Image
 from basicsr.utils.download_util import load_file_from_url
 
 import modules.esrgan_model_arch as arch
-from modules import shared, modelloader, images, devices
+from modules import modelloader, images, devices
 from modules.upscaler import Upscaler, UpscalerData
 from modules.shared import opts
 

modules/esrgan_model_arch.py

@@ -2,7 +2,6 @@
 
 from collections import OrderedDict
 import math
-import functools
 import torch
 import torch.nn as nn
 import torch.nn.functional as F

modules/extensions.py

@@ -3,7 +3,6 @@ import sys
 import traceback
 
 import time
-from datetime import datetime
 import git
 
 from modules import shared

modules/generation_parameters_copypaste.py

@@ -1,15 +1,11 @@
 import base64
-import html
 import io
-import math
 import os
 import re
-from pathlib import Path
 
 import gradio as gr
 from modules.paths import data_path
 from modules import shared, ui_tempdir, script_callbacks
-import tempfile
 from PIL import Image
 
 re_param_code = r'\s*([\w ]+):\s*("(?:\\"[^,]|\\"|\\|[^\"])+"|[^,]*)(?:,|$)'

modules/hypernetworks/hypernetwork.py

@@ -1,4 +1,3 @@
-import csv
 import datetime
 import glob
 import html
@@ -18,7 +17,7 @@ from modules.textual_inversion.learn_schedule import LearnRateScheduler
 from torch import einsum
 from torch.nn.init import normal_, xavier_normal_, xavier_uniform_, kaiming_normal_, kaiming_uniform_, zeros_
 
-from collections import defaultdict, deque
+from collections import deque
 from statistics import stdev, mean
 
 

modules/hypernetworks/ui.py

@@ -1,6 +1,4 @@
 import html
-import os
-import re
 
 import gradio as gr
 import modules.hypernetworks.hypernetwork

modules/images.py

@@ -19,7 +19,7 @@ import json
 import hashlib
 
 from modules import sd_samplers, shared, script_callbacks, errors
-from modules.shared import opts, cmd_opts
+from modules.shared import opts
 
 LANCZOS = (Image.Resampling.LANCZOS if hasattr(Image, 'Resampling') else Image.LANCZOS)
 

modules/img2img.py

@@ -1,12 +1,9 @@
-import math
 import os
-import sys
-import traceback
 
 import numpy as np
 from PIL import Image, ImageOps, ImageFilter, ImageEnhance, ImageChops, UnidentifiedImageError
 
-from modules import devices, sd_samplers
+from modules import sd_samplers
 from modules.generation_parameters_copypaste import create_override_settings_dict
 from modules.processing import Processed, StableDiffusionProcessingImg2Img, process_images
 from modules.shared import opts, state

modules/mac_specific.py

@@ -1,6 +1,5 @@
 import torch
 import platform
-from modules import paths
 from modules.sd_hijack_utils import CondFunc
 from packaging import version
 

modules/modelloader.py

@@ -1,4 +1,3 @@
-import glob
 import os
 import shutil
 import importlib

modules/models/diffusion/uni_pc/uni_pc.py

@@ -1,5 +1,4 @@
 import torch
-import torch.nn.functional as F
 import math
 from tqdm.auto import trange
 

modules/processing.py

@@ -2,7 +2,6 @@ import json
 import math
 import os
 import sys
-import warnings
 import hashlib
 
 import torch
@@ -11,10 +10,10 @@ from PIL import Image, ImageFilter, ImageOps
 import random
 import cv2
 from skimage import exposure
-from typing import Any, Dict, List, Optional
+from typing import Any, Dict, List
 
 import modules.sd_hijack
-from modules import devices, prompt_parser, masking, sd_samplers, lowvram, generation_parameters_copypaste, script_callbacks, extra_networks, sd_vae_approx, scripts
+from modules import devices, prompt_parser, masking, sd_samplers, lowvram, generation_parameters_copypaste, extra_networks, sd_vae_approx, scripts
 from modules.sd_hijack import model_hijack
 from modules.shared import opts, cmd_opts, state
 import modules.shared as shared

