From 96d6ca4199e7c5eee8d451618de5161cea317c40 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Wed, 10 May 2023 08:25:25 +0300 Subject: manual fixes for ruff --- extensions-builtin/ScuNET/scunet_model_arch.py | 9 ++++++--- 1 file changed, 6 insertions(+), 3 deletions(-) (limited to 'extensions-builtin/ScuNET') diff --git a/extensions-builtin/ScuNET/scunet_model_arch.py b/extensions-builtin/ScuNET/scunet_model_arch.py index 43ca8d36..8028918a 100644 --- a/extensions-builtin/ScuNET/scunet_model_arch.py +++ b/extensions-builtin/ScuNET/scunet_model_arch.py @@ -61,7 +61,9 @@ class WMSA(nn.Module): Returns: output: tensor shape [b h w c] """ - if self.type != 'W': x = torch.roll(x, shifts=(-(self.window_size // 2), -(self.window_size // 2)), dims=(1, 2)) + if self.type != 'W': + x = torch.roll(x, shifts=(-(self.window_size // 2), -(self.window_size // 2)), dims=(1, 2)) + x = rearrange(x, 'b (w1 p1) (w2 p2) c -> b w1 w2 p1 p2 c', p1=self.window_size, p2=self.window_size) h_windows = x.size(1) w_windows = x.size(2) @@ -85,8 +87,9 @@ class WMSA(nn.Module): output = self.linear(output) output = rearrange(output, 'b (w1 w2) (p1 p2) c -> b (w1 p1) (w2 p2) c', w1=h_windows, p1=self.window_size) - if self.type != 'W': output = torch.roll(output, shifts=(self.window_size // 2, self.window_size // 2), - dims=(1, 2)) + if self.type != 'W': + output = torch.roll(output, shifts=(self.window_size // 2, self.window_size // 2), dims=(1, 2)) + return output def relative_embedding(self): -- cgit v1.2.3 From f741a98baccae100fcfb40c017b5c35c5cba1b0c Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Wed, 10 May 2023 08:43:42 +0300 Subject: imports cleanup for ruff --- extensions-builtin/Lora/lora.py | 1 - extensions-builtin/ScuNET/scripts/scunet_model.py | 1 - extensions-builtin/SwinIR/scripts/swinir_model.py | 3 +-- modules/codeformer/codeformer_arch.py | 4 +--- modules/codeformer/vqgan_arch.py | 2 -- modules/codeformer_model.py | 4 +--- modules/config_states.py | 2 +- modules/esrgan_model.py | 2 +- modules/esrgan_model_arch.py | 1 - modules/extensions.py | 1 - modules/generation_parameters_copypaste.py | 4 ---- modules/hypernetworks/hypernetwork.py | 3 +-- modules/hypernetworks/ui.py | 2 -- modules/images.py | 2 +- modules/img2img.py | 5 +---- modules/mac_specific.py | 1 - modules/modelloader.py | 1 - modules/models/diffusion/uni_pc/uni_pc.py | 1 - modules/processing.py | 5 ++--- modules/sd_hijack.py | 2 +- modules/sd_hijack_inpainting.py | 6 ------ modules/sd_hijack_ip2p.py | 5 +---- modules/sd_hijack_xlmr.py | 2 -- modules/sd_models.py | 2 +- modules/sd_models_config.py | 1 - modules/sd_samplers_kdiffusion.py | 1 - modules/sd_vae.py | 3 --- modules/shared.py | 3 --- modules/styles.py | 9 --------- modules/textual_inversion/autocrop.py | 4 +--- modules/textual_inversion/image_embedding.py | 2 +- modules/textual_inversion/preprocess.py | 4 ---- modules/textual_inversion/textual_inversion.py | 1 - modules/txt2img.py | 9 +++------ modules/ui.py | 5 ++--- modules/ui_extra_networks.py | 1 - modules/ui_postprocessing.py | 2 +- modules/upscaler.py | 2 -- modules/xlmr.py | 2 +- pyproject.toml | 11 +++++++---- scripts/custom_code.py | 2 +- scripts/outpainting_mk_2.py | 4 ++-- scripts/poor_mans_outpainting.py | 4 ++-- scripts/prompt_matrix.py | 7 ++----- scripts/prompts_from_file.py | 5 +---- scripts/sd_upscale.py | 4 ++-- scripts/xyz_grid.py | 6 ++---- webui.py | 2 +- 48 files changed, 42 insertions(+), 114 deletions(-) (limited to 'extensions-builtin/ScuNET') diff --git a/extensions-builtin/Lora/lora.py b/extensions-builtin/Lora/lora.py index ba1293df..0ab43229 100644 --- a/extensions-builtin/Lora/lora.py +++ b/extensions-builtin/Lora/lora.py @@ -1,4 +1,3 @@ -import glob import os import re import torch diff --git a/extensions-builtin/ScuNET/scripts/scunet_model.py b/extensions-builtin/ScuNET/scripts/scunet_model.py index c7fd5739..aa2fdb3a 100644 --- a/extensions-builtin/ScuNET/scripts/scunet_model.py +++ b/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): diff --git a/extensions-builtin/SwinIR/scripts/swinir_model.py b/extensions-builtin/SwinIR/scripts/swinir_model.py index d77c3a92..55dd94ab 100644 --- a/extensions-builtin/SwinIR/scripts/swinir_model.py +++ b/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 diff --git a/modules/codeformer/codeformer_arch.py b/modules/codeformer/codeformer_arch.py index f1a7cf09..00c407de 100644 --- a/modules/codeformer/codeformer_arch.py +++ b/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): diff --git a/modules/codeformer/vqgan_arch.py b/modules/codeformer/vqgan_arch.py index e7293683..820e6b12 100644 --- a/modules/codeformer/vqgan_arch.py +++ b/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 diff --git a/modules/codeformer_model.py b/modules/codeformer_model.py index 8d84bbc9..8e56cb89 100644 --- a/modules/codeformer_model.py +++ b/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 imwrite, img2tensor, tensor2img + from basicsr.utils import 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 diff --git a/modules/config_states.py b/modules/config_states.py index 2ea00929..8f1ff428 100644 --- a/modules/config_states.py +++ b/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() diff --git a/modules/esrgan_model.py b/modules/esrgan_model.py index f4369257..85aa6934 100644 --- a/modules/esrgan_model.py +++ b/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 diff --git a/modules/esrgan_model_arch.py b/modules/esrgan_model_arch.py index 7f8bc7c0..4de9dd8d 100644 --- a/modules/esrgan_model_arch.py +++ b/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 diff --git a/modules/extensions.py b/modules/extensions.py index 34d9d654..829f8cd9 100644 --- a/modules/extensions.py +++ b/modules/extensions.py @@ -3,7 +3,6 @@ import sys import traceback import time -from datetime import datetime import git from modules import shared diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index fe8b18b2..f1c59c46 100644 --- a/modules/generation_parameters_copypaste.py +++ b/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*("(?:\\"[^,]|\\"|\\|[^\"])+"|[^,]*)(?:,|$)' diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index 1fc49537..9fe749b7 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/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 diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py index 76599f5a..be168736 100644 --- a/modules/hypernetworks/ui.py +++ b/modules/hypernetworks/ui.py @@ -1,6 +1,4 @@ import html -import os -import re import gradio as gr import modules.hypernetworks.hypernetwork diff --git a/modules/images.py b/modules/images.py index 5eb6d855..7392cb8b 100644 --- a/modules/images.py +++ b/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) diff --git a/modules/img2img.py b/modules/img2img.py index 32b1ecd6..d704bf90 100644 --- a/modules/img2img.py +++ b/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 diff --git a/modules/mac_specific.py b/modules/mac_specific.py index 40ce2101..5c2f92a1 100644 --- a/modules/mac_specific.py +++ b/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 diff --git a/modules/modelloader.py b/modules/modelloader.py index cf685000..92ada694 100644 --- a/modules/modelloader.py +++ b/modules/modelloader.py @@ -1,4 +1,3 @@ -import glob import os import shutil import importlib diff --git a/modules/models/diffusion/uni_pc/uni_pc.py b/modules/models/diffusion/uni_pc/uni_pc.py index 11b330bc..a4c4ef4e 100644 --- a/modules/models/diffusion/uni_pc/uni_pc.py +++ b/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 diff --git a/modules/processing.py b/modules/processing.py index 6f5233c1..c3932d6b 100644 --- a/modules/processing.py +++ b/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 diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py index d8135211..81573b78 100644 --- a/modules/sd_hijack.py +++ b/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 diff --git a/modules/sd_hijack_inpainting.py b/modules/sd_hijack_inpainting.py index 55a2ce4d..344d75c8 100644 --- a/modules/sd_hijack_inpainting.py +++ b/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 diff --git a/modules/sd_hijack_ip2p.py b/modules/sd_hijack_ip2p.py index 41ed54a2..6fe6b6ff 100644 --- a/modules/sd_hijack_ip2p.py +++ b/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 diff --git a/modules/sd_hijack_xlmr.py b/modules/sd_hijack_xlmr.py index 4ac51c38..28528329 100644 --- a/modules/sd_hijack_xlmr.py +++ b/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): diff --git a/modules/sd_models.py b/modules/sd_models.py index 11c1a344..1c09c709 100644 --- a/modules/sd_models.py +++ b/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: diff --git a/modules/sd_models_config.py b/modules/sd_models_config.py index 7a79925a..9bfe1237 100644 --- a/modules/sd_models_config.py +++ b/modules/sd_models_config.py @@ -1,4 +1,3 @@ -import re import os import torch diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index 0fc9f456..3b8e9622 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/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 diff --git a/modules/sd_vae.py b/modules/sd_vae.py index 521e485a..b7176125 100644 --- a/modules/sd_vae.py +++ b/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 diff --git a/modules/shared.py b/modules/shared.py index 4631965b..44cd2c0c 100644 --- a/modules/shared.py +++ b/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 diff --git a/modules/styles.py b/modules/styles.py index 11642075..c22769cf 100644 --- a/modules/styles.py +++ b/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 diff --git a/modules/textual_inversion/autocrop.py b/modules/textual_inversion/autocrop.py index d7d8d2e3..7770d22f 100644 --- a/modules/textual_inversion/autocrop.py +++ b/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" diff --git a/modules/textual_inversion/image_embedding.py b/modules/textual_inversion/image_embedding.py index 5593f88c..ee0e850a 100644 --- a/modules/textual_inversion/image_embedding.py +++ b/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 diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py index da0bcb26..d0cad09e 100644 --- a/modules/textual_inversion/preprocess.py +++ b/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 diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index f753b75f..9ed9ba45 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -1,7 +1,6 @@ import os import sys import traceback -import inspect from collections import namedtuple import torch diff --git a/modules/txt2img.py b/modules/txt2img.py index 16841d0f..f022381c 100644 --- a/modules/txt2img.py +++ b/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() diff --git a/modules/ui.py b/modules/ui.py index 6beda76f..f7e57593 100644 --- a/modules/ui.py +++ b/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 diff --git a/modules/ui_extra_networks.py b/modules/ui_extra_networks.py index 49e06289..800e467a 100644 --- a/modules/ui_extra_networks.py +++ b/modules/ui_extra_networks.py @@ -1,4 +1,3 @@ -import glob import os.path import urllib.parse from pathlib import Path diff --git a/modules/ui_postprocessing.py b/modules/ui_postprocessing.py index f25639e5..c7dc1154 100644 --- a/modules/ui_postprocessing.py +++ b/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 diff --git a/modules/upscaler.py b/modules/upscaler.py index 0ad4fe99..777593b0 100644 --- a/modules/upscaler.py +++ b/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 diff --git a/modules/xlmr.py b/modules/xlmr.py index beab3fdf..e056c3f6 100644 --- a/modules/xlmr.py +++ b/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 diff --git a/pyproject.toml b/pyproject.toml index 1e164abc..9caa9ba2 100644 --- a/pyproject.toml +++ b/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 \ No newline at end of file diff --git a/scripts/custom_code.py b/scripts/custom_code.py index f36a3675..cc6f0d49 100644 --- a/scripts/custom_code.py +++ b/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): diff --git a/scripts/outpainting_mk_2.py b/scripts/outpainting_mk_2.py index b10fed6c..665dbe89 100644 --- a/scripts/outpainting_mk_2.py +++ b/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 diff --git a/scripts/poor_mans_outpainting.py b/scripts/poor_mans_outpainting.py index ddcbd2d3..c0bbecc1 100644 --- a/scripts/poor_mans_outpainting.py +++ b/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): diff --git a/scripts/prompt_matrix.py b/scripts/prompt_matrix.py index e9b11517..fb06beab 100644 --- a/scripts/prompt_matrix.py +++ b/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.shared import opts, cmd_opts, state +from modules.processing import process_images +from modules.shared import opts, state import modules.sd_samplers diff --git a/scripts/prompts_from_file.py b/scripts/prompts_from_file.py index 76dc5778..149bc85f 100644 --- a/scripts/prompts_from_file.py +++ b/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 opts, cmd_opts, state +from modules.shared import state def process_string_tag(tag): diff --git a/scripts/sd_upscale.py b/scripts/sd_upscale.py index 332d76d9..d873a09c 100644 --- a/scripts/sd_upscale.py +++ b/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): diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py index 2ff42ef8..332e0ecd 100644 --- a/scripts/xyz_grid.py +++ b/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 diff --git a/webui.py b/webui.py index ec3d2aba..48277075 100644 --- a/webui.py +++ b/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 -- cgit v1.2.3 From a5121e7a0623db328a9462d340d389ed6737374a Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Wed, 10 May 2023 11:37:18 +0300 Subject: fixes for B007 --- extensions-builtin/LDSR/ldsr_model_arch.py | 2 +- extensions-builtin/Lora/lora.py | 2 +- extensions-builtin/ScuNET/scripts/scunet_model.py | 2 +- extensions-builtin/SwinIR/swinir_model_arch.py | 2 +- extensions-builtin/SwinIR/swinir_model_arch_v2.py | 2 +- modules/codeformer_model.py | 2 +- modules/esrgan_model.py | 8 ++------ modules/extra_networks.py | 2 +- modules/generation_parameters_copypaste.py | 2 +- modules/hypernetworks/hypernetwork.py | 12 ++++++------ modules/images.py | 2 +- modules/interrogate.py | 4 ++-- modules/prompt_parser.py | 14 +++++++------- modules/safe.py | 4 ++-- modules/scripts.py | 10 +++++----- modules/scripts_postprocessing.py | 8 ++++---- modules/sd_hijack_clip.py | 2 +- modules/shared.py | 6 +++--- modules/textual_inversion/learn_schedule.py | 2 +- modules/textual_inversion/textual_inversion.py | 10 +++++----- modules/ui.py | 6 +++--- modules/ui_extra_networks.py | 2 +- modules/ui_tempdir.py | 2 +- modules/upscaler.py | 2 +- pyproject.toml | 1 - scripts/prompts_from_file.py | 2 +- scripts/sd_upscale.py | 4 ++-- scripts/xyz_grid.py | 2 +- 28 files changed, 57 insertions(+), 62 deletions(-) (limited to 'extensions-builtin/ScuNET') diff --git a/extensions-builtin/LDSR/ldsr_model_arch.py b/extensions-builtin/LDSR/ldsr_model_arch.py index a5fb8907..27e38549 100644 --- a/extensions-builtin/LDSR/ldsr_model_arch.py +++ b/extensions-builtin/LDSR/ldsr_model_arch.py @@ -88,7 +88,7 @@ class LDSR: x_t = None logs = None - for n in range(n_runs): + for _ in range(n_runs): if custom_shape is not None: x_t = torch.randn(1, custom_shape[1], custom_shape[2], custom_shape[3]).to(model.device) x_t = repeat(x_t, '1 c h w -> b c h w', b=custom_shape[0]) diff --git a/extensions-builtin/Lora/lora.py b/extensions-builtin/Lora/lora.py index 9795540f..7b56136f 100644 --- a/extensions-builtin/Lora/lora.py +++ b/extensions-builtin/Lora/lora.py @@ -418,7 +418,7 @@ def infotext_pasted(infotext, params): added = [] - for k, v in params.items(): + for k in params: if not k.startswith("AddNet Model "): continue diff --git a/extensions-builtin/ScuNET/scripts/scunet_model.py b/extensions-builtin/ScuNET/scripts/scunet_model.py index aa2fdb3a..1f5ea0d3 100644 --- a/extensions-builtin/ScuNET/scripts/scunet_model.py +++ b/extensions-builtin/ScuNET/scripts/scunet_model.py @@ -132,7 +132,7 @@ class UpscalerScuNET(modules.upscaler.Upscaler): model = net(in_nc=3, config=[4, 4, 4, 4, 4, 4, 4], dim=64) model.load_state_dict(torch.load(filename), strict=True) model.eval() - for k, v in model.named_parameters(): + for _, v in model.named_parameters(): v.requires_grad = False model = model.to(device) diff --git a/extensions-builtin/SwinIR/swinir_model_arch.py b/extensions-builtin/SwinIR/swinir_model_arch.py index 75f7bedc..de195d9b 100644 --- a/extensions-builtin/SwinIR/swinir_model_arch.py +++ b/extensions-builtin/SwinIR/swinir_model_arch.py @@ -848,7 +848,7 @@ class SwinIR(nn.Module): H, W = self.patches_resolution flops += H * W * 3 * self.embed_dim * 9 flops += self.patch_embed.flops() - for i, layer in enumerate(self.layers): + for layer in self.layers: flops += layer.flops() flops += H * W * 3 * self.embed_dim * self.embed_dim flops += self.upsample.flops() diff --git a/extensions-builtin/SwinIR/swinir_model_arch_v2.py b/extensions-builtin/SwinIR/swinir_model_arch_v2.py index d4c0b0da..15777af9 100644 --- a/extensions-builtin/SwinIR/swinir_model_arch_v2.py +++ b/extensions-builtin/SwinIR/swinir_model_arch_v2.py @@ -1001,7 +1001,7 @@ class Swin2SR(nn.Module): H, W = self.patches_resolution flops += H * W * 3 * self.embed_dim * 9 flops += self.patch_embed.flops() - for i, layer in enumerate(self.layers): + for layer in self.layers: flops += layer.flops() flops += H * W * 3 * self.embed_dim * self.embed_dim flops += self.upsample.flops() diff --git a/modules/codeformer_model.py b/modules/codeformer_model.py index 8e56cb89..ececdbae 100644 --- a/modules/codeformer_model.py +++ b/modules/codeformer_model.py @@ -94,7 +94,7 @@ def setup_model(dirname): self.face_helper.get_face_landmarks_5(only_center_face=False, resize=640, eye_dist_threshold=5) self.face_helper.align_warp_face() - for idx, cropped_face in enumerate(self.face_helper.cropped_faces): + for cropped_face in self.face_helper.cropped_faces: cropped_face_t = img2tensor(cropped_face / 255., bgr2rgb=True, float32=True) normalize(cropped_face_t, (0.5, 0.5, 0.5), (0.5, 0.5, 0.5), inplace=True) cropped_face_t = cropped_face_t.unsqueeze(0).to(devices.device_codeformer) diff --git a/modules/esrgan_model.py b/modules/esrgan_model.py index 85aa6934..a009eb42 100644 --- a/modules/esrgan_model.py +++ b/modules/esrgan_model.py @@ -16,9 +16,7 @@ def mod2normal(state_dict): # this code is copied from https://github.com/victorca25/iNNfer if 'conv_first.weight' in state_dict: crt_net = {} - items = [] - for k, v in state_dict.items(): - items.append(k) + items = list(state_dict) crt_net['model.0.weight'] = state_dict['conv_first.weight'] crt_net['model.0.bias'] = state_dict['conv_first.bias'] @@ -52,9 +50,7 @@ def resrgan2normal(state_dict, nb=23): if "conv_first.weight" in state_dict and "body.0.rdb1.conv1.weight" in state_dict: re8x = 0 crt_net = {} - items = [] - for k, v in state_dict.items(): - items.append(k) + items = list(state_dict) crt_net['model.0.weight'] = state_dict['conv_first.weight'] crt_net['model.0.bias'] = state_dict['conv_first.bias'] diff --git a/modules/extra_networks.py b/modules/extra_networks.py index 1978673d..f9db41bc 100644 --- a/modules/extra_networks.py +++ b/modules/extra_networks.py @@ -91,7 +91,7 @@ def deactivate(p, extra_network_data): """call deactivate for extra networks in extra_network_data in specified order, then call deactivate for all remaining registered networks""" - for extra_network_name, extra_network_args in extra_network_data.items(): + for extra_network_name in extra_network_data: extra_network = extra_network_registry.get(extra_network_name, None) if extra_network is None: continue diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 7fbbe707..b0e945a1 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -247,7 +247,7 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model lines.append(lastline) lastline = '' - for i, line in enumerate(lines): + for line in lines: line = line.strip() if line.startswith("Negative prompt:"): done_with_prompt = True diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index 6ef0bfdf..38ef074f 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -177,34 +177,34 @@ class Hypernetwork: def weights(self): res = [] - for k, layers in