modules/sd_hijack.py

@@ -3,7 +3,7 @@ from torch.nn.functional import silu
 from types import MethodType
 
 import modules.textual_inversion.textual_inversion
-from modules import devices, sd_hijack_optimizations, shared, sd_hijack_checkpoint
+from modules import devices, sd_hijack_optimizations, shared
 from modules.hypernetworks import hypernetwork
 from modules.shared import cmd_opts
 from modules import sd_hijack_clip, sd_hijack_open_clip, sd_hijack_unet, sd_hijack_xlmr, xlmr

modules/sd_hijack_inpainting.py

@@ -1,15 +1,9 @@
-import os
 import torch
 
-from einops import repeat
-from omegaconf import ListConfig
-
 import ldm.models.diffusion.ddpm
 import ldm.models.diffusion.ddim
 import ldm.models.diffusion.plms
 
-from ldm.models.diffusion.ddpm import LatentDiffusion
-from ldm.models.diffusion.plms import PLMSSampler
 from ldm.models.diffusion.ddim import DDIMSampler, noise_like
 from ldm.models.diffusion.sampling_util import norm_thresholding
 

modules/sd_hijack_ip2p.py

@@ -1,8 +1,5 @@
-import collections
 import os.path
-import sys
+
-import gc
-import time
 
 def should_hijack_ip2p(checkpoint_info):
     from modules import sd_models_config

modules/sd_hijack_xlmr.py

@@ -1,8 +1,6 @@
-import open_clip.tokenizer
 import torch
 
 from modules import sd_hijack_clip, devices
-from modules.shared import opts
 
 
 class FrozenXLMREmbedderWithCustomWords(sd_hijack_clip.FrozenCLIPEmbedderWithCustomWords):

modules/sd_models.py

@@ -565,7 +565,7 @@ def reload_model_weights(sd_model=None, info=None):
 
 
 def unload_model_weights(sd_model=None, info=None):
-    from modules import lowvram, devices, sd_hijack
+    from modules import devices, sd_hijack
     timer = Timer()
 
     if model_data.sd_model:

modules/sd_models_config.py

@@ -1,4 +1,3 @@
-import re
 import os
 
 import torch

modules/sd_samplers_kdiffusion.py

@@ -1,7 +1,6 @@
 from collections import deque
 import torch
 import inspect
-import einops
 import k_diffusion.sampling
 from modules import prompt_parser, devices, sd_samplers_common
 

modules/sd_vae.py

@@ -1,8 +1,5 @@
-import torch
-import safetensors.torch
 import os
 import collections
-from collections import namedtuple
 from modules import paths, shared, devices, script_callbacks, sd_models
 import glob
 from copy import deepcopy

modules/shared.py

@@ -1,12 +1,9 @@
-import argparse
 import datetime
 import json
 import os
 import sys
 import time
-import requests
 
-from PIL import Image
 import gradio as gr
 import tqdm
 

modules/styles.py

@@ -1,18 +1,9 @@
-# We need this so Python doesn't complain about the unknown StableDiffusionProcessing-typehint at runtime
-from __future__ import annotations
-
 import csv
 import os
 import os.path
 import typing
-import collections.abc as abc
-import tempfile
 import shutil
 
-if typing.TYPE_CHECKING:
-    # Only import this when code is being type-checked, it doesn't have any effect at runtime
-    from .processing import StableDiffusionProcessing
-
 
 class PromptStyle(typing.NamedTuple):
     name: str

modules/textual_inversion/autocrop.py

@@ -1,10 +1,8 @@
 import cv2
 import requests
 import os
-from collections import defaultdict
-from math import log, sqrt
 import numpy as np
-from PIL import Image, ImageDraw
+from PIL import ImageDraw
 