self.layers.items(): + for layers in self.layers.values(): for layer in layers: res += layer.parameters() return res def train(self, mode=True): - for k, layers in self.layers.items(): + for layers in self.layers.values(): for layer in layers: layer.train(mode=mode) for param in layer.parameters(): param.requires_grad = mode def to(self, device): - for k, layers in self.layers.items(): + for layers in self.layers.values(): for layer in layers: layer.to(device) return self def set_multiplier(self, multiplier): - for k, layers in self.layers.items(): + for layers in self.layers.values(): for layer in layers: layer.multiplier = multiplier return self def eval(self): - for k, layers in self.layers.items(): + for layers in self.layers.values(): for layer in layers: layer.eval() for param in layer.parameters(): @@ -619,7 +619,7 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi try: sd_hijack_checkpoint.add() - for i in range((steps-initial_step) * gradient_step): + for _ in range((steps-initial_step) * gradient_step): if scheduler.finished: break if shared.state.interrupted: diff --git a/modules/images.py b/modules/images.py index 7392cb8b..c4e98c75 100644 --- a/modules/images.py +++ b/modules/images.py @@ -149,7 +149,7 @@ def draw_grid_annotations(im, width, height, hor_texts, ver_texts, margin=0): return ImageFont.truetype(Roboto, fontsize) def draw_texts(drawing, draw_x, draw_y, lines, initial_fnt, initial_fontsize): - for i, line in enumerate(lines): + for line in lines: fnt = initial_fnt fontsize = initial_fontsize while drawing.multiline_textsize(line.text, font=fnt)[0] > line.allowed_width and fontsize > 0: diff --git a/modules/interrogate.py b/modules/interrogate.py index a1c8e537..111b1322 100644 --- a/modules/interrogate.py +++ b/modules/interrogate.py @@ -207,8 +207,8 @@ class InterrogateModels: image_features /= image_features.norm(dim=-1, keepdim=True) - for name, topn, items in self.categories(): - matches = self.rank(image_features, items, top_count=topn) + for cat in self.categories(): + matches = self.rank(image_features, cat.items, top_count=cat.topn) for match, score in matches: if shared.opts.interrogate_return_ranks: res += f", ({match}:{score/100:.3f})" diff --git a/modules/prompt_parser.py b/modules/prompt_parser.py index 3a720721..b4aff704 100644 --- a/modules/prompt_parser.py +++ b/modules/prompt_parser.py @@ -143,7 +143,7 @@ def get_learned_conditioning(model, prompts, steps): conds = model.get_learned_conditioning(texts) cond_schedule = [] - for i, (end_at_step, text) in enumerate(prompt_schedule): + for i, (end_at_step, _) in enumerate(prompt_schedule): cond_schedule.append(ScheduledPromptConditioning(end_at_step, conds[i])) cache[prompt] = cond_schedule @@ -219,8 +219,8 @@ def reconstruct_cond_batch(c: List[List[ScheduledPromptConditioning]], current_s res = torch.zeros((len(c),) + param.shape, device=param.device, dtype=param.dtype) for i, cond_schedule in enumerate(c): target_index = 0 - for current, (end_at, cond) in enumerate(cond_schedule): - if current_step <= end_at: + for current, entry in enumerate(cond_schedule): + if current_step <= entry.end_at_step: target_index = current break res[i] = cond_schedule[target_index].cond @@ -234,13 +234,13 @@ def reconstruct_multicond_batch(c: MulticondLearnedConditioning, current_step): tensors = [] conds_list = [] - for batch_no, composable_prompts in enumerate(c.batch): + for composable_prompts in c.batch: conds_for_batch = [] - for cond_index, composable_prompt in enumerate(composable_prompts): + for composable_prompt in composable_prompts: target_index = 0 - for current, (end_at, cond) in enumerate(composable_prompt.schedules): - if current_step <= end_at: + for current, entry in enumerate(composable_prompt.schedules): + if current_step <= entry.end_at_step: target_index = current break diff --git a/modules/safe.py b/modules/safe.py index 2d5b972f..1e791c5b 100644 --- a/modules/safe.py +++ b/modules/safe.py @@ -95,11 +95,11 @@ def check_pt(filename, extra_handler): except zipfile.BadZipfile: - # if it's not a zip file, it's an olf pytorch format, with five objects written to pickle + # if it's not a zip file, it's an old pytorch format, with five objects written to pickle with open(filename, "rb") as file: unpickler = RestrictedUnpickler(file) unpickler.extra_handler = extra_handler - for i in range(5): + for _ in range(5): unpickler.load() diff --git a/modules/scripts.py b/modules/scripts.py index d945b89f..0c12ebd5 100644 --- a/modules/scripts.py +++ b/modules/scripts.py @@ -231,7 +231,7 @@ def load_scripts(): syspath = sys.path def register_scripts_from_module(module): - for key, script_class in module.__dict__.items(): + for script_class in module.__dict__.values(): if type(script_class) != type: continue @@ -295,9 +295,9 @@ class ScriptRunner: auto_processing_scripts = scripts_auto_postprocessing.create_auto_preprocessing_script_data() - for script_class, path, basedir, script_module in auto_processing_scripts + scripts_data: - script = script_class() - script.filename = path + for script_data in auto_processing_scripts + scripts_data: + script = script_data.script_class() + script.filename = script_data.path script.is_txt2img = not is_img2img script.is_img2img = is_img2img @@ -492,7 +492,7 @@ class ScriptRunner: module = script_loading.load_module(script.filename) cache[filename] = module - for key, script_class in module.__dict__.items(): + for script_class in module.__dict__.values(): if type(script_class) == type and issubclass(script_class, Script): self.scripts[si] = script_class() self.scripts[si].filename = filename diff --git a/modules/scripts_postprocessing.py b/modules/scripts_postprocessing.py index b11568c0..6751406c 100644 --- a/modules/scripts_postprocessing.py +++ b/modules/scripts_postprocessing.py @@ -66,9 +66,9 @@ class ScriptPostprocessingRunner: def initialize_scripts(self, scripts_data): self.scripts = [] - for script_class, path, basedir, script_module in scripts_data: - script: ScriptPostprocessing = script_class() - script.filename = path + for script_data in scripts_data: + script: ScriptPostprocessing = script_data.script_class() + script.filename = script_data.path if script.name == "Simple Upscale": continue @@ -124,7 +124,7 @@ class ScriptPostprocessingRunner: script_args = args[script.args_from:script.args_to] process_args = {} - for (name, component), value in zip(script.controls.items(), script_args): + for (name, component), value in zip(script.controls.items(), script_args): # noqa B007 process_args[name] = value script.process(pp, **process_args) diff --git a/modules/sd_hijack_clip.py b/modules/sd_hijack_clip.py index 9fa5c5c5..c0c350f6 100644 --- a/modules/sd_hijack_clip.py +++ b/modules/sd_hijack_clip.py @@ -223,7 +223,7 @@ class FrozenCLIPEmbedderWithCustomWordsBase(torch.nn.Module): self.hijack.fixes = [x.fixes for x in batch_chunk] for fixes in self.hijack.fixes: - for position, embedding in fixes: + for position, embedding in fixes: # noqa: B007 used_embeddings[embedding.name] = embedding z = self.process_tokens(tokens, multipliers) diff --git a/modules/shared.py b/modules/shared.py index e2691585..913c9e63 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -211,7 +211,7 @@ class OptionInfo: def options_section(section_identifier, options_dict): - for k, v in options_dict.items(): + for v in options_dict.values(): v.section = section_identifier return options_dict @@ -579,7 +579,7 @@ class Options: section_ids = {} settings_items = self.data_labels.items() - for k, item in settings_items: + for _, item in settings_items: if item.section not in section_ids: section_ids[item.section] = len(section_ids) @@ -740,7 +740,7 @@ def walk_files(path, allowed_extensions=None): if allowed_extensions is not None: allowed_extensions = set(allowed_extensions) - for root, dirs, files in os.walk(path): + for root, _, files in os.walk(path): for filename in files: if allowed_extensions is not None: _, ext = os.path.splitext(filename) diff --git a/modules/textual_inversion/learn_schedule.py b/modules/textual_inversion/learn_schedule.py index fda58898..c56bea45 100644 --- a/modules/textual_inversion/learn_schedule.py +++ b/modules/textual_inversion/learn_schedule.py @@ -12,7 +12,7 @@ class LearnScheduleIterator: self.it = 0 self.maxit = 0 try: - for i, pair in enumerate(pairs): + for pair in pairs: if not pair.strip(): continue tmp = pair.split(':') diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index c37bb2ad..47035332 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -29,7 +29,7 @@ textual_inversion_templates = {} def list_textual_inversion_templates(): textual_inversion_templates.clear() - for root, dirs, fns in os.walk(shared.cmd_opts.textual_inversion_templates_dir): + for root, _, fns in os.walk(shared.cmd_opts.textual_inversion_templates_dir): for fn in fns: path = os.path.join(root, fn) @@ -198,7 +198,7 @@ class EmbeddingDatabase: if not os.path.isdir(embdir.path): return - for root, dirs, fns in os.walk(embdir.path, followlinks=True): + for root, _, fns in os.walk(embdir.path, followlinks=True): for fn in fns: try: fullfn = os.path.join(root, fn) @@ -215,7 +215,7 @@ class EmbeddingDatabase: def load_textual_inversion_embeddings(self, force_reload=False): if not force_reload: need_reload = False - for path, embdir in self.embedding_dirs.items(): + for embdir in self.embedding_dirs.values(): if embdir.has_changed(): need_reload = True break @@ -228,7 +228,7 @@ class EmbeddingDatabase: self.skipped_embeddings.clear() self.expected_shape = self.get_expected_shape() - for path, embdir in self.embedding_dirs.items(): + for embdir in self.embedding_dirs.values(): self.load_from_dir(embdir) embdir.update() @@ -469,7 +469,7 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st try: sd_hijack_checkpoint.add() - for i in range((steps-initial_step) * gradient_step): + for _ in range((steps-initial_step) * gradient_step): if scheduler.finished: break if shared.state.interrupted: diff --git a/modules/ui.py b/modules/ui.py index 84d661b2..83bfb7d8 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -416,7 +416,7 @@ def create_sampler_and_steps_selection(choices, tabname): def ordered_ui_categories(): user_order = {x.strip(): i * 2 + 1 for i, x in enumerate(shared.opts.ui_reorder.split(","))} - for i, category in sorted(enumerate(shared.ui_reorder_categories), key=lambda x: user_order.get(x[1], x[0] * 2 + 0)): + for _, category in sorted(enumerate(shared.ui_reorder_categories), key=lambda x: user_order.get(x[1], x[0] * 2 + 0)): yield category @@ -1646,7 +1646,7 @@ def create_ui(): with gr.Blocks(theme=shared.gradio_theme, analytics_enabled=False, title="Stable Diffusion") as demo: with gr.Row(elem_id="quicksettings", variant="compact"): - for i, k, item in sorted(quicksettings_list, key=lambda x: quicksettings_names.get(x[1], x[0])): + for _i, k, _item in sorted(quicksettings_list, key=lambda x: quicksettings_names.get(x[1], x[0])): component = create_setting_component(k, is_quicksettings=True) component_dict[k] = component @@ -1673,7 +1673,7 @@ def create_ui(): outputs=[text_settings, result], ) - for i, k, item in quicksettings_list: + for _i, k, _item in quicksettings_list: component = component_dict[k] info = opts.data_labels[k] diff --git a/modules/ui_extra_networks.py b/modules/ui_extra_networks.py index ab585917..2fd82e8e 100644 --- a/modules/ui_extra_networks.py +++ b/modules/ui_extra_networks.py @@ -90,7 +90,7 @@ class ExtraNetworksPage: subdirs = {} for parentdir in [os.path.abspath(x) for x in self.allowed_directories_for_previews()]: - for root, dirs, files in os.walk(parentdir): + for root, dirs, _ in os.walk(parentdir): for dirname in dirs: x = os.path.join(root, dirname) diff --git a/modules/ui_tempdir.py b/modules/ui_tempdir.py index cac73c51..f05049e1 100644 --- a/modules/ui_tempdir.py +++ b/modules/ui_tempdir.py @@ -72,7 +72,7 @@ def cleanup_tmpdr(): if temp_dir == "" or not os.path.isdir(temp_dir): return - for root, dirs, files in os.walk(temp_dir, topdown=False): + for root, _, files in os.walk(temp_dir, topdown=False): for name in files: _, extension = os.path.splitext(name) if extension != ".png": diff --git a/modules/upscaler.py b/modules/upscaler.py index e145be30..8acb6e96 100644 --- a/modules/upscaler.py +++ b/modules/upscaler.py @@ -55,7 +55,7 @@ class Upscaler: dest_w = int(img.width * scale) dest_h = int(img.height * scale) - for i in range(3): + for _ in range(3): shape = (img.width, img.height) img = self.do_upscale(img, selected_model) diff --git a/pyproject.toml b/pyproject.toml index 346a0cde..c88907be 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -20,7 +20,6 @@ ignore = [ "I001", # Import block is un-sorted or un-formatted "C901", # Function is too complex "C408", # Rewrite as a literal - "B007", # Loop control variable not used within loop body ] diff --git a/scripts/prompts_from_file.py b/scripts/prompts_from_file.py index 149bc85f..27af5ff6 100644 --- a/scripts/prompts_from_file.py +++ b/scripts/prompts_from_file.py @@ -156,7 +156,7 @@ class Script(scripts.Script): images = [] all_prompts = [] infotexts = [] - for n, args in enumerate(jobs): + for args in jobs: state.job = f"{state.job_no + 1} out of {state.job_count}" copy_p = copy.copy(p) diff --git a/scripts/sd_upscale.py b/scripts/sd_upscale.py index d873a09c..0b1d3096 100644 --- a/scripts/sd_upscale.py +++ b/scripts/sd_upscale.py @@ -56,7 +56,7 @@ class Script(scripts.Script): work = [] - for y, h, row in grid.tiles: + for _y, _h, row in grid.tiles: for tiledata in row: work.append(tiledata[2]) @@ -85,7 +85,7 @@ class Script(scripts.Script): work_results += processed.images image_index = 0 - for y, h, row in grid.tiles: + for _y, _h, row in grid.tiles: for tiledata in row: tiledata[2] = work_results[image_index] if image_index < len(work_results) else Image.new("RGB", (p.width, p.height)) image_index += 1 diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py index 332e0ecd..38a20381 100644 --- a/scripts/xyz_grid.py +++ b/scripts/xyz_grid.py @@ -704,7 +704,7 @@ class Script(scripts.Script): if not include_sub_grids: # Done with sub-grids, drop all related information: - for sg in range(z_count): + for _ in range(z_count): del processed.images[1] del processed.all_prompts[1] del processed.all_seeds[1] -- cgit v1.2.3 From 49a55b410b66b7dd9be9335d8a2e3a71e4f8b15c Mon Sep 17 00:00:00 2001 From: Aarni Koskela Date: Thu, 11 May 2023 18:28:15 +0300 Subject: Autofix Ruff W (not W605) (mostly whitespace) --- extensions-builtin/LDSR/ldsr_model_arch.py | 4 +- extensions-builtin/LDSR/sd_hijack_ddpm_v1.py | 6 +-- extensions-builtin/ScuNET/scunet_model_arch.py | 2 +- extensions-builtin/SwinIR/scripts/swinir_model.py | 2 +- extensions-builtin/SwinIR/swinir_model_arch.py | 2 +- extensions-builtin/SwinIR/swinir_model_arch_v2.py | 52 +++++++++++------------ launch.py | 2 +- modules/api/api.py | 4 +- modules/api/models.py | 2 +- modules/cmd_args.py | 2 +- modules/codeformer/codeformer_arch.py | 14 +++--- modules/codeformer/vqgan_arch.py | 38 ++++++++--------- modules/esrgan_model_arch.py | 4 +- modules/extras.py | 2 +- modules/hypernetworks/hypernetwork.py | 12 +++--- modules/images.py | 2 +- modules/mac_specific.py | 4 +- modules/masking.py | 2 +- modules/ngrok.py | 4 +- modules/processing.py | 2 +- modules/script_callbacks.py | 14 +++--- modules/sd_hijack.py | 12 +++--- modules/sd_hijack_optimizations.py | 32 +++++++------- modules/sd_models.py | 4 +- modules/sd_samplers_kdiffusion.py | 18 ++++---- modules/sub_quadratic_attention.py | 2 +- modules/textual_inversion/dataset.py | 4 +- modules/textual_inversion/preprocess.py | 2 +- modules/textual_inversion/textual_inversion.py | 16 +++---- modules/ui.py | 18 ++++---- modules/ui_extensions.py | 6 +-- modules/xlmr.py | 6 +-- pyproject.toml | 5 ++- scripts/img2imgalt.py | 14 +++--- scripts/loopback.py | 8 ++-- scripts/poor_mans_outpainting.py | 2 +- scripts/prompt_matrix.py | 2 +- scripts/prompts_from_file.py | 4 +- scripts/sd_upscale.py | 2 +- 39 files changed, 167 insertions(+), 166 deletions(-) (limited to 'extensions-builtin/ScuNET') diff --git a/extensions-builtin/LDSR/ldsr_model_arch.py b/extensions-builtin/LDSR/ldsr_model_arch.py index 2173de79..7f450086 100644 --- a/extensions-builtin/LDSR/ldsr_model_arch.py +++ b/extensions-builtin/LDSR/ldsr_model_arch.py @@ -130,11 +130,11 @@ class LDSR: im_og = im_og.resize((width_downsampled_pre, height_downsampled_pre), Image.LANCZOS) else: print(f"Down sample rate is 1 from {target_scale} / 4 (Not downsampling)") - + # pad width and height to multiples of 64, pads with the edge values of image to avoid artifacts pad_w, pad_h = np.max(((2, 2), np.ceil(np.array(im_og.size) / 64).astype(int)), axis=0) * 64 - im_og.size im_padded = Image.fromarray(np.pad(np.array(im_og), ((0, pad_h), (0, pad_w), (0, 0)), mode='edge')) - + logs = self.run(model["model"], im_padded, diffusion_steps, eta) sample = logs["sample"] diff --git a/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py b/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py index 57c02d12..631a08ef 100644 --- a/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py +++ b/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py @@ -460,7 +460,7 @@ class LatentDiffusionV1(DDPMV1): self.instantiate_cond_stage(cond_stage_config) self.cond_stage_forward = cond_stage_forward self.clip_denoised = False - self.bbox_tokenizer = None + self.bbox_tokenizer = None self.restarted_from_ckpt = False if ckpt_path is not None: @@ -792,7 +792,7 @@ class LatentDiffusionV1(DDPMV1): z = z.view((z.shape[0], -1, ks[0], ks[1], z.shape[-1])) # (bn, nc, ks[0], ks[1], L ) # 2. apply model loop over last dim - if isinstance(self.first_stage_model, VQModelInterface): + if isinstance(self.first_stage_model, VQModelInterface): output_list = [self.first_stage_model.decode(z[:, :, :, :, i], force_not_quantize=predict_cids or force_not_quantize) for i in range(z.shape[-1])] @@ -890,7 +890,7 @@ class LatentDiffusionV1(DDPMV1): if hasattr(self, "split_input_params"): assert len(cond) == 1 # todo can only deal with one conditioning atm - assert not return_ids + assert not return_ids ks = self.split_input_params["ks"] # eg. (128, 128) stride = self.split_input_params["stride"] # eg. (64, 64) diff --git a/extensions-builtin/ScuNET/scunet_model_arch.py b/extensions-builtin/ScuNET/scunet_model_arch.py index 8028918a..b51a8806 100644 --- a/extensions-builtin/ScuNET/scunet_model_arch.py +++ b/extensions-builtin/ScuNET/scunet_model_arch.py @@ -265,4 +265,4 @@ class SCUNet(nn.Module): nn.init.constant_(m.bias, 0) elif isinstance(m, nn.LayerNorm): nn.init.constant_(m.bias, 0) - nn.init.constant_(m.weight, 1.0) \ No newline at end of file + nn.init.constant_(m.weight, 1.0) diff --git a/extensions-builtin/SwinIR/scripts/swinir_model.py b/extensions-builtin/SwinIR/scripts/swinir_model.py index 55dd94ab..0ba50487 100644 --- a/extensions-builtin/SwinIR/scripts/swinir_model.py +++ b/extensions-builtin/SwinIR/scripts/swinir_model.py @@ -150,7 +150,7 @@ def inference(img, model, tile, tile_overlap, window_size, scale): for w_idx in w_idx_list: if state.interrupted or state.skipped: break - + in_patch = img[..., h_idx: h_idx + tile, w_idx: w_idx + tile] out_patch = model(in_patch) out_patch_mask = torch.ones_like(out_patch) diff --git a/extensions-builtin/SwinIR/swinir_model_arch.py b/extensions-builtin/SwinIR/swinir_model_arch.py index 73e37cfa..93b93274 100644 --- a/extensions-builtin/SwinIR/swinir_model_arch.py +++ b/extensions-builtin/SwinIR/swinir_model_arch.py @@ -805,7 +805,7 @@ class SwinIR(nn.Module): def forward(self, x): H, W = x.shape[2:] x = self.check_image_size(x) - + self.mean = self.mean.type_as(x) x = (x - self.mean) * self.img_range diff --git a/extensions-builtin/SwinIR/swinir_model_arch_v2.py b/extensions-builtin/SwinIR/swinir_model_arch_v2.py index 3ca9be78..dad22cca 100644 --- a/extensions-builtin/SwinIR/swinir_model_arch_v2.py +++ b/extensions-builtin/SwinIR/swinir_model_arch_v2.py @@ -241,7 +241,7 @@ class SwinTransformerBlock(nn.Module): attn_mask = None self.register_buffer("attn_mask", attn_mask) - + def calculate_mask(self, x_size): # calculate attention mask for SW-MSA H, W = x_size @@ -263,7 +263,7 @@ class SwinTransformerBlock(nn.Module): attn_mask = mask_windows.unsqueeze(1) - mask_windows.unsqueeze(2) attn_mask = attn_mask.masked_fill(attn_mask != 0, float(-100.0)).masked_fill(attn_mask == 0, float(0.0)) - return attn_mask + return attn_mask def forward(self, x, x_size): H, W = x_size @@ -288,7 +288,7 @@ class SwinTransformerBlock(nn.Module): attn_windows = self.attn(x_windows, mask=self.attn_mask) # nW*B, window_size*window_size, C else: attn_windows = self.attn(x_windows, mask=self.calculate_mask(x_size).to(x.device)) - + # merge windows attn_windows = attn_windows.view(-1, self.window_size, self.window_size, C) shifted_x = window_reverse(attn_windows, self.window_size, H, W) # B H' W' C @@ -369,7 +369,7 @@ class PatchMerging(nn.Module): H, W = self.input_resolution flops = (H // 2) * (W // 2) * 4 * self.dim * 2 * self.dim flops += H * W * self.dim // 2 - return flops + return flops class BasicLayer(nn.Module): """ A basic Swin Transformer layer for one stage. @@ -447,7 +447,7 @@ class BasicLayer(nn.Module): nn.init.constant_(blk.norm1.weight, 0) nn.init.constant_(blk.norm2.bias, 0) nn.init.constant_(blk.norm2.weight, 0) - + class PatchEmbed(nn.Module): r""" Image to Patch Embedding Args: @@ -492,7 +492,7 @@ class PatchEmbed(nn.Module): flops = Ho * Wo * self.embed_dim * self.in_chans * (self.patch_size[0] * self.patch_size[1]) if self.norm is not None: flops += Ho * Wo * self.embed_dim - return flops + return flops class RSTB(nn.Module): """Residual Swin Transformer Block (RSTB). @@ -531,7 +531,7 @@ class RSTB(nn.Module): num_heads=num_heads, window_size=window_size, mlp_ratio=mlp_ratio, - qkv_bias=qkv_bias, + qkv_bias=qkv_bias, drop=drop, attn_drop=attn_drop, drop_path=drop_path, norm_layer=norm_layer, @@ -622,7 +622,7 @@ class Upsample(nn.Sequential): else: raise ValueError(f'scale {scale} is not supported. ' 'Supported scales: 2^n and 3.') super(Upsample, self).__init__(*m) - + class Upsample_hf(nn.Sequential): """Upsample module. @@ -642,7 +642,7 @@ class Upsample_hf(nn.Sequential): m.append(nn.PixelShuffle(3)) else: raise ValueError(f'scale {scale} is not supported. ' 'Supported scales: 2^n and 3.') - super(Upsample_hf, self).__init__(*m) + super(Upsample_hf, self).__init__(*m) class UpsampleOneStep(nn.Sequential): @@ -667,8 +667,8 @@ class UpsampleOneStep(nn.Sequential): H, W = self.input_resolution flops = H * W * self.num_feat * 3 * 9 return flops - - + + class Swin2SR(nn.Module): r""" Swin2SR @@ -699,7 +699,7 @@ class Swin2SR(nn.Module): def __init__(self, img_size=64, patch_size=1, in_chans=3, embed_dim=96, depths=(6, 6, 6, 6), num_heads=(6, 6, 6, 6), - window_size=7, mlp_ratio=4., qkv_bias=True, + window_size=7, mlp_ratio=4., qkv_bias=True, drop_rate=0., attn_drop_rate=0., drop_path_rate=0.1, norm_layer=nn.LayerNorm, ape=False, patch_norm=True, use_checkpoint=False, upscale=2, img_range=1., upsampler='', resi_connection='1conv', @@ -764,7 +764,7 @@ class Swin2SR(nn.Module): num_heads=num_heads[i_layer], window_size=window_size, mlp_ratio=self.mlp_ratio, - qkv_bias=qkv_bias, + qkv_bias=qkv_bias, drop=drop_rate, attn_drop=attn_drop_rate, drop_path=dpr[sum(depths[:i_layer]):sum(depths[:i_layer + 1])], # no impact on SR results norm_layer=norm_layer, @@ -776,7 +776,7 @@ class Swin2SR(nn.Module): ) self.layers.append(layer) - + if self.upsampler == 'pixelshuffle_hf': self.layers_hf = nn.ModuleList() for i_layer in range(self.num_layers): @@ -787,7 +787,7 @@ class Swin2SR(nn.Module): num_heads=num_heads[i_layer], window_size=window_size, mlp_ratio=self.mlp_ratio, - qkv_bias=qkv_bias, + qkv_bias=qkv_bias, drop=drop_rate, attn_drop=attn_drop_rate, drop_path=dpr[sum(depths[:i_layer]):sum(depths[:i_layer + 1])], # no impact on SR results norm_layer=norm_layer, @@ -799,7 +799,7 @@ class Swin2SR(nn.Module): ) self.layers_hf.append(layer) - + self.norm = norm_layer(self.num_features) # build the last conv layer in deep feature extraction @@ -829,10 +829,10 @@ class Swin2SR(nn.Module): self.conv_aux = nn.Conv2d(num_feat, num_out_ch, 3, 1, 1) self.conv_after_aux = nn.Sequential( nn.Conv2d(3, num_feat, 3, 1, 1), - nn.LeakyReLU(inplace=True)) + nn.LeakyReLU(inplace=True)) self.upsample = Upsample(upscale, num_feat) self.conv_last = nn.Conv2d(num_feat, num_out_ch, 3, 1, 1) - + elif self.upsampler == 'pixelshuffle_hf': self.conv_before_upsample = nn.Sequential(nn.Conv2d(embed_dim, num_feat, 3, 1, 1), nn.LeakyReLU(inplace=True)) @@ -846,7 +846,7 @@ class Swin2SR(nn.Module): nn.Conv2d(embed_dim, num_feat, 3, 1, 1), nn.LeakyReLU(inplace=True)) self.conv_last_hf = nn.Conv2d(num_feat, num_out_ch, 3, 1, 1) - + elif self.upsampler == 'pixelshuffledirect': # for lightweight SR (to save parameters) self.upsample = UpsampleOneStep(upscale, embed_dim, num_out_ch, @@ -905,7 +905,7 @@ class Swin2SR(nn.Module): x = self.patch_unembed(x, x_size) return x - + def forward_features_hf(self, x): x_size = (x.shape[2], x.shape[3]) x = self.patch_embed(x) @@ -919,7 +919,7 @@ class Swin2SR(nn.Module): x = self.norm(x) # B L C x = self.patch_unembed(x, x_size) - return x + return x def forward(self, x): H, W = x.shape[2:] @@ -951,7 +951,7 @@ class Swin2SR(nn.Module): x = self.conv_after_body(self.forward_features(x)) + x x_before = self.conv_before_upsample(x) x_out = self.conv_last(self.upsample(x_before)) - + x_hf = self.conv_first_hf(x_before) x_hf = self.conv_after_body_hf(self.forward_features_hf(x_hf)) + x_hf x_hf = self.conv_before_upsample_hf(x_hf) @@ -977,15 +977,15 @@ class Swin2SR(nn.Module): x_first = self.conv_first(x) res = self.conv_after_body(self.forward_features(x_first)) + x_first x = x + self.conv_last(res) - + x = x / self.img_range + self.mean if self.upsampler == "pixelshuffle_aux": return x[:, :, :H*self.upscale, :W*self.upscale], aux - + elif self.upsampler == "pixelshuffle_hf": x_out = x_out / self.img_range + self.mean return x_out[:, :, :H*self.upscale, :W*self.upscale], x[:, :, :H*self.upscale, :W*self.upscale], x_hf[:, :, :H*self.upscale, :W*self.upscale] - + else: return x[:, :, :H*self.upscale, :W*self.upscale] @@ -1014,4 +1014,4 @@ if __name__ == '__main__': x = torch.randn((1, 3, height, width)) x = model(x) - print(x.shape) \ No newline at end of file + print(x.shape) diff --git a/launch.py b/launch.py index 670af87c..62b33f14 100644 --- a/launch.py +++ b/launch.py @@ -327,7 +327,7 @@ def prepare_environment(): if args.update_all_extensions: git_pull_recursive(extensions_dir) - + if "--exit" in sys.argv: print("Exiting because of --exit argument") exit(0) diff --git a/modules/api/api.py b/modules/api/api.py index 594fa655..165985c3 100644 --- a/modules/api/api.py +++ b/modules/api/api.py @@ -227,7 +227,7 @@ class Api: script_idx = script_name_to_index(script_name, script_runner.selectable_scripts) script = script_runner.selectable_scripts[script_idx] return script, script_idx - + def get_scripts_list(self): t2ilist = [str(title.lower()) for title in scripts.scripts_txt2img.titles] i2ilist = [str(title.lower()) for title in scripts.scripts_img2img.titles] @@ -237,7 +237,7 @@ class Api: def get_script(self, script_name, script_runner): if script_name is None or script_name == "": return None, None - + script_idx = script_name_to_index(script_name, script_runner.scripts) return script_runner.scripts[script_idx] diff --git a/modules/api/models.py b/modules/api/models.py index 4d291076..006ccdb7 100644 --- a/modules/api/models.py +++ b/modules/api/models.py @@ -289,4 +289,4 @@ class MemoryResponse(BaseModel): class ScriptsList(BaseModel): txt2img: list = Field(default=None,title="Txt2img", description="Titles of scripts (txt2img)") - img2img: list = Field(default=None,title="Img2img", description="Titles of scripts (img2img)") \ No newline at end of file + img2img: list = Field(default=None,title="Img2img", description="Titles of scripts (img2img)") diff --git a/modules/cmd_args.py b/modules/cmd_args.py index e01ca655..f4a4ab36 100644 --- a/modules/cmd_args.py +++ b/modules/cmd_args.py @@ -102,4 +102,4 @@ parser.add_argument("--no-gradio-queue", action='store_true', help="Disables gra parser.add_argument("--skip-version-check", action='store_true', help="Do not check versions of torch and xformers") parser.add_argument("--no-hashing", action='store_true', help="disable sha256 hashing of checkpoints to help loading performance", default=False) parser.add_argument("--no-download-sd-model", action='store_true', help="don't download SD1.5 model even if no model is found in --ckpt-dir", default=False) -parser.add_argument('--subpath', type=str, help='customize the subpath for gradio, use with reverse proxy') \ No newline at end of file +parser.add_argument('--subpath', type=str, help='customize the subpath for gradio, use with reverse proxy') diff --git a/modules/codeformer/codeformer_arch.py b/modules/codeformer/codeformer_arch.py index 45c70f84..12db6814 100644 --- a/modules/codeformer/codeformer_arch.py +++ b/modules/codeformer/codeformer_arch.py @@ -119,7 +119,7 @@ class TransformerSALayer(nn.Module): tgt_mask: Optional[Tensor] = None, tgt_key_padding_mask: Optional[Tensor] = None, query_pos: Optional[Tensor] = None): - + # self attention tgt2 = self.norm1(tgt) q = k = self.with_pos_embed(tgt2, query_pos) @@ -159,7 +159,7 @@ class Fuse_sft_block(nn.Module): @ARCH_REGISTRY.register() class CodeFormer(VQAutoEncoder): - def __init__(self, dim_embd=512, n_head=8, n_layers=9, + def __init__(self, dim_embd=512, n_head=8, n_layers=9, codebook_size=1024, latent_size=256, connect_list=('32', '64', '128', '256'), fix_modules=('quantize', 'generator')): @@ -179,14 +179,14 @@ class CodeFormer(VQAutoEncoder): self.feat_emb = nn.Linear(256, self.dim_embd) # transformer - self.ft_layers = nn.Sequential(*[TransformerSALayer(embed_dim=dim_embd, nhead=n_head, dim_mlp=self.dim_mlp, dropout=0.0) + self.ft_layers = nn.Sequential(*[TransformerSALayer(embed_dim=dim_embd, nhead=n_head, dim_mlp=self.dim_mlp, dropout=0.0) for _ in range(self.n_layers)]) # logits_predict head self.idx_pred_layer = nn.Sequential( nn.LayerNorm(dim_embd), nn.Linear(dim_embd, codebook_size, bias=False)) - + self.channels = { '16': 512, '32': 256, @@ -221,7 +221,7 @@ class CodeFormer(VQAutoEncoder): enc_feat_dict = {} out_list = [self.fuse_encoder_block[f_size] for f_size in self.connect_list] for i, block in enumerate(self.encoder.blocks): - x = block(x) + x = block(x) if i in out_list: enc_feat_dict[str(x.shape[-1])] = x.clone() @@ -266,11 +266,11 @@ class CodeFormer(VQAutoEncoder): fuse_list = [self.fuse_generator_block[f_size] for f_size in self.connect_list] for i, block in enumerate(self.generator.blocks): - x = block(x) + x = block(x) if i in fuse_list: # fuse after i-th block f_size = str(x.shape[-1]) if w>0: x = self.fuse_convs_dict[f_size](enc_feat_dict[f_size].detach(), x, w) out = x # logits doesn't need softmax before cross_entropy loss - return out, logits, lq_feat \ No newline at end of file + return out, logits, lq_feat diff --git a/modules/codeformer/vqgan_arch.py b/modules/codeformer/vqgan_arch.py index b24a0394..09ee6660 100644 --- a/modules/codeformer/vqgan_arch.py +++ b/modules/codeformer/vqgan_arch.py @@ -13,7 +13,7 @@ from basicsr.utils.registry import ARCH_REGISTRY def normalize(in_channels): return torch.nn.GroupNorm(num_groups=32, num_channels=in_channels, eps=1e-6, affine=True) - + @torch.jit.script def swish(x): @@ -210,15 +210,15 @@ class AttnBlock(nn.Module): # compute attention b, c, h, w = q.shape q = q.reshape(b, c, h*w) - q = q.permute(0, 2, 1) + q = q.permute(0, 2, 1) k = k.reshape(b, c, h*w) - w_ = torch.bmm(q, k) + w_ = torch.bmm(q, k) w_ = w_ * (int(c)**(-0.5)) w_ = F.softmax(w_, dim=2) # attend to values v = v.reshape(b, c, h*w) - w_ = w_.permute(0, 2, 1) + w_ = w_.permute(0, 2, 1) h_ = torch.bmm(v, w_) h_ = h_.reshape(b, c, h, w) @@ -270,18 +270,18 @@ class Encoder(nn.Module): def forward(self, x): for block in self.blocks: x = block(x) - + return x class Generator(nn.Module): def __init__(self, nf, emb_dim, ch_mult, res_blocks, img_size, attn_resolutions): super().__init__() - self.nf = nf - self.ch_mult = ch_mult + self.nf = nf + self.ch_mult = ch_mult self.num_resolutions = len(self.ch_mult) self.num_res_blocks = res_blocks - self.resolution = img_size + self.resolution = img_size self.attn_resolutions = attn_resolutions self.in_channels = emb_dim self.out_channels = 3 @@ -315,24 +315,24 @@ class Generator(nn.Module): blocks.append(nn.Conv2d(block_in_ch, self.out_channels, kernel_size=3, stride=1, padding=1)) self.blocks = nn.ModuleList(blocks) - + def forward(self, x): for block in self.blocks: x = block(x) - + return x - + @ARCH_REGISTRY.register() class VQAutoEncoder(nn.Module): def __init__(self, img_size, nf, ch_mult, quantizer="nearest", res_blocks=2, attn_resolutions=None, codebook_size=1024, emb_dim=256, beta=0.25, gumbel_straight_through=False, gumbel_kl_weight=1e-8, model_path=None): super().__init__() logger = get_root_logger() - self.in_channels = 3 - self.nf = nf - self.n_blocks = res_blocks + self.in_channels = 3 + self.nf = nf + self.n_blocks = res_blocks self.codebook_size = codebook_size self.embed_dim = emb_dim self.ch_mult = ch_mult @@ -363,11 +363,11 @@ class VQAutoEncoder(nn.Module): self.kl_weight ) self.generator = Generator( - self.nf, + self.nf, self.embed_dim, - self.ch_mult, - self.n_blocks, - self.resolution, + self.ch_mult, + self.n_blocks, + self.resolution, self.attn_resolutions ) @@ -432,4 +432,4 @@ class VQGANDiscriminator(nn.Module): raise ValueError('Wrong params!') def forward(self, x): - return self.main(x) \ No newline at end of file + return self.main(x) diff --git a/modules/esrgan_model_arch.py b/modules/esrgan_model_arch.py index 4de9dd8d..2b9888ba 100644 --- a/modules/esrgan_model_arch.py +++ b/modules/esrgan_model_arch.py @@ -105,7 +105,7 @@ class ResidualDenseBlock_5C(nn.Module): Modified options that can be used: - "Partial Convolution based Padding" arXiv:1811.11718 - "Spectral normalization" arXiv:1802.05957 - - "ICASSP 2020 - ESRGAN+ : Further Improving ESRGAN" N. C. + - "ICASSP 2020 - ESRGAN+ : Further Improving ESRGAN" N. C. {Rakotonirina} and A. {Rasoanaivo} """ @@ -170,7 +170,7 @@ class GaussianNoise(nn.Module): scale = self.sigma * x.detach() if self.is_relative_detach else self.sigma * x sampled_noise = self.noise.repeat(*x.size()).normal_() * scale x = x + sampled_noise - return x + return x def conv1x1(in_planes, out_planes, stride=1): return nn.Conv2d(in_planes, out_planes, kernel_size=1, stride=stride, bias=False) diff --git a/modules/extras.py b/modules/extras.py index eb4f0b42..bdf9b3b7 100644 --- a/modules/extras.py +++ b/modules/extras.py @@ -199,7 +199,7 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_ result_is_inpainting_model = True else: theta_0[key] = theta_func2(a, b, multiplier) - + theta_0[key] = to_half(theta_0[key], save_as_half) shared.state.sampling_step += 1 diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index 38ef074f..570b5603 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -540,7 +540,7 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi return hypernetwork, filename scheduler = LearnRateScheduler(learn_rate, steps, initial_step) - + clip_grad = torch.nn.utils.clip_grad_value_ if clip_grad_mode == "value" else torch.nn.utils.clip_grad_norm_ if clip_grad_mode == "norm" else None if clip_grad: clip_grad_sched = LearnRateScheduler(clip_grad_value, steps, initial_step, verbose=False) @@ -593,7 +593,7 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi print(e) scaler = torch.cuda.amp.GradScaler() - + batch_size = ds.batch_size gradient_step = ds.gradient_step # n steps = batch_size * gradient_step * n image processed @@ -636,7 +636,7 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi if clip_grad: clip_grad_sched.step(hypernetwork.step) - + with devices.autocast(): x = batch.latent_sample.to(devices.device, non_blocking=pin_memory) if use_weight: @@ -657,14 +657,14 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi _loss_step += loss.item() scaler.scale(loss).backward() - + # go back until we reach gradient accumulation steps if (j + 1) % gradient_step != 0: continue loss_logging.append(_loss_step) if clip_grad: clip_grad(weights, clip_grad_sched.learn_rate) - + scaler.step(optimizer) scaler.update() hypernetwork.step += 1 @@ -674,7 +674,7 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi _loss_step = 0 steps_done = hypernetwork.step + 1 - + epoch_num = hypernetwork.step // steps_per_epoch epoch_step = hypernetwork.step % steps_per_epoch diff --git a/modules/images.py b/modules/images.py index 3b8b62d9..b2de3662 100644 --- a/modules/images.py +++ b/modules/images.py @@ -367,7 +367,7 @@ class FilenameGenerator: self.seed = seed self.prompt = prompt self.image = image - + def hasprompt(self, *args): lower = self.prompt.lower() if self.p is None or self.prompt is None: diff --git a/modules/mac_specific.py b/modules/mac_specific.py index 5c2f92a1..d74c6b95 100644 --- a/modules/mac_specific.py +++ b/modules/mac_specific.py @@ -42,7 +42,7 @@ if has_mps: # MPS workaround for https://github.com/pytorch/pytorch/issues/79383 CondFunc('torch.Tensor.to', lambda orig_func, self, *args, **kwargs: orig_func(self.contiguous(), *args, **kwargs), lambda _, self, *args, **kwargs: self.device.type != 'mps' and (args and isinstance(args[0], torch.device) and args[0].type == 'mps' or isinstance(kwargs.get('device'), torch.device) and kwargs['device'].type == 'mps')) - # MPS workaround for https://github.com/pytorch/pytorch/issues/80800 + # MPS workaround for https://github.com/pytorch/pytorch/issues/80800 CondFunc('torch.nn.functional.layer_norm', lambda orig_func, *args, **kwargs: orig_func(*([args[0].contiguous()] + list(args[1:])), **kwargs), lambda _, *args, **kwargs: args and isinstance(args[0], torch.Tensor) and args[0].device.type == 'mps') # MPS workaround for https://github.com/pytorch/pytorch/issues/90532 @@ -60,4 +60,4 @@ if has_mps: # MPS workaround for https://github.com/pytorch/pytorch/issues/92311 if platform.processor() == 'i386': for funcName in ['torch.argmax', 'torch.Tensor.argmax']: - CondFunc(funcName, lambda _, input, *args, **kwargs: torch.max(input.float() if input.dtype == torch.int64 else input, *args, **kwargs)[1], lambda _, input, *args, **kwargs: input.device.type == 'mps') \ No newline at end of file + CondFunc(funcName, lambda _, input, *args, **kwargs: torch.max(input.float() if input.dtype == torch.int64 else input, *args, **kwargs)[1], lambda _, input, *args, **kwargs: input.device.type == 'mps') diff --git a/modules/masking.py b/modules/masking.py index a5c4d2da..be9f84c7 100644 --- a/modules/masking.py +++ b/modules/masking.py @@ -4,7 +4,7 @@ from PIL import Image, ImageFilter, ImageOps def get_crop_region(mask, pad=0): """finds a rectangular region that contains all masked ares in an image. Returns (x1, y1, x2, y2) coordinates of the rectangle. For example, if a user has painted the top-right part of a 512x512 image", the result may be (256, 0, 512, 256)""" - + h, w = mask.shape crop_left = 0 diff --git a/modules/ngrok.py b/modules/ngrok.py index 7a7b4b26..67a74e85 100644 --- a/modules/ngrok.py +++ b/modules/ngrok.py @@ -13,7 +13,7 @@ def connect(token, port, region): config = conf.PyngrokConfig( auth_token=token, region=region ) - + # Guard for existing tunnels existing = ngrok.get_tunnels(pyngrok_config=config) if existing: @@ -24,7 +24,7 @@ def connect(token, port, region): print(f'ngrok has already been connected to localhost:{port}! URL: {public_url}\n' 'You can use this link after the launch is complete.') return - + try: if account is None: public_url = ngrok.connect(port, pyngrok_config=config, bind_tls=True).public_url diff --git a/modules/processing.py b/modules/processing.py index c3932d6b..f902b9df 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -164,7 +164,7 @@ class StableDiffusionProcessing: self.all_subseeds = None self.iteration = 0 self.is_hr_pass = False - + @property def sd_model(self): diff --git a/modules/script_callbacks.py b/modules/script_callbacks.py index 17109732..7d9dd736 100644 --- a/modules/script_callbacks.py +++ b/modules/script_callbacks.py @@ -32,22 +32,22 @@ class CFGDenoiserParams: def __init__(self, x, image_cond, sigma, sampling_step, total_sampling_steps, text_cond, text_uncond): self.x = x """Latent image representation in the process of being denoised""" - + self.image_cond = image_cond """Conditioning image""" - + self.sigma = sigma """Current sigma noise step value""" - + self.sampling_step = sampling_step """Current Sampling step number""" - + self.total_sampling_steps = total_sampling_steps """Total number of sampling steps planned""" - + self.text_cond = text_cond """ Encoder hidden states of text conditioning from prompt""" - + self.text_uncond = text_uncond """ Encoder hidden states of text conditioning from negative prompt""" @@ -240,7 +240,7 @@ def add_callback(callbacks, fun): callbacks.append(ScriptCallback(filename, fun)) - + def remove_current_script_callbacks(): stack = [x for x in inspect.stack() if x.filename != __file__] filename = stack[0].filename if len(stack) > 0 else 'unknown file' diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py index e374aeb8..7e50f1ab 100644 --- a/modules/sd_hijack.py +++ b/modules/sd_hijack.py @@ -34,7 +34,7 @@ def apply_optimizations(): ldm.modules.diffusionmodules.model.nonlinearity = silu ldm.modules.diffusionmodules.openaimodel.th = sd_hijack_unet.th - + optimization_method = None can_use_sdp = hasattr(torch.nn.functional, "scaled_dot_product_attention") and callable(torch.nn.functional.scaled_dot_product_attention) # not everyone has torch 2.x to use sdp @@ -92,12 +92,12 @@ def fix_checkpoint(): def weighted_loss(sd_model, pred, target, mean=True): #Calculate the weight normally, but ignore the mean loss = sd_model._old_get_loss(pred, target, mean=False) - + #Check if we have weights available weight = getattr(sd_model, '_custom_loss_weight', None) if weight is not None: loss *= weight - + #Return the loss, as mean if specified return loss.mean() if mean else loss @@ -105,7 +105,7 @@ def weighted_forward(sd_model, x, c, w, *args, **kwargs): try: #Temporarily append weights to a place accessible during loss calc sd_model._custom_loss_weight = w - + #Replace 'get_loss' with a weight-aware one. Otherwise we need to reimplement 'forward' completely #Keep 'get_loss', but don't overwrite the previous old_get_loss if it's already set if not hasattr(sd_model, '_old_get_loss'): @@ -120,7 +120,7 @@ def weighted_forward(sd_model, x, c, w, *args, **kwargs): del sd_model._custom_loss_weight except AttributeError: pass - + #If we have an old loss function, reset the loss function to the original one if hasattr(sd_model, '_old_get_loss'): sd_model.get_loss = sd_model._old_get_loss @@ -184,7 +184,7 @@ class StableDiffusionModelHijack: def undo_hijack(self, m): if type(m.cond_stage_model) == xlmr.BertSeriesModelWithTransformation: - m.cond_stage_model = m.cond_stage_model.wrapped + m.cond_stage_model = m.cond_stage_model.wrapped elif type(m.cond_stage_model) == sd_hijack_clip.FrozenCLIPEmbedderWithCustomWords: m.cond_stage_model = m.cond_stage_model.wrapped diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py index a174bbe1..f00fe55c 100644 --- a/modules/sd_hijack_optimizations.py +++ b/modules/sd_hijack_optimizations.py @@ -62,10 +62,10 @@ def split_cross_attention_forward_v1(self, x, context=None, mask=None): end = i + 2 s1 = einsum('b i d, b j d -> b i j', q[i:end], k[i:end]) s1 *= self.scale - + s2 = s1.softmax(dim=-1) del s1 - + r1[i:end] = einsum('b i j, b j d -> b i d', s2, v[i:end]) del s2 del q, k, v @@ -95,43 +95,43 @@ def split_cross_attention_forward(self, x, context=None, mask=None): with devices.without_autocast(disable=not shared.opts.upcast_attn): k_in = k_in * self.scale - + del context, x - + q, k, v = (rearrange(t, 'b n (h d) -> (b h) n d', h=h) for t in (q_in, k_in, v_in)) del q_in, k_in, v_in - + r1 = torch.zeros(q.shape[0], q.shape[1], v.shape[2], device=q.device, dtype=q.dtype) - + mem_free_total = get_available_vram() - + gb = 1024 ** 3 tensor_size = q.shape[0] * q.shape[1] * k.shape[1] * q.element_size() modifier = 3 if q.element_size() == 2 else 2.5 mem_required = tensor_size * modifier steps = 1 - + if mem_required > mem_free_total: steps = 2 ** (math.ceil(math.log(mem_required / mem_free_total, 2))) # print(f"Expected tensor size:{tensor_size/gb:0.1f}GB, cuda free:{mem_free_cuda/gb:0.1f}GB " # f"torch free:{mem_free_torch/gb:0.1f} total:{mem_free_total/gb:0.1f} steps:{steps}") - + if steps > 64: max_res = math.floor(math.sqrt(math.sqrt(mem_free_total / 2.5)) / 8) * 64 raise RuntimeError(f'Not enough memory, use lower resolution (max approx. {max_res}x{max_res}). ' f'Need: {mem_required / 64 / gb:0.1f}GB free, Have:{mem_free_total / gb:0.1f}GB free') - + slice_size = q.shape[1] // steps if (q.shape[1] % steps) == 0 else q.shape[1] for i in range(0, q.shape[1], slice_size): end = i + slice_size s1 = einsum('b i d, b j d -> b i j', q[:, i:end], k) - + s2 = s1.softmax(dim=-1, dtype=q.dtype) del s1 - + r1[:, i:end] = einsum('b i j, b j d -> b i d', s2, v) del s2 - + del q, k, v r1 = r1.to(dtype) @@ -228,7 +228,7 @@ def split_cross_attention_forward_invokeAI(self, x, context=None, mask=None): with devices.without_autocast(disable=not shared.opts.upcast_attn): k = k * self.scale - + q, k, v = (rearrange(t, 'b n (h d) -> (b h) n d', h=h) for t in (q, k, v)) r = einsum_op(q, k, v) r = r.to(dtype) @@ -369,7 +369,7 @@ def scaled_dot_product_attention_forward(self, x, context=None, mask=None): q = q_in.view(batch_size, -1, h, head_dim).transpose(1, 2) k = k_in.view(batch_size, -1, h, head_dim).transpose(1, 2) v = v_in.view(batch_size, -1, h, head_dim).transpose(1, 2) - + del q_in, k_in, v_in dtype = q.dtype @@ -451,7 +451,7 @@ def cross_attention_attnblock_forward(self, x): h3 += x return h3 - + def xformers_attnblock_forward(self, x): try: h_ = x diff --git a/modules/sd_models.py b/modules/sd_models.py index d1e946a5..3316d021 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -165,7 +165,7 @@ def model_hash(filename): def select_checkpoint(): model_checkpoint = shared.opts.sd_model_checkpoint - + checkpoint_info = checkpoint_alisases.get(model_checkpoint, None) if checkpoint_info is not None: return checkpoint_info @@ -372,7 +372,7 @@ def enable_midas_autodownload(): if not os.path.exists(path): if not os.path.exists(midas_path): mkdir(midas_path) - + print(f"Downloading midas model weights for {model_type} to {path}") request.urlretrieve(midas_urls[model_type], path) print(f"{model_type} downloaded") diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index 2f733cf5..e9e41818 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -93,10 +93,10 @@ class CFGDenoiser(torch.nn.Module): if shared.sd_model.model.conditioning_key == "crossattn-adm": image_uncond = torch.zeros_like(image_cond) - make_condition_dict = lambda c_crossattn, c_adm: {"c_crossattn": c_crossattn, "c_adm": c_adm} + make_condition_dict = lambda c_crossattn, c_adm: {"c_crossattn": c_crossattn, "c_adm": c_adm} else: image_uncond = image_cond - make_condition_dict = lambda c_crossattn, c_concat: {"c_crossattn": c_crossattn, "c_concat": [c_concat]} + make_condition_dict = lambda c_crossattn, c_concat: {"c_crossattn": c_crossattn, "c_concat": [c_concat]} if not is_edit_model: x_in = torch.cat([torch.stack([x[i] for _ in range(n)]) for i, n in enumerate(repeats)] + [x]) @@ -316,7 +316,7 @@ class KDiffusionSampler: sigma_sched = sigmas[steps - t_enc - 1:] xi = x + noise * sigma_sched[0] - + extra_params_kwargs = self.initialize(p) parameters = inspect.signature(self.func).parameters @@ -339,9 +339,9 @@ class KDiffusionSampler: self.model_wrap_cfg.init_latent = x self.last_latent = x extra_args={ - 'cond': conditioning, - 'image_cond': image_conditioning, - 'uncond': unconditional_conditioning, + 'cond': conditioning, + 'image_cond': image_conditioning, + 'uncond': unconditional_conditioning, 'cond_scale': p.cfg_scale, 's_min_uncond': self.s_min_uncond } @@ -374,9 +374,9 @@ class KDiffusionSampler: self.last_latent = x samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args={ - 'cond': conditioning, - 'image_cond': image_conditioning, - 'uncond': unconditional_conditioning, + 'cond': conditioning, + 'image_cond': image_conditioning, + 'uncond': unconditional_conditioning, 'cond_scale': p.cfg_scale, 's_min_uncond': self.s_min_uncond }, disable=False, callback=self.callback_state, **extra_params_kwargs)) diff --git a/modules/sub_quadratic_attention.py b/modules/sub_quadratic_attention.py index cc38debd..497568eb 100644 --- a/modules/sub_quadratic_attention.py +++ b/modules/sub_quadratic_attention.py @@ -179,7 +179,7 @@ def efficient_dot_product_attention( chunk_idx, min(query_chunk_size, q_tokens) ) - + summarize_chunk: SummarizeChunk = partial(_summarize_chunk, scale=scale) summarize_chunk: SummarizeChunk = partial(checkpoint, summarize_chunk) if use_checkpoint else summarize_chunk compute_query_chunk_attn: ComputeQueryChunkAttn = partial( diff --git a/modules/textual_inversion/dataset.py b/modules/textual_inversion/dataset.py index 41610e03..b9621fc9 100644 --- a/modules/textual_inversion/dataset.py +++ b/modules/textual_inversion/dataset.py @@ -118,7 +118,7 @@ class PersonalizedBase(Dataset): weight = torch.ones(latent_sample.shape) else: weight = None - + if latent_sampling_method == "random": entry = DatasetEntry(filename=path, filename_text=filename_text, latent_dist=latent_dist, weight=weight) else: @@ -243,4 +243,4 @@ class BatchLoaderRandom(BatchLoader): return self def collate_wrapper_random(batch): - return BatchLoaderRandom(batch) \ No newline at end of file + return BatchLoaderRandom(batch) diff --git a/modules/textual_inversion/preprocess.py b/modules/textual_inversion/preprocess.py index d0cad09e..a009d8e8 100644 --- a/modules/textual_inversion/preprocess.py +++ b/modules/textual_inversion/preprocess.py @@ -125,7 +125,7 @@ def multicrop_pic(image: Image, mindim, maxdim, minarea, maxarea, objective, thr default=None ) return wh and center_crop(image, *wh) - + def preprocess_work(process_src, process_dst, process_width, process_height, preprocess_txt_action, process_keep_original_size, process_flip, process_split, process_caption, process_caption_deepbooru=False, split_threshold=0.5, overlap_ratio=0.2, process_focal_crop=False, process_focal_crop_face_weight=0.9, process_focal_crop_entropy_weight=0.3, process_focal_crop_edges_weight=0.5, process_focal_crop_debug=False, process_multicrop=None, process_multicrop_mindim=None, process_multicrop_maxdim=None, process_multicrop_minarea=None, process_multicrop_maxarea=None, process_multicrop_objective=None, process_multicrop_threshold=None): width = process_width diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index 9e1b2b9a..d489ed1e 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -323,16 +323,16 @@ def tensorboard_add(tensorboard_writer, loss, global_step, step, learn_rate, epo tensorboard_add_scaler(tensorboard_writer, f"Learn rate/train/epoch-{epoch_num}", learn_rate, step) def tensorboard_add_scaler(tensorboard_writer, tag, value, step): - tensorboard_writer.add_scalar(tag=tag, + tensorboard_writer.add_scalar(tag=tag, scalar_value=value, global_step=step) def tensorboard_add_image(tensorboard_writer, tag, pil_image, step): # Convert a pil image to a torch tensor img_tensor = torch.as_tensor(np.array(pil_image, copy=True)) - img_tensor = img_tensor.view(pil_image.size[1], pil_image.size[0], + img_tensor = img_tensor.view(pil_image.size[1], pil_image.size[0], len(pil_image.getbands())) img_tensor = img_tensor.permute((2, 0, 1)) - + tensorboard_writer.add_image(tag, img_tensor, global_step=step) def validate_train_inputs(model_name, learn_rate, batch_size, gradient_step, data_root, template_file, template_filename, steps, save_model_every, create_image_every, log_directory, name="embedding"): @@ -402,7 +402,7 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st if initial_step >= steps: shared.state.textinfo = "Model has already been trained beyond specified max steps" return embedding, filename - + scheduler = LearnRateScheduler(learn_rate, steps, initial_step) clip_grad = torch.nn.utils.clip_grad_value_ if clip_grad_mode == "value" else \ torch.nn.utils.clip_grad_norm_ if clip_grad_mode == "norm" else \ @@ -412,7 +412,7 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st # dataset loading may take a while, so input validations and early returns should be done before this shared.state.textinfo = f"Preparing dataset from {html.escape(data_root)}..." old_parallel_processing_allowed = shared.parallel_processing_allowed - + if shared.opts.training_enable_tensorboard: tensorboard_writer = tensorboard_setup(log_directory) @@ -439,7 +439,7 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st optimizer_saved_dict = torch.load(f"{filename}.optim", map_location='cpu') if embedding.checksum() == optimizer_saved_dict.get('hash', None): optimizer_state_dict = optimizer_saved_dict.get('optimizer_state_dict', None) - + if optimizer_state_dict is not None: optimizer.load_state_dict(optimizer_state_dict) print("Loaded existing optimizer from checkpoint") @@ -485,7 +485,7 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st if clip_grad: clip_grad_sched.step(embedding.step) - + with devices.autocast(): x = batch.latent_sample.to(devices.device, non_blocking=pin_memory) if use_weight: @@ -513,7 +513,7 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st # go back until we reach gradient accumulation steps if (j + 1) % gradient_step != 0: continue - + if clip_grad: clip_grad(embedding.vec, clip_grad_sched.learn_rate) diff --git a/modules/ui.py b/modules/ui.py index 1efb656a..ff82fff6 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -1171,7 +1171,7 @@ def create_ui(): process_focal_crop_entropy_weight = gr.Slider(label='Focal point entropy weight', value=0.15, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_entropy_weight") process_focal_crop_edges_weight = gr.Slider(label='Focal point edges weight', value=0.5, minimum=0.0, maximum=1.0, step=0.05, elem_id="train_process_focal_crop_edges_weight") process_focal_crop_debug = gr.Checkbox(label='Create debug image', elem_id="train_process_focal_crop_debug") - + with gr.Column(visible=False) as process_multicrop_col: gr.Markdown('Each image is center-cropped with an automatically chosen width and height.') with gr.Row(): @@ -1183,7 +1183,7 @@ def create_ui(): with gr.Row(): process_multicrop_objective = gr.Radio(["Maximize area", "Minimize error"], value="Maximize area", label="Resizing objective", elem_id="train_process_multicrop_objective") process_multicrop_threshold = gr.Slider(minimum=0, maximum=1, step=0.01, label="Error threshold", value=0.1, elem_id="train_process_multicrop_threshold") - + with gr.Row(): with gr.Column(scale=3): gr.HTML(value="") @@ -1226,7 +1226,7 @@ def create_ui(): with FormRow(): embedding_learn_rate = gr.Textbox(label='Embedding Learning rate', placeholder="Embedding Learning rate", value="0.005", elem_id="train_embedding_learn_rate") hypernetwork_learn_rate = gr.Textbox(label='Hypernetwork Learning rate', placeholder="Hypernetwork Learning rate", value="0.00001", elem_id="train_hypernetwork_learn_rate") - + with FormRow(): clip_grad_mode = gr.Dropdown(value="disabled", label="Gradient Clipping", choices=["disabled", "value", "norm"]) clip_grad_value = gr.Textbox(placeholder="Gradient clip value", value="0.1", show_label=False) @@ -1565,7 +1565,7 @@ def create_ui(): gr.HTML(shared.html("licenses.html"), elem_id="licenses") gr.Button(value="Show all pages", elem_id="settings_show_all_pages") - + def unload_sd_weights(): modules.sd_models.unload_model_weights() @@ -1841,15 +1841,15 @@ def versions_html(): return f""" version: {tag} - •  + • python: {python_version} - •  + • torch: {getattr(torch, '__long_version__',torch.__version__)} - •  + • xformers: {xformers_version} - •  + • gradio: {gr.__version__} - •  + • checkpoint: N/A """ diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py index ed70abe5..af497733 100644 --- a/modules/ui_extensions.py +++ b/modules/ui_extensions.py @@ -467,7 +467,7 @@ def refresh_available_extensions_from_data(hide_tags, sort_column, filter_text=" {html.escape(description)}

Added: {html.escape(added)}

{install_code} - + """ for tag in [x for x in extension_tags if x not in tags]: @@ -535,9 +535,9 @@ def create_ui(): hide_tags = gr.CheckboxGroup(value=["ads", "localization", "installed"], label="Hide extensions with tags", choices=["script", "ads", "localization", "installed"]) sort_column = gr.Radio(value="newest first", label="Order", choices=["newest first", "oldest first", "a-z", "z-a", "internal order", ], type="index") - with gr.Row(): + with gr.Row(): search_extensions_text = gr.Text(label="Search").style(container=False) - + install_result = gr.HTML() available_extensions_table = gr.HTML() diff --git a/modules/xlmr.py b/modules/xlmr.py index e056c3f6..a407a3ca 100644 --- a/modules/xlmr.py +++ b/modules/xlmr.py @@ -28,7 +28,7 @@ class BertSeriesModelWithTransformation(BertPreTrainedModel): config_class = BertSeriesConfig def __init__(self, config=None, **kargs): - # modify initialization for autoloading + # modify initialization for autoloading if config is None: config = XLMRobertaConfig() config.attention_probs_dropout_prob= 0.1 @@ -74,7 +74,7 @@ class BertSeriesModelWithTransformation(BertPreTrainedModel): text["attention_mask"] = torch.tensor( text['attention_mask']).to(device) features = self(**text) - return features['projection_state'] + return features['projection_state'] def forward( self, @@ -134,4 +134,4 @@ class BertSeriesModelWithTransformation(BertPreTrainedModel): class RobertaSeriesModelWithTransformation(BertSeriesModelWithTransformation): base_model_prefix = 'roberta' - config_class= RobertaSeriesConfig \ No newline at end of file + config_class= RobertaSeriesConfig diff --git a/pyproject.toml b/pyproject.toml index c88907be..d4a1bbf4 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -6,6 +6,7 @@ extend-select = [ "B", "C", "I", + "W", ] exclude = [ @@ -20,7 +21,7 @@ ignore = [ "I001", # Import block is un-sorted or un-formatted "C901", # Function is too complex "C408", # Rewrite as a literal - + "W605", # invalid escape sequence, messes with some docstrings ] [tool.ruff.per-file-ignores] @@ -28,4 +29,4 @@ ignore = [ [tool.ruff.flake8-bugbear] # Allow default arguments like, e.g., `data: List[str] = fastapi.Query(None)`. -extend-immutable-calls = ["fastapi.Depends", "fastapi.security.HTTPBasic"] \ No newline at end of file +extend-immutable-calls = ["fastapi.Depends", "fastapi.security.HTTPBasic"] diff --git a/scripts/img2imgalt.py b/scripts/img2imgalt.py index bb00fb3f..1e833fa8 100644 --- a/scripts/img2imgalt.py +++ b/scripts/img2imgalt.py @@ -149,9 +149,9 @@ class Script(scripts.Script): sigma_adjustment = gr.Checkbox(label="Sigma adjustment for finding noise for image", value=False, elem_id=self.elem_id("sigma_adjustment")) return [ - info, + info, override_sampler, - override_prompt, original_prompt, original_negative_prompt, + override_prompt, original_prompt, original_negative_prompt, override_steps, st, override_strength, cfg, randomness, sigma_adjustment, @@ -191,17 +191,17 @@ class Script(scripts.Script): self.cache = Cached(rec_noise, cfg, st, lat, original_prompt, original_negative_prompt, sigma_adjustment) rand_noise = processing.create_random_tensors(p.init_latent.shape[1:], seeds=seeds, subseeds=subseeds, subseed_strength=p.subseed_strength, seed_resize_from_h=p.seed_resize_from_h, seed_resize_from_w=p.seed_resize_from_w, p=p) - + combined_noise = ((1 - randomness) * rec_noise + randomness * rand_noise) / ((randomness**2 + (1-randomness)**2) ** 0.5) - + sampler = sd_samplers.create_sampler(p.sampler_name, p.sd_model) sigmas = sampler.model_wrap.get_sigmas(p.steps) - + noise_dt = combined_noise - (p.init_latent / sigmas[0]) - + p.seed = p.seed + 1 - + return sampler.sample_img2img(p, p.init_latent, noise_dt, conditioning, unconditional_conditioning, image_conditioning=p.image_conditioning) p.sample = sample_extra diff --git a/scripts/loopback.py b/scripts/loopback.py index ad6609be..2d5feaf9 100644 --- a/scripts/loopback.py +++ b/scripts/loopback.py @@ -14,7 +14,7 @@ class Script(scripts.Script): def show(self, is_img2img): return is_img2img - def ui(self, is_img2img): + def ui(self, is_img2img): loops = gr.Slider(minimum=1, maximum=32, step=1, label='Loops', value=4, elem_id=self.elem_id("loops")) final_denoising_strength = gr.Slider(minimum=0, maximum=1, step=0.01, label='Final denoising