 GREEN = "#0F0"
 BLUE = "#00F"

modules/textual_inversion/image_embedding.py

@@ -2,7 +2,7 @@ import base64
 import json
 import numpy as np
 import zlib
-from PIL import Image, PngImagePlugin, ImageDraw, ImageFont
+from PIL import Image, ImageDraw, ImageFont
 from fonts.ttf import Roboto
 import torch
 from modules.shared import opts

modules/textual_inversion/preprocess.py

@@ -1,13 +1,9 @@
 import os
 from PIL import Image, ImageOps
 import math
-import platform
-import sys
 import tqdm
-import time
 
 from modules import paths, shared, images, deepbooru
-from modules.shared import opts, cmd_opts
 from modules.textual_inversion import autocrop
 
 

modules/textual_inversion/textual_inversion.py

@@ -1,7 +1,6 @@
 import os
 import sys
 import traceback
-import inspect
 from collections import namedtuple
 
 import torch

modules/txt2img.py

@@ -1,18 +1,15 @@
 import modules.scripts
-from modules import sd_samplers
+from modules import sd_samplers, processing
 from modules.generation_parameters_copypaste import create_override_settings_dict
-from modules.processing import StableDiffusionProcessing, Processed, StableDiffusionProcessingTxt2Img, \
-    StableDiffusionProcessingImg2Img, process_images
 from modules.shared import opts, cmd_opts
 import modules.shared as shared
-import modules.processing as processing
 from modules.ui import plaintext_to_html
 
 
 def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, override_settings_texts, *args):
     override_settings = create_override_settings_dict(override_settings_texts)
 
-    p = StableDiffusionProcessingTxt2Img(
+    p = processing.StableDiffusionProcessingTxt2Img(
         sd_model=shared.sd_model,
         outpath_samples=opts.outdir_samples or opts.outdir_txt2img_samples,
         outpath_grids=opts.outdir_grids or opts.outdir_txt2img_grids,
@@ -53,7 +50,7 @@ def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, step
     processed = modules.scripts.scripts_txt2img.run(p, *args)
 
     if processed is None:
-        processed = process_images(p)
+        processed = processing.process_images(p)
 
     p.close()
 

modules/ui.py

@@ -14,10 +14,10 @@ from PIL import Image, PngImagePlugin
 from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call
 
 from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru, sd_vae, extra_networks, postprocessing, ui_components, ui_common, ui_postprocessing, progress
-from modules.ui_components import FormRow, FormColumn, FormGroup, ToolButton, FormHTML
+from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML
 from modules.paths import script_path, data_path
 
-from modules.shared import opts, cmd_opts, restricted_opts
+from modules.shared import opts, cmd_opts
 
 import modules.codeformer_model
 import modules.generation_parameters_copypaste as parameters_copypaste
@@ -28,7 +28,6 @@ import modules.shared as shared
 import modules.styles
 import modules.textual_inversion.ui
 from modules import prompt_parser
-from modules.images import save_image
 from modules.sd_hijack import model_hijack
 from modules.sd_samplers import samplers, samplers_for_img2img
 from modules.textual_inversion import textual_inversion

modules/ui_extra_networks.py

@@ -1,4 +1,3 @@
-import glob
 import os.path
 import urllib.parse
 from pathlib import Path

modules/ui_postprocessing.py

@@ -1,5 +1,5 @@
 import gradio as gr
-from modules import scripts_postprocessing, scripts, shared, gfpgan_model, codeformer_model, ui_common, postprocessing, call_queue
+from modules import scripts, shared, ui_common, postprocessing, call_queue
 import modules.generation_parameters_copypaste as parameters_copypaste
 
 

modules/upscaler.py

@@ -2,8 +2,6 @@ import os
 from abc import abstractmethod
 
 import PIL
-import numpy as np
-import torch
 from PIL import Image
 
 import modules.shared

modules/xlmr.py

@@ -1,4 +1,4 @@
-from transformers import BertPreTrainedModel,BertModel,BertConfig
+from transformers import BertPreTrainedModel, BertConfig
 import torch.nn as nn
 import torch
 from transformers.models.xlm_roberta.configuration_xlm_roberta import XLMRobertaConfig

pyproject.toml

@@ -1,10 +1,13 @@
 [tool.ruff]
 