strength', value=0.5, elem_id=self.elem_id("final_denoising_strength")) denoising_curve = gr.Dropdown(label="Denoising strength curve", choices=["Aggressive", "Linear", "Lazy"], value="Linear") @@ -104,7 +104,7 @@ class Script(scripts.Script): p.seed = processed.seed + 1 p.denoising_strength = calculate_denoising_strength(i + 1) - + if state.skipped: break @@ -121,7 +121,7 @@ class Script(scripts.Script): all_images.append(last_image) p.inpainting_fill = original_inpainting_fill - + if state.interrupted: break @@ -132,7 +132,7 @@ class Script(scripts.Script): if opts.return_grid: grids.append(grid) - + all_images = grids + all_images processed = Processed(p, all_images, initial_seed, initial_info) diff --git a/scripts/poor_mans_outpainting.py b/scripts/poor_mans_outpainting.py index c0bbecc1..ea0632b6 100644 --- a/scripts/poor_mans_outpainting.py +++ b/scripts/poor_mans_outpainting.py @@ -19,7 +19,7 @@ class Script(scripts.Script): def ui(self, is_img2img): if not is_img2img: return None - + pixels = gr.Slider(label="Pixels to expand", minimum=8, maximum=256, step=8, value=128, elem_id=self.elem_id("pixels")) mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4, elem_id=self.elem_id("mask_blur")) inpainting_fill = gr.Radio(label='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='fill', type="index", elem_id=self.elem_id("inpainting_fill")) diff --git a/scripts/prompt_matrix.py b/scripts/prompt_matrix.py index fb06beab..88324fe6 100644 --- a/scripts/prompt_matrix.py +++ b/scripts/prompt_matrix.py @@ -96,7 +96,7 @@ class Script(scripts.Script): p.prompt_for_display = positive_prompt processed = process_images(p) - grid = images.image_grid(processed.images, p.batch_size, rows=1 << ((len(prompt_matrix_parts) - 1) // 2)) + grid = images.image_grid(processed.images, p.batch_size, rows=1 << ((len(prompt_matrix_parts) - 1) // 2)) grid = images.draw_prompt_matrix(grid, processed.images[0].width, processed.images[0].height, prompt_matrix_parts, margin_size) processed.images.insert(0, grid) processed.index_of_first_image = 1 diff --git a/scripts/prompts_from_file.py b/scripts/prompts_from_file.py index 9607077a..2378816f 100644 --- a/scripts/prompts_from_file.py +++ b/scripts/prompts_from_file.py @@ -109,7 +109,7 @@ class Script(scripts.Script): def title(self): return "Prompts from file or textbox" - def ui(self, is_img2img): + def ui(self, is_img2img): checkbox_iterate = gr.Checkbox(label="Iterate seed every line", value=False, elem_id=self.elem_id("checkbox_iterate")) checkbox_iterate_batch = gr.Checkbox(label="Use same random seed for all lines", value=False, elem_id=self.elem_id("checkbox_iterate_batch")) @@ -166,7 +166,7 @@ class Script(scripts.Script): proc = process_images(copy_p) images += proc.images - + if checkbox_iterate: p.seed = p.seed + (p.batch_size * p.n_iter) all_prompts += proc.all_prompts diff --git a/scripts/sd_upscale.py b/scripts/sd_upscale.py index 0b1d3096..e614c23b 100644 --- a/scripts/sd_upscale.py +++ b/scripts/sd_upscale.py @@ -16,7 +16,7 @@ class Script(scripts.Script): def show(self, is_img2img): return is_img2img - def ui(self, is_img2img): + def ui(self, is_img2img): info = gr.HTML("

Will upscale the image by the selected scale factor; use width and height sliders to set tile size

") overlap = gr.Slider(minimum=0, maximum=256, step=16, label='Tile overlap', value=64, elem_id=self.elem_id("overlap")) scale_factor = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label='Scale Factor', value=2.0, elem_id=self.elem_id("scale_factor")) -- cgit v1.2.3 From a00e42556ffbc1b757fda5ba3f85a9e11c931441 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sun, 14 May 2023 11:04:21 +0300 Subject: add a bunch of descriptions and reword a lot of settings (sorry, localizers) --- extensions-builtin/ScuNET/scripts/scunet_model.py | 13 +++- javascript/ui_settings_hints.js | 3 +- modules/shared.py | 94 ++++++++++++----------- style.css | 4 +- 4 files changed, 65 insertions(+), 49 deletions(-) (limited to 'extensions-builtin/ScuNET') diff --git a/extensions-builtin/ScuNET/scripts/scunet_model.py b/extensions-builtin/ScuNET/scripts/scunet_model.py index 1f5ea0d3..cc2cbc6a 100644 --- a/extensions-builtin/ScuNET/scripts/scunet_model.py +++ b/extensions-builtin/ScuNET/scripts/scunet_model.py @@ -10,7 +10,7 @@ from tqdm import tqdm from basicsr.utils.download_util import load_file_from_url import modules.upscaler -from modules import devices, modelloader +from modules import devices, modelloader, script_callbacks from scunet_model_arch import SCUNet as net from modules.shared import opts @@ -137,3 +137,14 @@ class UpscalerScuNET(modules.upscaler.Upscaler): model = model.to(device) return model + + +def on_ui_settings(): + import gradio as gr + from modules import shared + + shared.opts.add_option("SCUNET_tile", shared.OptionInfo(256, "Tile size for SCUNET upscalers.", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}, section=('upscaling', "Upscaling")).info("0 = no tiling")) + shared.opts.add_option("SCUNET_tile_overlap", shared.OptionInfo(8, "Tile overlap for SCUNET upscalers.", gr.Slider, {"minimum": 0, "maximum": 64, "step": 1}, section=('upscaling', "Upscaling")).info("Low values = visible seam")) + + +script_callbacks.on_ui_settings(on_ui_settings) diff --git a/javascript/ui_settings_hints.js b/javascript/ui_settings_hints.js index 9251fd71..6d1933dc 100644 --- a/javascript/ui_settings_hints.js +++ b/javascript/ui_settings_hints.js @@ -15,7 +15,8 @@ onOptionsChanged(function(){ var span = null if(div.classList.contains('gradio-checkbox')) span = div.querySelector('label span') - else if(div.classList.contains('gradio-checkboxgroup')) span = div.querySelector('span') + else if(div.classList.contains('gradio-checkboxgroup')) span = div.querySelector('span').firstChild + else if(div.classList.contains('gradio-radio')) span = div.querySelector('span').firstChild else span = div.querySelector('label span').firstChild if(!span) return diff --git a/modules/shared.py b/modules/shared.py index 24fdcd59..a0577644 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -228,6 +228,12 @@ class OptionInfo: self.comment_after += f"({info})" return self + def needs_restart(self): + self.comment_after += " (requires restart)" + return self + + + def options_section(section_identifier, options_dict): for v in options_dict.values(): @@ -278,10 +284,10 @@ options_templates.update(options_section(('saving-images', "Saving images/grids" "save_mask_composite": OptionInfo(False, "For inpainting, save a masked composite"), "jpeg_quality": OptionInfo(80, "Quality for saved jpeg images", gr.Slider, {"minimum": 1, "maximum": 100, "step": 1}), "webp_lossless": OptionInfo(False, "Use lossless compression for webp images"), - "export_for_4chan": OptionInfo(True, "If the saved image file size is above the limit, or its either width or height are above the limit, save a downscaled copy as JPG"), + "export_for_4chan": OptionInfo(True, "Save copy of large images as JPG").info("if the file size is above the limit, or either width or height are above the limit"), "img_downscale_threshold": OptionInfo(4.0, "File size limit for the above option, MB", gr.Number), "target_side_length": OptionInfo(4000, "Width/height limit for the above option, in pixels", gr.Number), - "img_max_size_mp": OptionInfo(200, "Maximum image size, in megapixels", gr.Number), + "img_max_size_mp": OptionInfo(200, "Maximum image size", gr.Number).info("in megapixels"), "use_original_name_batch": OptionInfo(True, "Use original name for output filename during batch process in extras tab"), "use_upscaler_name_as_suffix": OptionInfo(False, "Use upscaler name as filename suffix in the extras tab"), @@ -314,23 +320,21 @@ options_templates.update(options_section(('saving-to-dirs', "Saving to a directo })) options_templates.update(options_section(('upscaling', "Upscaling"), { - "ESRGAN_tile": OptionInfo(192, "Tile size for ESRGAN upscalers. 0 = no tiling.", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}), - "ESRGAN_tile_overlap": OptionInfo(8, "Tile overlap, in pixels for ESRGAN upscalers. Low values = visible seam.", gr.Slider, {"minimum": 0, "maximum": 48, "step": 1}), - "realesrgan_enabled_models": OptionInfo(["R-ESRGAN 4x+", "R-ESRGAN 4x+ Anime6B"], "Select which Real-ESRGAN models to show in the web UI. (Requires restart)", gr.CheckboxGroup, lambda: {"choices": shared_items.realesrgan_models_names()}), + "ESRGAN_tile": OptionInfo(192, "Tile size for ESRGAN upscalers.", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}).info("0 = no tiling"), + "ESRGAN_tile_overlap": OptionInfo(8, "Tile overlap for ESRGAN upscalers.", gr.Slider, {"minimum": 0, "maximum": 48, "step": 1}).info("Low values = visible seam"), + "realesrgan_enabled_models": OptionInfo(["R-ESRGAN 4x+", "R-ESRGAN 4x+ Anime6B"], "Select which Real-ESRGAN models to show in the web UI.", gr.CheckboxGroup, lambda: {"choices": shared_items.realesrgan_models_names()}), "upscaler_for_img2img": OptionInfo(None, "Upscaler for img2img", gr.Dropdown, lambda: {"choices": [x.name for x in sd_upscalers]}), - "SCUNET_tile": OptionInfo(256, "Tile size for SCUNET upscalers. 0 = no tiling.", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}), - "SCUNET_tile_overlap": OptionInfo(8, "Tile overlap, in pixels for SCUNET upscalers. Low values = visible seam.", gr.Slider, {"minimum": 0, "maximum": 64, "step": 1}), })) options_templates.update(options_section(('face-restoration', "Face restoration"), { "face_restoration_model": OptionInfo("CodeFormer", "Face restoration model", gr.Radio, lambda: {"choices": [x.name() for x in face_restorers]}), - "code_former_weight": OptionInfo(0.5, "CodeFormer weight parameter; 0 = maximum effect; 1 = minimum effect", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}), + "code_former_weight": OptionInfo(0.5, "CodeFormer weight", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}).info("0 = maximum effect; 1 = minimum effect"), "face_restoration_unload": OptionInfo(False, "Move face restoration model from VRAM into RAM after processing"), })) options_templates.update(options_section(('system', "System"), { "show_warnings": OptionInfo(False, "Show warnings in console."), - "memmon_poll_rate": OptionInfo(8, "VRAM usage polls per second during generation. Set to 0 to disable.", gr.Slider, {"minimum": 0, "maximum": 40, "step": 1}), + "memmon_poll_rate": OptionInfo(8, "VRAM usage polls per second during generation.", gr.Slider, {"minimum": 0, "maximum": 40, "step": 1}).info("0 = disable"), "samples_log_stdout": OptionInfo(False, "Always print all generation info to standard output"), "multiple_tqdm": OptionInfo(True, "Add a second progress bar to the console that shows progress for an entire job."), "print_hypernet_extra": OptionInfo(False, "Print extra hypernetwork information to console."), @@ -355,20 +359,20 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": list_checkpoint_tiles()}, refresh=refresh_checkpoints), "sd_checkpoint_cache": OptionInfo(0, "Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}), "sd_vae_checkpoint_cache": OptionInfo(0, "VAE Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}), - "sd_vae": OptionInfo("Automatic", "SD VAE", gr.Dropdown, lambda: {"choices": shared_items.sd_vae_items()}, refresh=shared_items.refresh_vae_list), + "sd_vae": OptionInfo("Automatic", "SD VAE", gr.Dropdown, lambda: {"choices": shared_items.sd_vae_items()}, refresh=shared_items.refresh_vae_list).info("choose VAE model: Automatic = use one with same filename as checkpoint; None = use VAE from checkpoint"), "sd_vae_as_default": OptionInfo(True, "Ignore selected VAE for stable diffusion checkpoints that have their own .vae.pt next to them"), "inpainting_mask_weight": OptionInfo(1.0, "Inpainting conditioning mask strength", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), "initial_noise_multiplier": OptionInfo(1.0, "Noise multiplier for img2img", gr.Slider, {"minimum": 0.5, "maximum": 1.5, "step": 0.01}), "img2img_color_correction": OptionInfo(False, "Apply color correction to img2img results to match original colors."), - "img2img_fix_steps": OptionInfo(False, "With img2img, do exactly the amount of steps the slider specifies (normally you'd do less with less denoising)."), + "img2img_fix_steps": OptionInfo(False, "With img2img, do exactly the amount of steps the slider specifies.").info("normally you'd do less with less denoising"), "img2img_background_color": OptionInfo("#ffffff", "With img2img, fill image's transparent parts with this color.", ui_components.FormColorPicker, {}), "enable_quantization": OptionInfo(False, "Enable quantization in K samplers for sharper and cleaner results. This may change existing seeds. Requires restart to apply."), - "enable_emphasis": OptionInfo(True, "Emphasis: use (text) to make model pay more attention to text and [text] to make it pay less attention"), + "enable_emphasis": OptionInfo(True, "Enable emphasis").info("use (text) to make model pay more attention to text and [text] to make it pay less attention"), "enable_batch_seeds": OptionInfo(True, "Make K-diffusion samplers produce same images in a batch as when making a single image"), - "comma_padding_backtrack": OptionInfo(20, "Increase coherency by padding from the last comma within n tokens when using more than 75 tokens", gr.Slider, {"minimum": 0, "maximum": 74, "step": 1 }), - "CLIP_stop_at_last_layers": OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}), + "comma_padding_backtrack": OptionInfo(20, "Prompt word wrap length limit", gr.Slider, {"minimum": 0, "maximum": 74, "step": 1}).info("in tokens - for texts shorter than specified, if they don't fit into 75 token limit, move them to the next 75 token chunk"), + "CLIP_stop_at_last_layers": OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}).link("wiki", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#clip-skip").info("ignore last layers of CLIP nrtwork; 1 ignores none, 2 ignores one layer"), "upcast_attn": OptionInfo(False, "Upcast cross attention layer to float32"), - "randn_source": OptionInfo("GPU", "Random number generator source. Changes seeds drastically. Use CPU to produce the same picture across different vidocard vendors.", gr.Radio, {"choices": ["GPU", "CPU"]}), + "randn_source": OptionInfo("GPU", "Random number generator source.", gr.Radio, {"choices": ["GPU", "CPU"]}).info("changes seeds drastically; use CPU to produce the same picture across different vidocard vendors"), "token_merging_ratio": OptionInfo(0.0, "Token merging ratio", gr.Slider, {"minimum": 0.0, "maximum": 0.9, "step": 0.1}).link("PR", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/9256").info("0=disable, higher=faster"), "token_merging_ratio_hr": OptionInfo(0.0, "Togen merging ratio for high-res pass", gr.Slider, {"minimum": 0.0, "maximum": 0.9, "step": 0.1}), })) @@ -382,30 +386,32 @@ options_templates.update(options_section(('compatibility', "Compatibility"), { })) options_templates.update(options_section(('interrogate', "Interrogate Options"), { - "interrogate_keep_models_in_memory": OptionInfo(False, "Interrogate: keep models in VRAM"), - "interrogate_return_ranks": OptionInfo(False, "Interrogate: include ranks of model tags matches in results (Has no effect on caption-based interrogators)."), - "interrogate_clip_num_beams": OptionInfo(1, "Interrogate: num_beams for BLIP", gr.Slider, {"minimum": 1, "maximum": 16, "step": 1}), - "interrogate_clip_min_length": OptionInfo(24, "Interrogate: minimum description length (excluding artists, etc..)", gr.Slider, {"minimum": 1, "maximum": 128, "step": 1}), - "interrogate_clip_max_length": OptionInfo(48, "Interrogate: maximum description length", gr.Slider, {"minimum": 1, "maximum": 256, "step": 1}), - "interrogate_clip_dict_limit": OptionInfo(1500, "CLIP: maximum number of lines in text file (0 = No limit)"), + "interrogate_keep_models_in_memory": OptionInfo(False, "Keep models in VRAM"), + "interrogate_return_ranks": OptionInfo(False, "Include ranks of model tags matches in results.").info("booru only"), + "interrogate_clip_num_beams": OptionInfo(1, "BLIP: num_beams", gr.Slider, {"minimum": 1, "maximum": 16, "step": 1}), + "interrogate_clip_min_length": OptionInfo(24, "BLIP: minimum description length", gr.Slider, {"minimum": 1, "maximum": 128, "step": 1}), + "interrogate_clip_max_length": OptionInfo(48, "BLIP: maximum description length", gr.Slider, {"minimum": 1, "maximum": 256, "step": 1}), + "interrogate_clip_dict_limit": OptionInfo(1500, "CLIP: maximum number of lines in text file").info("0 = No limit"), "interrogate_clip_skip_categories": OptionInfo([], "CLIP: skip inquire categories", gr.CheckboxGroup, lambda: {"choices": modules.interrogate.category_types()}, refresh=modules.interrogate.category_types), - "interrogate_deepbooru_score_threshold": OptionInfo(0.5, "Interrogate: deepbooru score threshold", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}), - "deepbooru_sort_alpha": OptionInfo(True, "Interrogate: deepbooru sort alphabetically"), - "deepbooru_use_spaces": OptionInfo(False, "use spaces for tags in deepbooru"), - "deepbooru_escape": OptionInfo(True, "escape (\\) brackets in deepbooru (so they are used as literal brackets and not for emphasis)"), - "deepbooru_filter_tags": OptionInfo("", "filter out those tags from deepbooru output (separated by comma)"), + "interrogate_deepbooru_score_threshold": OptionInfo(0.5, "deepbooru: score threshold", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}), + "deepbooru_sort_alpha": OptionInfo(True, "deepbooru: sort tags alphabetically").info("if not: sort by score"), + "deepbooru_use_spaces": OptionInfo(True, "deepbooru: use spaces in tags").info("if not: use underscores"), + "deepbooru_escape": OptionInfo(True, "deepbooru: escape (\\) brackets").info("so they are used as literal brackets and not for emphasis"), + "deepbooru_filter_tags": OptionInfo("", "deepbooru: filter out those tags").info("separate by comma"), })) options_templates.update(options_section(('extra_networks', "Extra Networks"), { "extra_networks_default_view": OptionInfo("cards", "Default view for Extra Networks", gr.Dropdown, {"choices": ["cards", "thumbs"]}), "extra_networks_default_multiplier": OptionInfo(1.0, "Multiplier for extra networks", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), - "extra_networks_card_width": OptionInfo(0, "Card width for Extra Networks (px)"), - "extra_networks_card_height": OptionInfo(0, "Card height for Extra Networks (px)"), - "extra_networks_add_text_separator": OptionInfo(" ", "Extra text to add before <...> when adding extra network to prompt"), + "extra_networks_card_width": OptionInfo(0, "Card width for Extra Networks").info("in pixels"), + "extra_networks_card_height": OptionInfo(0, "Card height for Extra Networks").info("in pixels"), + "extra_networks_add_text_separator": OptionInfo(" ", "Extra networks separator").info("extra text to add before <...> when adding extra network to prompt"), "sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": ["None", *hypernetworks]}, refresh=reload_hypernetworks), })) options_templates.update(options_section(('ui', "User interface"), { + "localization": OptionInfo("None", "Localization", gr.Dropdown, lambda: {"choices": ["None"] + list(localization.localizations.keys())}, refresh=lambda: localization.list_localizations(cmd_opts.localizations_dir)).needs_restart(), + "gradio_theme": OptionInfo("Default", "Gradio theme", ui_components.DropdownEditable, lambda: {"choices": ["Default"] + gradio_hf_hub_themes}).needs_restart(), "return_grid": OptionInfo(True, "Show grid in results for web"), "return_mask": OptionInfo(False, "For inpainting, include the greyscale mask in results for web"), "return_mask_composite": OptionInfo(False, "For inpainting, include masked composite in results for web"), @@ -418,17 +424,15 @@ options_templates.update(options_section(('ui', "User interface"), { "js_modal_lightbox_gamepad": OptionInfo(True, "Navigate image viewer with gamepad"), "js_modal_lightbox_gamepad_repeat": OptionInfo(250, "Gamepad repeat period, in milliseconds"), "show_progress_in_title": OptionInfo(True, "Show generation progress in window title."), - "samplers_in_dropdown": OptionInfo(True, "Use dropdown for sampler selection instead of radio group"), - "dimensions_and_batch_together": OptionInfo(True, "Show Width/Height and Batch sliders in same row"), + "samplers_in_dropdown": OptionInfo(True, "Use dropdown for sampler selection instead of radio group").needs_restart(), + "dimensions_and_batch_together": OptionInfo(True, "Show Width/Height and Batch sliders in same row").needs_restart(), "keyedit_precision_attention": OptionInfo(0.1, "Ctrl+up/down precision when editing (attention:1.1)", gr.Slider, {"minimum": 0.01, "maximum": 0.2, "step": 0.001}), "keyedit_precision_extra": OptionInfo(0.05, "Ctrl+up/down precision when editing ", gr.Slider, {"minimum": 0.01, "maximum": 0.2, "step": 0.001}), "keyedit_delimiters": OptionInfo(".,\\/!?%^*;:{}=`~()", "Ctrl+up/down word delimiters"), - "quicksettings_list": OptionInfo(["sd_model_checkpoint"], "Quicksettings list", ui_components.DropdownMulti, lambda: {"choices": list(opts.data_labels.keys())}).js("info", "settingsHintsShowQuicksettings"), - "hidden_tabs": OptionInfo([], "Hidden UI tabs (requires restart)", ui_components.DropdownMulti, lambda: {"choices": list(tab_names)}), + "quicksettings_list": OptionInfo(["sd_model_checkpoint"], "Quicksettings list", ui_components.DropdownMulti, lambda: {"choices": list(opts.data_labels.keys())}).js("info", "settingsHintsShowQuicksettings").info("setting entries that appear at the top of page rather than in settings tab").needs_restart(), + "hidden_tabs": OptionInfo([], "Hidden UI tabs", ui_components.DropdownMulti, lambda: {"choices": list(tab_names)}).needs_restart(), "ui_reorder": OptionInfo(", ".join(ui_reorder_categories), "txt2img/img2img UI item order"), - "ui_extra_networks_tab_reorder": OptionInfo("", "Extra networks tab order"), - "localization": OptionInfo("None", "Localization (requires restart)", gr.Dropdown, lambda: {"choices": ["None"] + list(localization.localizations.keys())}, refresh=lambda: localization.list_localizations(cmd_opts.localizations_dir)), - "gradio_theme": OptionInfo("Default", "Gradio theme (requires restart)", ui_components.DropdownEditable, lambda: {"choices": ["Default"] + gradio_hf_hub_themes}) + "ui_extra_networks_tab_reorder": OptionInfo("", "Extra networks tab order").needs_restart(), })) options_templates.update(options_section(('infotext', "Infotext"), { @@ -443,26 +447,26 @@ options_templates.update(options_section(('ui', "Live previews"), { "live_previews_enable": OptionInfo(True, "Show live previews of the created image"), "live_previews_format": OptionInfo("auto", "Live preview file format", gr.Radio, {"choices": ["auto", "jpeg", "png", "webp"]}), "show_progress_grid": OptionInfo(True, "Show previews of all images generated in a batch as a grid"), - "show_progress_every_n_steps": OptionInfo(10, "Show new live preview image every N sampling steps. Set to -1 to show after completion of batch.", gr.Slider, {"minimum": -1, "maximum": 32, "step": 1}), - "show_progress_type": OptionInfo("Approx NN", "Image creation progress preview mode", gr.Radio, {"choices": ["Full", "Approx NN", "Approx cheap"]}), + "show_progress_every_n_steps": OptionInfo(10, "Live preview display period", gr.Slider, {"minimum": -1, "maximum": 32, "step": 1}).info("in sampling steps - show new live preview image every N sampling steps; -1 = only show after completion of batch"), + "show_progress_type": OptionInfo("Approx NN", "Live preview method", gr.Radio, {"choices": ["Full", "Approx NN", "Approx cheap"]}).info("Full = slow but pretty; Approx NN = fast but low quality; Approx cheap = super fast but terrible otherwise"), "live_preview_content": OptionInfo("Prompt", "Live preview subject", gr.Radio, {"choices": ["Combined", "Prompt", "Negative prompt"]}), - "live_preview_refresh_period": OptionInfo(1000, "Progressbar/preview update period, in milliseconds") + "live_preview_refresh_period": OptionInfo(1000, "Progressbar and preview update period").info("in milliseconds"), })) options_templates.update(options_section(('sampler-params', "Sampler parameters"), { - "hide_samplers": OptionInfo([], "Hide samplers in user interface (requires restart)", gr.CheckboxGroup, lambda: {"choices": [x.name for x in list_samplers()]}), - "eta_ddim": OptionInfo(0.0, "eta (noise multiplier) for DDIM", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), - "eta_ancestral": OptionInfo(1.0, "eta (noise multiplier) for ancestral samplers", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), + "hide_samplers": OptionInfo([], "Hide samplers in user interface", gr.CheckboxGroup, lambda: {"choices": [x.name for x in list_samplers()]}).needs_restart(), + "eta_ddim": OptionInfo(0.0, "Eta for DDIM", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}).info("noise multiplier; higher = more unperdictable results"), + "eta_ancestral": OptionInfo(1.0, "Eta for ancestral samplers", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}).info("noise multiplier; applies to Euler a and other samplers that have a in them"), "ddim_discretize": OptionInfo('uniform', "img2img DDIM discretize", gr.Radio, {"choices": ['uniform', 'quad']}), 's_churn': OptionInfo(0.0, "sigma churn", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), 's_min_uncond': OptionInfo(0, "Negative Guidance minimum sigma", gr.Slider, {"minimum": 0.0, "maximum": 4.0, "step": 0.01}), 's_tmin': OptionInfo(0.0, "sigma tmin", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), 's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), - 'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}), - 'always_discard_next_to_last_sigma': OptionInfo(False, "Always discard next-to-last sigma"), + 'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}).info("ENSD; does not improve anything, just produces different results for ancestral samplers - only useful for reproducing images"), + 'always_discard_next_to_last_sigma': OptionInfo(False, "Always discard next-to-last sigma").link("PR", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/6044"), 'uni_pc_variant': OptionInfo("bh1", "UniPC variant", gr.Radio, {"choices": ["bh1", "bh2", "vary_coeff"]}), 'uni_pc_skip_type': OptionInfo("time_uniform", "UniPC skip type", gr.Radio, {"choices": ["time_uniform", "time_quadratic", "logSNR"]}), - 'uni_pc_order': OptionInfo(3, "UniPC order (must be < sampling steps)", gr.Slider, {"minimum": 1, "maximum": 50, "step": 1}), + 'uni_pc_order': OptionInfo(3, "UniPC order", gr.Slider, {"minimum": 1, "maximum": 50, "step": 1}).info("must be < sampling steps"), 'uni_pc_lower_order_final': OptionInfo(True, "UniPC lower order final"), })) diff --git a/style.css b/style.css index 1e978592..0c2f453c 100644 --- a/style.css +++ b/style.css @@ -425,11 +425,11 @@ table.settings-value-table td{ color: var(--body-text-color); } -#settings .gradio-textbox, #settings .gradio-slider, #settings .gradio-number, #settings .gradio-dropdown, #settings .gradio-checkboxgroup{ +#settings .gradio-textbox, #settings .gradio-slider, #settings .gradio-number, #settings .gradio-dropdown, #settings .gradio-checkboxgroup, #settings .gradio-radio{ margin-top: 0.75em; } -.gradio-textbox .settings-comment, .gradio-slider .settings-comment, .gradio-number .settings-comment, .gradio-dropdown .settings-comment, .gradio-checkboxgroup .settings-comment { +#settings span .settings-comment { display: inline } -- cgit v1.2.3 From df6fffb054f8d3444baa887151a4874506a68be1 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Fri, 19 May 2023 09:09:00 +0300 Subject: change upscalers to download models into user-specified directory (from commandline args) rather than the default models/<...> --- extensions-builtin/LDSR/scripts/ldsr_model.py | 4 ++-- extensions-builtin/ScuNET/scripts/scunet_model.py | 3 +-- extensions-builtin/SwinIR/scripts/swinir_model.py | 2 +- modules/esrgan_model.py | 2 +- modules/modelloader.py | 7 +++++-- modules/realesrgan_model.py | 2 +- modules/upscaler.py | 1 + 7 files changed, 12 insertions(+), 9 deletions(-) (limited to 'extensions-builtin/ScuNET') diff --git a/extensions-builtin/LDSR/scripts/ldsr_model.py b/extensions-builtin/LDSR/scripts/ldsr_model.py index fbbe9005..c4da79f3 100644 --- a/extensions-builtin/LDSR/scripts/ldsr_model.py +++ b/extensions-builtin/LDSR/scripts/ldsr_model.py @@ -45,9 +45,9 @@ class UpscalerLDSR(Upscaler): if local_safetensors_path is not None and os.path.exists(local_safetensors_path): model = local_safetensors_path else: - model = local_ckpt_path if local_ckpt_path is not None else load_file_from_url(url=self.model_url, model_dir=self.model_path, file_name="model.ckpt", progress=True) + model = local_ckpt_path if local_ckpt_path is not None else load_file_from_url(url=self.model_url, model_dir=self.model_download_path, file_name="model.ckpt", progress=True) - yaml = local_yaml_path if local_yaml_path is not None else load_file_from_url(url=self.yaml_url, model_dir=self.model_path, file_name="project.yaml", progress=True) + yaml = local_yaml_path if local_yaml_path is not None else load_file_from_url(url=self.yaml_url, model_dir=self.model_download_path, file_name="project.yaml", progress=True) try: return LDSR(model, yaml) diff --git a/extensions-builtin/ScuNET/scripts/scunet_model.py b/extensions-builtin/ScuNET/scripts/scunet_model.py index cc2cbc6a..45d9297b 100644 --- a/extensions-builtin/ScuNET/scripts/scunet_model.py +++ b/extensions-builtin/ScuNET/scripts/scunet_model.py @@ -121,8 +121,7 @@ class UpscalerScuNET(modules.upscaler.Upscaler): def load_model(self, path: str): device = devices.get_device_for('scunet') if "http" in path: - filename = load_file_from_url(url=self.model_url, model_dir=self.model_path, file_name="%s.pth" % self.name, - progress=True) + filename = load_file_from_url(url=self.model_url, model_dir=self.model_download_path, file_name="%s.pth" % self.name, progress=True) else: filename = path if not os.path.exists(os.path.join(self.model_path, filename)) or filename is None: diff --git a/extensions-builtin/SwinIR/scripts/swinir_model.py b/extensions-builtin/SwinIR/scripts/swinir_model.py index 0ba50487..1c7bf325 100644 --- a/extensions-builtin/SwinIR/scripts/swinir_model.py +++ b/extensions-builtin/SwinIR/scripts/swinir_model.py @@ -51,7 +51,7 @@ class UpscalerSwinIR(Upscaler): def load_model(self, path, scale=4): if "http" in path: dl_name = "%s%s" % (self.model_name.replace(" ", "_"), ".pth") - filename = load_file_from_url(url=path, model_dir=self.model_path, file_name=dl_name, progress=True) + filename = load_file_from_url(url=path, model_dir=self.model_download_path, file_name=dl_name, progress=True) else: filename = path if filename is None or not os.path.exists(filename): diff --git a/modules/esrgan_model.py b/modules/esrgan_model.py index a009eb42..2fced999 100644 --- a/modules/esrgan_model.py +++ b/modules/esrgan_model.py @@ -154,7 +154,7 @@ class UpscalerESRGAN(Upscaler): if "http" in path: filename = load_file_from_url( url=self.model_url, - model_dir=self.model_path, + model_dir=self.model_download_path, file_name=f"{self.model_name}.pth", progress=True, ) diff --git a/modules/modelloader.py b/modules/modelloader.py index 2a479bcb..be23071a 100644 --- a/modules/modelloader.py +++ b/modules/modelloader.py @@ -47,7 +47,7 @@ def load_models(model_path: str, model_url: str = None, command_path: str = None if model_url is not None and len(output) == 0: if download_name is not None: from basicsr.utils.download_util import load_file_from_url - dl = load_file_from_url(model_url, model_path, True, download_name) + dl = load_file_from_url(model_url, places[0], True, download_name) output.append(dl) else: output.append(model_url) @@ -144,7 +144,10 @@ def load_upscalers(): for cls in reversed(used_classes.values()): name = cls.__name__ cmd_name = f"{name.lower().replace('upscaler', '')}_models_path" - scaler = cls(commandline_options.get(cmd_name, None)) + commandline_model_path = commandline_options.get(cmd_name, None) + scaler = cls(commandline_model_path) + scaler.user_path = commandline_model_path + scaler.model_download_path = commandline_model_path or scaler.model_path datas += scaler.scalers shared.sd_upscalers = sorted( diff --git a/modules/realesrgan_model.py b/modules/realesrgan_model.py index c24d8dbb..99983678 100644 --- a/modules/realesrgan_model.py +++ b/modules/realesrgan_model.py @@ -73,7 +73,7 @@ class UpscalerRealESRGAN(Upscaler): return None if info.local_data_path.startswith("http"): - info.local_data_path = load_file_from_url(url=info.data_path, model_dir=self.model_path, progress=True) + info.local_data_path = load_file_from_url(url=info.data_path, model_dir=self.model_download_path, progress=True) return info except Exception as e: diff --git a/modules/upscaler.py b/modules/upscaler.py index 8acb6e96..7b1046d6 100644 --- a/modules/upscaler.py +++ b/modules/upscaler.py @@ -34,6 +34,7 @@ class Upscaler: self.half = not modules.shared.cmd_opts.no_half self.pre_pad = 0 self.mod_scale = None + self.model_download_path = None if self.model_path is None and self.name: self.model_path = os.path.join(shared.models_path, self.name) -- cgit v1.2.3 From 00dfe27f59727407c5b408a80ff2a262934df495 Mon Sep 17 00:00:00 2001 From: Aarni Koskela Date: Mon, 29 May 2023 08:54:13 +0300 Subject: Add & use modules.errors.print_error where currently printing exception info by hand --- extensions-builtin/LDSR/scripts/ldsr_model.py | 7 ++--- extensions-builtin/ScuNET/scripts/scunet_model.py | 6 ++-- modules/api/api.py | 7 +++-- modules/call_queue.py | 22 ++++++-------- modules/codeformer_model.py | 10 +++---- modules/config_states.py | 12 +++----- modules/errors.py | 16 +++++++++++ modules/extensions.py | 10 +++---- modules/gfpgan_model.py | 6 ++-- modules/hypernetworks/hypernetwork.py | 14 ++++----- modules/images.py | 9 ++---- modules/interrogate.py | 5 ++-- modules/launch_utils.py | 7 +++-- modules/localization.py | 6 ++-- modules/processing.py | 2 +- modules/realesrgan_model.py | 14 ++++----- modules/safe.py | 26 +++++++++-------- modules/script_callbacks.py | 9 +++--- modules/script_loading.py | 7 ++--- modules/scripts.py | 35 ++++++++--------------- modules/sd_hijack_optimizations.py | 6 ++-- modules/textual_inversion/textual_inversion.py | 9 ++---- modules/ui.py | 10 +++---- modules/ui_extensions.py | 9 ++---- scripts/prompts_from_file.py | 6 ++-- 25 files changed, 117 insertions(+), 153 deletions(-) (limited to 'extensions-builtin/ScuNET') diff --git a/extensions-builtin/LDSR/scripts/ldsr_model.py b/extensions-builtin/LDSR/scripts/ldsr_model.py index c4da79f3..95f1669d 100644 --- a/extensions-builtin/LDSR/scripts/ldsr_model.py +++ b/extensions-builtin/LDSR/scripts/ldsr_model.py @@ -1,9 +1,8 @@ import os -import sys -import traceback from basicsr.utils.download_util import load_file_from_url +from modules.errors import print_error from modules.upscaler import Upscaler, UpscalerData from ldsr_model_arch import LDSR from modules import shared, script_callbacks @@ -51,10 +50,8 @@ class UpscalerLDSR(Upscaler): try: return LDSR(model, yaml) - except Exception: - print("Error importing LDSR:", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + print_error("Error importing LDSR", exc_info=True) return None def do_upscale(self, img, path): diff --git a/extensions-builtin/ScuNET/scripts/scunet_model.py b/extensions-builtin/ScuNET/scripts/scunet_model.py index 45d9297b..dd1b822e 100644 --- a/extensions-builtin/ScuNET/scripts/scunet_model.py +++ b/extensions-builtin/ScuNET/scripts/scunet_model.py @@ -1,6 +1,5 @@ import os.path import sys -import traceback import PIL.Image import numpy as np @@ -12,6 +11,8 @@ from basicsr.utils.download_util import load_file_from_url import modules.upscaler from modules import devices, modelloader, script_callbacks from scunet_model_arch import SCUNet as net + +from modules.errors import print_error from modules.shared import opts @@ -38,8 +39,7 @@ class UpscalerScuNET(modules.upscaler.Upscaler): scaler_data = modules.upscaler.UpscalerData(name, file, self, 4) scalers.append(scaler_data) except Exception: - print(f"Error loading ScuNET model: {file}", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + print_error(f"Error loading ScuNET model: {file}", exc_info=True) if add_model2: scaler_data2 = modules.upscaler.UpscalerData(self.model_name2, self.model_url2, self) scalers.append(scaler_data2) diff --git a/modules/api/api.py b/modules/api/api.py index 6a456861..79ce9228 100644 --- a/modules/api/api.py +++ b/modules/api/api.py @@ -16,6 +16,7 @@ from secrets import compare_digest import modules.shared as shared from modules import sd_samplers, deepbooru, sd_hijack, images, scripts, ui, postprocessing from modules.api import models +from modules.errors import print_error from modules.shared import opts from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img, process_images from modules.textual_inversion.textual_inversion import create_embedding, train_embedding @@ -108,7 +109,6 @@ def api_middleware(app: FastAPI): from rich.console import Console console = Console() except Exception: - import traceback rich_available = False @app.middleware("http") @@ -139,11 +139,12 @@ def api_middleware(app: FastAPI): "errors": str(e), } if not isinstance(e, HTTPException): # do not print backtrace on known httpexceptions - print(f"API error: {request.method}: {request.url} {err}") + message = f"API error: {request.method}: {request.url} {err}" if rich_available: + print(message) console.print_exception(show_locals=True, max_frames=2, extra_lines=1, suppress=[anyio, starlette], word_wrap=False, width=min([console.width, 200])) else: - traceback.print_exc() + print_error(message, exc_info=True) return JSONResponse(status_code=vars(e).get('status_code', 500), content=jsonable_encoder(err)) @app.middleware("http") diff --git a/modules/call_queue.py b/modules/call_queue.py index 447bb764..dba2a9b4 100644 --- a/modules/call_queue.py +++ b/modules/call_queue.py @@ -1,10 +1,9 @@ import html -import sys import threading -import traceback import time from modules import shared, progress +from modules.errors import print_error queue_lock = threading.Lock() @@ -56,16 +55,14 @@ def wrap_gradio_call(func, extra_outputs=None, add_stats=False): try: res = list(func(*args, **kwargs)) except Exception as e: - # When printing out our debug argument list, do not print out more than a MB of text - max_debug_str_len = 131072 # (1024*1024)/8 - - print("Error completing request", file=sys.stderr) - argStr = f"Arguments: {args} {kwargs}" - print(argStr[:max_debug_str_len], file=sys.stderr) - if len(argStr) > max_debug_str_len: - print(f"(Argument list truncated at {max_debug_str_len}/{len(argStr)} characters)", file=sys.stderr) - - print(traceback.format_exc(), file=sys.stderr) + # When printing out our debug argument list, + # do not print out more than a 100 KB of text + max_debug_str_len = 131072 + message = "Error completing request" + arg_str = f"Arguments: {args} {kwargs}"[:max_debug_str_len] + if len(arg_str) > max_debug_str_len: + arg_str += f" (Argument list truncated at {max_debug_str_len}/{len(arg_str)} characters)" + print_error(f"{message}\n{arg_str}", exc_info=True) shared.state.job = "" shared.state.job_count = 0 @@ -108,4 +105,3 @@ def wrap_gradio_call(func, extra_outputs=None, add_stats=False): return tuple(res) return f - diff --git a/modules/codeformer_model.py b/modules/codeformer_model.py index ececdbae..76143e9f 100644 --- a/modules/codeformer_model.py +++ b/modules/codeformer_model.py @@ -1,6 +1,4 @@ import os -import sys -import traceback import cv2 import torch @@ -8,6 +6,7 @@ import torch import modules.face_restoration import modules.shared from modules import shared, devices, modelloader +from modules.errors import print_error from modules.paths import models_path # codeformer people made a choice to include modified basicsr library to their project which makes @@ -105,8 +104,8 @@ def setup_model(dirname): restored_face = tensor2img(output, rgb2bgr=True, min_max=(-1, 1)) del output torch.cuda.empty_cache() - except Exception as error: - print(f'\tFailed inference for CodeFormer: {error}', file=sys.stderr) + except Exception: + print_error('Failed inference for CodeFormer', exc_info=True) restored_face = tensor2img(cropped_face_t, rgb2bgr=True, min_max=(-1, 1)) restored_face = restored_face.astype('uint8') @@ -135,7 +134,6 @@ def setup_model(dirname): shared.face_restorers.append(codeformer) except