+exclude = ["extensions"]
+
 ignore = [
 	"E501",
-	"E731",
+	
-	"E402",   # Module level import not at top of file
+	"F401", # Module imported but unused
-	"F401"    # Module imported but unused
 ]
 
-exclude = ["extensions"]
+
+[tool.ruff.per-file-ignores]
+"webui.py" = ["E402"]  # Module level import not at top of file

scripts/custom_code.py

@@ -4,7 +4,7 @@ import ast
 import copy
 
 from modules.processing import Processed
-from modules.shared import opts, cmd_opts, state
+from modules.shared import cmd_opts
 
 
 def convertExpr2Expression(expr):

scripts/outpainting_mk_2.py

@@ -7,9 +7,9 @@ import modules.scripts as scripts
 import gradio as gr
 from PIL import Image, ImageDraw
 
-from modules import images, processing, devices
+from modules import images
 from modules.processing import Processed, process_images
-from modules.shared import opts, cmd_opts, state
+from modules.shared import opts, state
 
 
 # this function is taken from https://github.com/parlance-zz/g-diffuser-bot

scripts/poor_mans_outpainting.py

@@ -4,9 +4,9 @@ import modules.scripts as scripts
 import gradio as gr
 from PIL import Image, ImageDraw
 
-from modules import images, processing, devices
+from modules import images, devices
 from modules.processing import Processed, process_images
-from modules.shared import opts, cmd_opts, state
+from modules.shared import opts, state
 
 
 class Script(scripts.Script):

scripts/prompt_matrix.py

@@ -1,14 +1,11 @@
 import math
-from collections import namedtuple
-from copy import copy
-import random
 
 import modules.scripts as scripts
 import gradio as gr
 
 from modules import images
-from modules.processing import process_images, Processed
+from modules.processing import process_images
-from modules.shared import opts, cmd_opts, state
+from modules.shared import opts, state
 import modules.sd_samplers
 
 

scripts/prompts_from_file.py

@@ -1,6 +1,4 @@
 import copy
-import math
-import os
 import random
 import sys
 import traceback
@@ -11,8 +9,7 @@ import gradio as gr
 
 from modules import sd_samplers
 from modules.processing import Processed, process_images
-from PIL import Image
+from modules.shared import state
-from modules.shared import opts, cmd_opts, state
 
 
 def process_string_tag(tag):

scripts/sd_upscale.py

@@ -4,9 +4,9 @@ import modules.scripts as scripts
 import gradio as gr
 from PIL import Image
 
-from modules import processing, shared, sd_samplers, images, devices
+from modules import processing, shared, images, devices
 from modules.processing import Processed
-from modules.shared import opts, cmd_opts, state
+from modules.shared import opts, state
 
 
 class Script(scripts.Script):

scripts/xyz_grid.py

@@ -10,15 +10,13 @@ import numpy as np
 import modules.scripts as scripts
 import gradio as gr
 
-from modules import images, paths, sd_samplers, processing, sd_models, sd_vae
+from modules import images, sd_samplers, processing, sd_models, sd_vae
 from modules.processing import process_images, Processed, StableDiffusionProcessingTxt2Img
-from modules.shared import opts, cmd_opts, state
+from modules.shared import opts, state
 import modules.shared as shared
 import modules.sd_samplers
 import modules.sd_models
 import modules.sd_vae
-import glob
-import os
 import re
 
 from modules.ui_components import ToolButton

webui.py

@@ -43,7 +43,7 @@ if ".dev" in torch.__version__ or "+git" in torch.__version__:
     torch.__long_version__ = torch.__version__
     torch.__version__ = re.search(r'[\d.]+[\d]', torch.__version__).group(0)
 
-from modules import shared, devices, sd_samplers, upscaler, extensions, localization, ui_tempdir, ui_extra_networks, config_states
+from modules import shared, sd_samplers, upscaler, extensions, localization, ui_tempdir, ui_extra_networks, config_states
 import modules.codeformer_model as codeformer
 import modules.face_restoration
 import modules.gfpgan_model as gfpgan