Exception: - print("Error setting up CodeFormer:", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + print_error("Error setting up CodeFormer", exc_info=True) # sys.path = stored_sys_path diff --git a/modules/config_states.py b/modules/config_states.py index db65bcdb..faeaf28b 100644 --- a/modules/config_states.py +++ b/modules/config_states.py @@ -3,8 +3,6 @@ Supports saving and restoring webui and extensions from a known working set of c """ import os -import sys -import traceback import json import time import tqdm @@ -14,6 +12,7 @@ from collections import OrderedDict import git from modules import shared, extensions +from modules.errors import print_error from modules.paths_internal import script_path, config_states_dir @@ -53,8 +52,7 @@ def get_webui_config(): if os.path.exists(os.path.join(script_path, ".git")): webui_repo = git.Repo(script_path) except Exception: - print(f"Error reading webui git info from {script_path}:", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + print_error(f"Error reading webui git info from {script_path}", exc_info=True) webui_remote = None webui_commit_hash = None @@ -134,8 +132,7 @@ def restore_webui_config(config): if os.path.exists(os.path.join(script_path, ".git")): webui_repo = git.Repo(script_path) except Exception: - print(f"Error reading webui git info from {script_path}:", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + print_error(f"Error reading webui git info from {script_path}", exc_info=True) return try: @@ -143,8 +140,7 @@ def restore_webui_config(config): webui_repo.git.reset(webui_commit_hash, hard=True) print(f"* Restored webui to commit {webui_commit_hash}.") except Exception: - print(f"Error restoring webui to commit {webui_commit_hash}:", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + print_error(f"Error restoring webui to commit{webui_commit_hash}") def restore_extension_config(config): diff --git a/modules/errors.py b/modules/errors.py index da4694f8..41d8dc93 100644 --- a/modules/errors.py +++ b/modules/errors.py @@ -1,7 +1,23 @@ import sys +import textwrap import traceback +def print_error( + message: str, + *, + exc_info: bool = False, +) -> None: + """ + Print an error message to stderr, with optional traceback. + """ + for line in message.splitlines(): + print("***", line, file=sys.stderr) + if exc_info: + print(textwrap.indent(traceback.format_exc(), " "), file=sys.stderr) + print("---") + + def print_error_explanation(message): lines = message.strip().split("\n") max_len = max([len(x) for x in lines]) diff --git a/modules/extensions.py b/modules/extensions.py index 624832a0..369d2584 100644 --- a/modules/extensions.py +++ b/modules/extensions.py @@ -1,11 +1,10 @@ import os -import sys import threading -import traceback import git from modules import shared +from modules.errors import print_error from modules.paths_internal import extensions_dir, extensions_builtin_dir, script_path # noqa: F401 extensions = [] @@ -56,8 +55,7 @@ class Extension: if os.path.exists(os.path.join(self.path, ".git")): repo = git.Repo(self.path) except Exception: - print(f"Error reading github repository info from {self.path}:", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + print_error(f"Error reading github repository info from {self.path}", exc_info=True) if repo is None or repo.bare: self.remote = None @@ -72,8 +70,8 @@ class Extension: self.commit_hash = commit.hexsha self.version = self.commit_hash[:8] - except Exception as ex: - print(f"Failed reading extension data from Git repository ({self.name}): {ex}", file=sys.stderr) + except Exception: + print_error(f"Failed reading extension data from Git repository ({self.name})", exc_info=True) self.remote = None self.have_info_from_repo = True diff --git a/modules/gfpgan_model.py b/modules/gfpgan_model.py index 0131dea4..d2f647fe 100644 --- a/modules/gfpgan_model.py +++ b/modules/gfpgan_model.py @@ -1,12 +1,11 @@ import os -import sys -import traceback import facexlib import gfpgan import modules.face_restoration from modules import paths, shared, devices, modelloader +from modules.errors import print_error model_dir = "GFPGAN" user_path = None @@ -112,5 +111,4 @@ def setup_model(dirname): shared.face_restorers.append(FaceRestorerGFPGAN()) except Exception: - print("Error setting up GFPGAN:", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + print_error("Error setting up GFPGAN", exc_info=True) diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index 570b5603..fcc1ef20 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -2,8 +2,6 @@ import datetime import glob import html import os -import sys -import traceback import inspect import modules.textual_inversion.dataset @@ -12,6 +10,7 @@ import tqdm from einops import rearrange, repeat from ldm.util import default from modules import devices, processing, sd_models, shared, sd_samplers, hashes, sd_hijack_checkpoint +from modules.errors import print_error from modules.textual_inversion import textual_inversion, logging from modules.textual_inversion.learn_schedule import LearnRateScheduler from torch import einsum @@ -325,17 +324,14 @@ def load_hypernetwork(name): if path is None: return None - hypernetwork = Hypernetwork() - try: + hypernetwork = Hypernetwork() hypernetwork.load(path) + return hypernetwork except Exception: - print(f"Error loading hypernetwork {path}", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + print_error(f"Error loading hypernetwork {path}", exc_info=True) return None - return hypernetwork - def load_hypernetworks(names, multipliers=None): already_loaded = {} @@ -770,7 +766,7 @@ Last saved image: {html.escape(last_saved_image)}

""" except Exception: - print(traceback.format_exc(), file=sys.stderr) + print_error("Exception in training hypernetwork", exc_info=True) finally: pbar.leave = False pbar.close() diff --git a/modules/images.py b/modules/images.py index e21e554c..69151bec 100644 --- a/modules/images.py +++ b/modules/images.py @@ -1,6 +1,4 @@ import datetime -import sys -import traceback import pytz import io @@ -18,6 +16,7 @@ import json import hashlib from modules import sd_samplers, shared, script_callbacks, errors +from modules.errors import print_error from modules.paths_internal import roboto_ttf_file from modules.shared import opts @@ -464,8 +463,7 @@ class FilenameGenerator: replacement = fun(self, *pattern_args) except Exception: replacement = None - print(f"Error adding [{pattern}] to filename", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + print_error(f"Error adding [{pattern}] to filename", exc_info=True) if replacement == NOTHING_AND_SKIP_PREVIOUS_TEXT: continue @@ -697,8 +695,7 @@ def read_info_from_image(image): Negative prompt: {json_info["uc"]} Steps: {json_info["steps"]}, Sampler: {sampler}, CFG scale: {json_info["scale"]}, Seed: {json_info["seed"]}, Size: {image.width}x{image.height}, Clip skip: 2, ENSD: 31337""" except Exception: - print("Error parsing NovelAI image generation parameters:", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + print_error("Error parsing NovelAI image generation parameters", exc_info=True) return geninfo, items diff --git a/modules/interrogate.py b/modules/interrogate.py index 111b1322..d36e1a5a 100644 --- a/modules/interrogate.py +++ b/modules/interrogate.py @@ -1,6 +1,5 @@ import os import sys -import traceback from collections import namedtuple from pathlib import Path import re @@ -12,6 +11,7 @@ from torchvision import transforms from torchvision.transforms.functional import InterpolationMode from modules import devices, paths, shared, lowvram, modelloader, errors +from modules.errors import print_error blip_image_eval_size = 384 clip_model_name = 'ViT-L/14' @@ -216,8 +216,7 @@ class InterrogateModels: res += f", {match}" except Exception: - print("Error interrogating", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + print_error("Error interrogating", exc_info=True) res += "" self.unload() diff --git a/modules/launch_utils.py b/modules/launch_utils.py index 35a52310..22edc106 100644 --- a/modules/launch_utils.py +++ b/modules/launch_utils.py @@ -8,6 +8,7 @@ import json from functools import lru_cache from modules import cmd_args +from modules.errors import print_error from modules.paths_internal import script_path, extensions_dir args, _ = cmd_args.parser.parse_known_args() @@ -188,7 +189,7 @@ def run_extension_installer(extension_dir): print(run(f'"{python}" "{path_installer}"', errdesc=f"Error running install.py for extension {extension_dir}", custom_env=env)) except Exception as e: - print(e, file=sys.stderr) + print_error(str(e)) def list_extensions(settings_file): @@ -198,8 +199,8 @@ def list_extensions(settings_file): if os.path.isfile(settings_file): with open(settings_file, "r", encoding="utf8") as file: settings = json.load(file) - except Exception as e: - print(e, file=sys.stderr) + except Exception: + print_error("Could not load settings", exc_info=True) disabled_extensions = set(settings.get('disabled_extensions', [])) disable_all_extensions = settings.get('disable_all_extensions', 'none') diff --git a/modules/localization.py b/modules/localization.py index ee9c65e7..9a1df343 100644 --- a/modules/localization.py +++ b/modules/localization.py @@ -1,8 +1,7 @@ import json import os -import sys -import traceback +from modules.errors import print_error localizations = {} @@ -31,7 +30,6 @@ def localization_js(current_localization_name: str) -> str: with open(fn, "r", encoding="utf8") as file: data = json.load(file) except Exception: - print(f"Error loading localization from {fn}:", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + print_error(f"Error loading localization from {fn}", exc_info=True) return f"window.localization = {json.dumps(data)}" diff --git a/modules/processing.py b/modules/processing.py index b75f2515..5c9bcce8 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -1,4 +1,5 @@ import json +import logging import math import os import sys @@ -23,7 +24,6 @@ import modules.images as images import modules.styles import modules.sd_models as sd_models import modules.sd_vae as sd_vae -import logging from ldm.data.util import AddMiDaS from ldm.models.diffusion.ddpm import LatentDepth2ImageDiffusion diff --git a/modules/realesrgan_model.py b/modules/realesrgan_model.py index 99983678..c8d0c64f 100644 --- a/modules/realesrgan_model.py +++ b/modules/realesrgan_model.py @@ -1,12 +1,11 @@ import os -import sys -import traceback import numpy as np from PIL import Image from basicsr.utils.download_util import load_file_from_url from realesrgan import RealESRGANer +from modules.errors import print_error from modules.upscaler import Upscaler, UpscalerData from modules.shared import cmd_opts, opts from modules import modelloader @@ -36,8 +35,7 @@ class UpscalerRealESRGAN(Upscaler): self.scalers.append(scaler) except Exception: - print("Error importing Real-ESRGAN:", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + print_error("Error importing Real-ESRGAN", exc_info=True) self.enable = False self.scalers = [] @@ -76,9 +74,8 @@ class UpscalerRealESRGAN(Upscaler): info.local_data_path = load_file_from_url(url=info.data_path, model_dir=self.model_download_path, progress=True) return info - except Exception as e: - print(f"Error making Real-ESRGAN models list: {e}", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + except Exception: + print_error("Error making Real-ESRGAN models list", exc_info=True) return None def load_models(self, _): @@ -135,5 +132,4 @@ def get_realesrgan_models(scaler): ] return models except Exception: - print("Error making Real-ESRGAN models list:", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + print_error("Error making Real-ESRGAN models list", exc_info=True) diff --git a/modules/safe.py b/modules/safe.py index e8f50774..b596f565 100644 --- a/modules/safe.py +++ b/modules/safe.py @@ -2,8 +2,6 @@ import pickle import collections -import sys -import traceback import torch import numpy @@ -11,6 +9,8 @@ import _codecs import zipfile import re +from modules.errors import print_error + # PyTorch 1.13 and later have _TypedStorage renamed to TypedStorage TypedStorage = torch.storage.TypedStorage if hasattr(torch.storage, 'TypedStorage') else torch.storage._TypedStorage @@ -136,17 +136,20 @@ def load_with_extra(filename, extra_handler=None, *args, **kwargs): check_pt(filename, extra_handler) except pickle.UnpicklingError: - print(f"Error verifying pickled file from {filename}:", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) - print("-----> !!!! The file is most likely corrupted !!!! <-----", file=sys.stderr) - print("You can skip this check with --disable-safe-unpickle commandline argument, but that is not going to help you.\n\n", file=sys.stderr) + print_error( + f"Error verifying pickled file from {filename}\n" + "-----> !!!! The file is most likely corrupted !!!! <-----\n" + "You can skip this check with --disable-safe-unpickle commandline argument, but that is not going to help you.\n\n", + exc_info=True, + ) return None - except Exception: - print(f"Error verifying pickled file from {filename}:", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) - print("\nThe file may be malicious, so the program is not going to read it.", file=sys.stderr) - print("You can skip this check with --disable-safe-unpickle commandline argument.\n\n", file=sys.stderr) + print_error( + f"Error verifying pickled file from {filename}\n" + f"The file may be malicious, so the program is not going to read it.\n" + f"You can skip this check with --disable-safe-unpickle commandline argument.\n\n", + exc_info=True, + ) return None return unsafe_torch_load(filename, *args, **kwargs) @@ -190,4 +193,3 @@ with safe.Extra(handler): unsafe_torch_load = torch.load torch.load = load global_extra_handler = None - diff --git a/modules/script_callbacks.py b/modules/script_callbacks.py index d2728e12..6aa9c3b6 100644 --- a/modules/script_callbacks.py +++ b/modules/script_callbacks.py @@ -1,16 +1,15 @@ -import sys -import traceback -from collections import namedtuple import inspect +from collections import namedtuple from typing import Optional, Dict, Any from fastapi import FastAPI from gradio import Blocks +from modules.errors import print_error + def report_exception(c, job): - print(f"Error executing callback {job} for {c.script}", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + print_error(f"Error executing callback {job} for {c.script}", exc_info=True) class ImageSaveParams: diff --git a/modules/script_loading.py b/modules/script_loading.py index 57b15862..26efffcb 100644 --- a/modules/script_loading.py +++ b/modules/script_loading.py @@ -1,8 +1,8 @@ import os -import sys -import traceback import importlib.util +from modules.errors import print_error + def load_module(path): module_spec = importlib.util.spec_from_file_location(os.path.basename(path), path) @@ -27,5 +27,4 @@ def preload_extensions(extensions_dir, parser): module.preload(parser) except Exception: - print(f"Error running preload() for {preload_script}", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + print_error(f"Error running preload() for {preload_script}", exc_info=True) diff --git a/modules/scripts.py b/modules/scripts.py index c902804b..a7168fd1 100644 --- a/modules/scripts.py +++ b/modules/scripts.py @@ -1,12 +1,12 @@ import os import re import sys -import traceback from collections import namedtuple import gradio as gr from modules import shared, paths, script_callbacks, extensions, script_loading, scripts_postprocessing +from modules.errors import print_error AlwaysVisible = object() @@ -264,8 +264,7 @@ def load_scripts(): register_scripts_from_module(script_module) except Exception: - print(f"Error loading script: {scriptfile.filename}", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + print_error(f"Error loading script: {scriptfile.filename}", exc_info=True) finally: sys.path = syspath @@ -280,11 +279,9 @@ def load_scripts(): def wrap_call(func, filename, funcname, *args, default=None, **kwargs): try: - res = func(*args, **kwargs) - return res + return func(*args, **kwargs) except Exception: - print(f"Error calling: {filename}/{funcname}", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + print_error(f"Error calling: {filename}/{funcname}", exc_info=True) return default @@ -450,8 +447,7 @@ class ScriptRunner: script_args = p.script_args[script.args_from:script.args_to] script.process(p, *script_args) except Exception: - print(f"Error running process: {script.filename}", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + print_error(f"Error running process: {script.filename}", exc_info=True) def before_process_batch(self, p, **kwargs): for script in self.alwayson_scripts: @@ -459,8 +455,7 @@ class ScriptRunner: script_args = p.script_args[script.args_from:script.args_to] script.before_process_batch(p, *script_args, **kwargs) except Exception: - print(f"Error running before_process_batch: {script.filename}", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + print_error(f"Error running before_process_batch: {script.filename}", exc_info=True) def process_batch(self, p, **kwargs): for script in self.alwayson_scripts: @@ -468,8 +463,7 @@ class ScriptRunner: script_args = p.script_args[script.args_from:script.args_to] script.process_batch(p, *script_args, **kwargs) except Exception: - print(f"Error running process_batch: {script.filename}", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + print_error(f"Error running process_batch: {script.filename}", exc_info=True) def postprocess(self, p, processed): for script in self.alwayson_scripts: @@ -477,8 +471,7 @@ class ScriptRunner: script_args = p.script_args[script.args_from:script.args_to] script.postprocess(p, processed, *script_args) except Exception: - print(f"Error running postprocess: {script.filename}", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + print_error(f"Error running postprocess: {script.filename}", exc_info=True) def postprocess_batch(self, p, images, **kwargs): for script in self.alwayson_scripts: @@ -486,8 +479,7 @@ class ScriptRunner: script_args = p.script_args[script.args_from:script.args_to] script.postprocess_batch(p, *script_args, images=images, **kwargs) except Exception: - print(f"Error running postprocess_batch: {script.filename}", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + print_error(f"Error running postprocess_batch: {script.filename}", exc_info=True) def postprocess_image(self, p, pp: PostprocessImageArgs): for script in self.alwayson_scripts: @@ -495,24 +487,21 @@ class ScriptRunner: script_args = p.script_args[script.args_from:script.args_to] script.postprocess_image(p, pp, *script_args) except Exception: - print(f"Error running postprocess_batch: {script.filename}", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + print_error(f"Error running postprocess_image: {script.filename}", exc_info=True) def before_component(self, component, **kwargs): for script in self.scripts: try: script.before_component(component, **kwargs) except Exception: - print(f"Error running before_component: {script.filename}", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + print_error(f"Error running before_component: {script.filename}", exc_info=True) def after_component(self, component, **kwargs): for script in self.scripts: try: script.after_component(component, **kwargs) except Exception: - print(f"Error running after_component: {script.filename}", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + print_error(f"Error running after_component: {script.filename}", exc_info=True) def reload_sources(self, cache): for si, script in list(enumerate(self.scripts)): diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py index 2ec0b049..fd186fa2 100644 --- a/modules/sd_hijack_optimizations.py +++ b/modules/sd_hijack_optimizations.py @@ -1,7 +1,5 @@ from __future__ import annotations import math -import sys -import traceback import psutil import torch @@ -11,6 +9,7 @@ from ldm.util import default from einops import rearrange from modules import shared, errors, devices, sub_quadratic_attention +from modules.errors import print_error from modules.hypernetworks import hypernetwork import ldm.modules.attention @@ -140,8 +139,7 @@ if shared.cmd_opts.xformers or shared.cmd_opts.force_enable_xformers: import xformers.ops shared.xformers_available = True except Exception: - print("Cannot import xformers", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + print_error("Cannot import xformers", exc_info=True) def get_available_vram(): diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index d489ed1e..a040a988 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -1,6 +1,4 @@ import os -import sys -import traceback from collections import namedtuple import torch @@ -16,6 +14,7 @@ from torch.utils.tensorboard import SummaryWriter from modules import shared, devices, sd_hijack, processing, sd_models, images, sd_samplers, sd_hijack_checkpoint import modules.textual_inversion.dataset +from modules.errors import print_error from modules.textual_inversion.learn_schedule import LearnRateScheduler from modules.textual_inversion.image_embedding import embedding_to_b64, embedding_from_b64, insert_image_data_embed, extract_image_data_embed, caption_image_overlay @@ -207,8 +206,7 @@ class EmbeddingDatabase: self.load_from_file(fullfn, fn) except Exception: - print(f"Error loading embedding {fn}:", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + print_error(f"Error loading embedding {fn}", exc_info=True) continue def load_textual_inversion_embeddings(self, force_reload=False): @@ -632,8 +630,7 @@ Last saved image: {html.escape(last_saved_image)}
filename = os.path.join(shared.cmd_opts.embeddings_dir, f'{embedding_name}.pt') save_embedding(embedding, optimizer, checkpoint, embedding_name, filename, remove_cached_checksum=True) except Exception: - print(traceback.format_exc(), file=sys.stderr) - pass + print_error("Error training embedding", exc_info=True) finally: pbar.leave = False pbar.close() diff --git a/modules/ui.py b/modules/ui.py index 001b9792..1ad94f02 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -2,7 +2,6 @@ import json import mimetypes import os import sys -import traceback from functools import reduce import warnings @@ -14,6 +13,7 @@ from PIL import Image, PngImagePlugin # noqa: F401 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, ui_common, ui_postprocessing, progress, ui_loadsave +from modules.errors import print_error from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML from modules.paths import script_path, data_path @@ -231,9 +231,8 @@ def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info: res = all_seeds[index if 0 <= index < len(all_seeds) else 0] except json.decoder.JSONDecodeError: - if gen_info_string != '': - print("Error parsing JSON generation info:", file=sys.stderr) - print(gen_info_string, file=sys.stderr) + if gen_info_string: + print_error(f"Error parsing JSON generation info: {gen_info_string}") return [res, gr_show(False)] @@ -1753,8 +1752,7 @@ def create_ui(): try: results = modules.extras.run_modelmerger(*args) except Exception as e: - print("Error loading/saving model file:", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + print_error("Error loading/saving model file", exc_info=True) modules.sd_models.list_models() # to remove the potentially missing models from the list return [*[gr.Dropdown.update(choices=modules.sd_models.checkpoint_tiles()) for _ in range(4)], f"Error merging checkpoints: {e}"] return results diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py index 515ec262..cadf56be 100644 --- a/modules/ui_extensions.py +++ b/modules/ui_extensions.py @@ -1,10 +1,8 @@ import json import os.path -import sys import threading import time from datetime import datetime -import traceback import git @@ -14,6 +12,7 @@ import shutil import errno from modules import extensions, shared, paths, config_states +from modules.errors import print_error from modules.paths_internal import config_states_dir from modules.call_queue import wrap_gradio_gpu_call @@ -46,8 +45,7 @@ def apply_and_restart(disable_list, update_list, disable_all): try: ext.fetch_and_reset_hard() except Exception: - print(f"Error getting updates for {ext.name}:", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + print_error(f"Error getting updates for {ext.name}", exc_info=True) shared.opts.disabled_extensions = disabled shared.opts.disable_all_extensions = disable_all @@ -113,8 +111,7 @@ def check_updates(id_task, disable_list): if 'FETCH_HEAD' not in str(e): raise except Exception: - print(f"Error checking updates for {ext.name}:", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + print_error(f"Error checking updates for {ext.name}", exc_info=True) shared.state.nextjob() diff --git a/scripts/prompts_from_file.py b/scripts/prompts_from_file.py index b918a764..4dc24615 100644 --- a/scripts/prompts_from_file.py +++ b/scripts/prompts_from_file.py @@ -1,13 +1,12 @@ import copy import random -import sys -import traceback import shlex import modules.scripts as scripts import gradio as gr from modules import sd_samplers +from modules.errors import print_error from modules.processing import Processed, process_images from modules.shared import state @@ -136,8 +135,7 @@ class Script(scripts.Script): try: args = cmdargs(line) except Exception: - print(f"Error parsing line {line} as commandline:", file=sys.stderr) - print(traceback.format_exc(), file=sys.stderr) + print_error(f"Error parsing line {line} as commandline", exc_info=True) args = {"prompt": line} else: args = {"prompt": line} -- cgit v1.2.3 From 05933840f0676dd1a90a7e2ad3f2a0672624b2cd Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Wed, 31 May 2023 19:56:37 +0300 Subject: rename print_error to report, use it with together with package name --- extensions-builtin/LDSR/scripts/ldsr_model.py | 5 ++--- extensions-builtin/ScuNET/scripts/scunet_model.py | 5 ++--- modules/api/api.py | 5 ++--- modules/call_queue.py | 5 ++--- modules/codeformer_model.py | 7 +++---- modules/config_states.py | 9 ++++----- modules/errors.py | 8 ++------ modules/extensions.py | 7 +++---- modules/gfpgan_model.py | 5 ++--- modules/hypernetworks/hypernetwork.py | 7 +++---- modules/images.py | 5 ++--- modules/interrogate.py | 3 +-- modules/launch_utils.py | 7 +++---- modules/localization.py | 4 ++-- modules/realesrgan_model.py | 10 +++++----- modules/safe.py | 7 ++++--- modules/script_callbacks.py | 4 ++-- modules/script_loading.py | 4 ++-- modules/scripts.py | 23 +++++++++++------------ modules/sd_hijack_optimizations.py | 3 +-- modules/textual_inversion/textual_inversion.py | 7 +++---- modules/ui.py | 7 +++---- modules/ui_extensions.py | 7 +++---- scripts/prompts_from_file.py | 5 ++--- 24 files changed, 69 insertions(+), 90 deletions(-) (limited to 'extensions-builtin/ScuNET') diff --git a/extensions-builtin/LDSR/scripts/ldsr_model.py b/extensions-builtin/LDSR/scripts/ldsr_model.py index 95f1669d..dbd6d331 100644 --- a/extensions-builtin/LDSR/scripts/ldsr_model.py +++ b/extensions-builtin/LDSR/scripts/ldsr_model.py @@ -2,10 +2,9 @@ import os from basicsr.utils.download_util import load_file_from_url -from modules.errors import print_error from modules.upscaler import Upscaler, UpscalerData from ldsr_model_arch import LDSR -from modules import shared, script_callbacks +from modules import shared, script_callbacks, errors import sd_hijack_autoencoder # noqa: F401 import sd_hijack_ddpm_v1 # noqa: F401 @@ -51,7 +50,7 @@ class UpscalerLDSR(Upscaler): try: return LDSR(model, yaml) except Exception: - print_error("Error importing LDSR", exc_info=True) + errors.report("Error importing LDSR", exc_info=True) return None def do_upscale(self, img, path): diff --git a/extensions-builtin/ScuNET/scripts/scunet_model.py b/extensions-builtin/ScuNET/scripts/scunet_model.py index dd1b822e..85b4505f 100644 --- a/extensions-builtin/ScuNET/scripts/scunet_model.py +++ b/extensions-builtin/ScuNET/scripts/scunet_model.py @@ -9,10 +9,9 @@ from tqdm import tqdm from basicsr.utils.download_util import load_file_from_url import modules.upscaler -from modules import devices, modelloader, script_callbacks +from modules import devices, modelloader, script_callbacks, errors from scunet_model_arch import SCUNet as net -from modules.errors import print_error from modules.shared import opts @@ -39,7 +38,7 @@ class UpscalerScuNET(modules.upscaler.Upscaler): scaler_data = modules.upscaler.UpscalerData(name, file, self, 4) scalers.append(scaler_data) except Exception: - print_error(f"Error loading ScuNET model: {file}", exc_info=True) + errors.report(f"Error loading ScuNET model: {file}", exc_info=True) if add_model2: scaler_data2 = modules.upscaler.UpscalerData(self.model_name2, self.model_url2, self) scalers.append(scaler_data2) diff --git a/modules/api/api.py b/modules/api/api.py index fbd616a3..d34ab422 100644 --- a/modules/api/api.py +++ b/modules/api/api.py @@ -14,9 +14,8 @@ from fastapi.encoders import jsonable_encoder from secrets import compare_digest import modules.shared as shared -from modules import sd_samplers, deepbooru, sd_hijack, images, scripts, ui, postprocessing +from modules import sd_samplers, deepbooru, sd_hijack, images, scripts, ui, postprocessing, errors from modules.api import models -from modules.errors import print_error from modules.shared import opts from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img, process_images from modules.textual_inversion.textual_inversion import create_embedding, train_embedding @@ -145,7 +144,7 @@ def api_middleware(app: FastAPI): print(message) console.print_exception(show_locals=True, max_frames=2, extra_lines=1, suppress=[anyio, starlette], word_wrap=False, width=min([console.width, 200])) else: - print_error(message, exc_info=True) + errors.report(message, exc_info=True) return JSONResponse(status_code=vars(e).get('status_code', 500), content=jsonable_encoder(err)) @app.middleware("http") diff --git a/modules/call_queue.py b/modules/call_queue.py index dba2a9b4..53af6d70 100644 --- a/modules/call_queue.py +++ b/modules/call_queue.py @@ -2,8 +2,7 @@ import html import threading import time -from modules import shared, progress -from modules.errors import print_error +from modules import shared, progress, errors queue_lock = threading.Lock() @@ -62,7 +61,7 @@ def wrap_gradio_call(func, extra_outputs=None, add_stats=False): arg_str = f"Arguments: {args} {kwargs}"[:max_debug_str_len] if len(arg_str) > max_debug_str_len: arg_str += f" (Argument list truncated at {max_debug_str_len}/{len(arg_str)} characters)" - print_error(f"{message}\n{arg_str}", exc_info=True) + errors.report(f"{message}\n{arg_str}", exc_info=True) shared.state.job = "" shared.state.job_count = 0 diff --git a/modules/codeformer_model.py b/modules/codeformer_model.py index 76143e9f..4260b016 100644 --- a/modules/codeformer_model.py +++ b/modules/codeformer_model.py @@ -5,8 +5,7 @@ import torch import modules.face_restoration import modules.shared -from modules import shared, devices, modelloader -from modules.errors import print_error +from modules import shared, devices, modelloader, errors from modules.paths import models_path # codeformer people made a choice to include modified basicsr library to their project which makes @@ -105,7 +104,7 @@ def setup_model(dirname): del output torch.cuda.empty_cache() except Exception: - print_error('Failed inference for CodeFormer', exc_info=True) + errors.report('Failed inference for CodeFormer', exc_info=True) restored_face = tensor2img(cropped_face_t, rgb2bgr=True, min_max=(-1, 1)) restored_face = restored_face.astype('uint8') @@ -134,6 +133,6 @@ def setup_model(dirname): shared.face_restorers.append(codeformer) except Exception: - print_error("Error setting up CodeFormer", exc_info=True) + errors.report("Error setting up CodeFormer", exc_info=True) # sys.path = stored_sys_path diff --git a/modules/config_states.py b/modules/config_states.py index faeaf28b..6f1ab53f 100644 --- a/modules/config_states.py +++ b/modules/config_states.py @@ -11,8 +11,7 @@ from datetime import datetime from collections import OrderedDict import git -from modules import shared, extensions -from modules.errors import print_error +from modules import shared, extensions, errors from modules.paths_internal import script_path, config_states_dir @@ -52,7 +51,7 @@ def get_webui_config(): if os.path.exists(os.path.join(script_path, ".git")): webui_repo = git.Repo(script_path) except Exception: - print_error(f"Error reading webui git info from {script_path}", exc_info=True) + errors.report(f"Error reading webui git info from {script_path}", exc_info=True) webui_remote = None webui_commit_hash = None @@ -132,7 +131,7 @@ def restore_webui_config(config): if os.path.exists(os.path.join(script_path, ".git")): webui_repo = git.Repo(script_path) except Exception: - print_error(f"Error reading webui git info from {script_path}", exc_info=True) + errors.report(f"Error reading webui git info from {script_path}", exc_info=True) return try: @@ -140,7 +139,7 @@ def restore_webui_config(config): webui_repo.git.reset(webui_commit_hash, hard=True) print(f"* Restored webui to commit {webui_commit_hash}.") except Exception: - print_error(f"Error restoring webui to commit{webui_commit_hash}") + errors.report(f"Error restoring webui to commit{webui_commit_hash}") def restore_extension_config(config): diff --git a/modules/errors.py b/modules/errors.py index 41d8dc93..e408f500 100644 --- a/modules/errors.py +++ b/modules/errors.py @@ -3,11 +3,7 @@ import textwrap import traceback -def print_error( - message: str, - *, - exc_info: bool = False, -) -> None: +def report(message: str, *, exc_info: bool = False) -> None: """ Print an error message to stderr, with optional traceback. """ @@ -15,7 +11,7 @@ def print_error( print("***", line, file=sys.stderr) if exc_info: print(textwrap.indent(traceback.format_exc(), " "), file=sys.stderr) - print("---") + print("---", file=sys.stderr) def print_error_explanation(message): diff --git a/modules/extensions.py b/modules/extensions.py index 92f93ad9..8608584b 100644 --- a/modules/extensions.py +++ b/modules/extensions.py @@ -1,8 +1,7 @@ import os import threading -from modules import shared -from modules.errors import print_error +from modules import shared, errors from modules.gitpython_hack import Repo from modules.paths_internal import extensions_dir, extensions_builtin_dir, script_path # noqa: F401 @@ -54,7 +53,7 @@ class Extension: if os.path.exists(os.path.join(self.path, ".git")): repo = Repo(self.path) except Exception: - print_error(f"Error reading github repository info from {self.path}", exc_info=True) + errors.report(f"Error reading github repository info from {self.path}", exc_info=True) if repo is None or repo.bare: self.remote = None @@ -70,7 +69,7 @@ class Extension: self.version = self.commit_hash[:8] except Exception: - print_error(f"Failed reading extension data from Git repository ({self.name})", exc_info=True) + errors.report(f"Failed reading extension data from Git repository ({self.name})", exc_info=True) self.remote = None self.have_info_from_repo = True diff --git a/modules/gfpgan_model.py b/modules/gfpgan_model.py index d2f647fe..e239a09d 100644 --- a/modules/gfpgan_model.py +++ b/modules/gfpgan_model.py @@ -4,8 +4,7 @@ import facexlib import gfpgan import modules.face_restoration -from modules import paths, shared, devices, modelloader -from modules.errors import print_error +from modules import paths, shared, devices, modelloader, errors model_dir = "GFPGAN" user_path = None @@ -111,4 +110,4 @@ def setup_model(dirname): shared.face_restorers.append(FaceRestorerGFPGAN()) except Exception: - print_error("Error setting up GFPGAN", exc_info=True) + errors.report("Error setting up GFPGAN", exc_info=True) diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index fcc1ef20..5d12b449 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -9,8 +9,7 @@ import torch import tqdm from einops import rearrange, repeat from ldm.util import default -from modules import devices, processing, sd_models, shared, sd_samplers, hashes, sd_hijack_checkpoint -from modules.errors import print_error +from modules import devices, processing, sd_models, shared, sd_samplers, hashes, sd_hijack_checkpoint, errors from modules.textual_inversion import textual_inversion, logging from modules.textual_inversion.learn_schedule import LearnRateScheduler from torch import einsum @@ -329,7 +328,7 @@ def load_hypernetwork(name): hypernetwork.load(path) return hypernetwork except Exception: - print_error(f"Error loading hypernetwork {path}", exc_info=True) + errors.report(f"Error loading hypernetwork {path}", exc_info=True) return None @@ -766,7 +765,7 @@ Last saved image: {html.escape(last_saved_image)}

""" except Exception: - print_error("Exception in training hypernetwork", exc_info=True) + errors.report("Exception in training hypernetwork", exc_info=True) finally: pbar.leave = False pbar.close() diff --git a/modules/images.py b/modules/images.py index 09f728df..30e9ffc5 100644 --- a/modules/images.py +++ b/modules/images.py @@ -16,7 +16,6 @@ import json import hashlib from modules import sd_samplers, shared, script_callbacks, errors -from modules.errors import print_error from modules.paths_internal import roboto_ttf_file from modules.shared import opts @@ -463,7 +462,7 @@ class FilenameGenerator: replacement = fun(self, *pattern_args) except Exception: replacement = None - print_error(f"Error adding [{pattern}] to filename", exc_info=True) + errors.report(f"Error adding [{pattern}] to filename", exc_info=True) if replacement == NOTHING_AND_SKIP_PREVIOUS_TEXT: continue @@ -698,7 +697,7 @@ def read_info_from_image(image): Negative prompt: {json_info["uc"]} Steps: {json_info["steps"]}, Sampler: {sampler}, CFG scale: {json_info["scale"]}, Seed: {json_info["seed"]}, Size: {image.width}x{image.height}, Clip skip: 2, ENSD: 31337""" except Exception: - print_error("Error parsing NovelAI image generation parameters", exc_info=True) + errors.report("Error parsing NovelAI image generation parameters", exc_info=True) return geninfo, items diff --git a/modules/interrogate.py b/modules/interrogate.py index d36e1a5a..9b2c5b60 100644 --- a/modules/interrogate.py +++ b/modules/interrogate.py @@ -11,7 +11,6 @@ from torchvision import transforms from torchvision.transforms.functional import InterpolationMode from modules import devices, paths, shared, lowvram, modelloader, errors -from modules.errors import print_error blip_image_eval_size = 384 clip_model_name = 'ViT-L/14' @@ -216,7 +215,7 @@ class InterrogateModels: res += f", {match}" except Exception: - print_error("Error interrogating", exc_info=True) + errors.report("Error interrogating", exc_info=True) res += "" self.unload() diff --git a/modules/launch_utils.py b/modules/launch_utils.py index 0bf4cb7e..6e9bb770 100644 --- a/modules/launch_utils.py +++ b/modules/launch_utils.py @@ -7,8 +7,7 @@ import platform import json from functools import lru_cache -from modules import cmd_args -from modules.errors import print_error +from modules import cmd_args, errors from modules.paths_internal import script_path, extensions_dir args, _ = cmd_args.parser.parse_known_args() @@ -189,7 +188,7 @@ def run_extension_installer(extension_dir): print(run(f'"{python}" "{path_installer}"', errdesc=f"Error running install.py for extension {extension_dir}", custom_env=env)) except Exception as e: - print_error(str(e)) + errors.report(str(e)) def list_extensions(settings_file): @@ -200,7 +199,7 @@ def list_extensions(settings_file): with open(settings_file, "r", encoding="utf8") as file: settings = json.load(file) except Exception: - print_error("Could not load settings", exc_info=True) + errors.report("Could not load settings", exc_info=True) disabled_extensions = set(settings.get('disabled_extensions', [])) disable_all_extensions = settings.get('disable_all_extensions', 'none') diff --git a/modules/localization.py b/modules/localization.py index 9a1df343..e8f585da 100644 --- a/modules/localization.py +++ b/modules/localization.py @@ -1,7 +1,7 @@ import json import os -from modules.errors import print_error +from modules import errors localizations = {} @@ -30,6 +30,6 @@ def localization_js(current_localization_name: str) -> str: with open(fn, "r", encoding="utf8") as file: data = json.load(file) except Exception: - print_error(f"Error loading localization from {fn}", exc_info=True) + errors.report(f"Error loading localization from {fn}", exc_info=True) return f"window.localization = {json.dumps(data)}" diff --git a/modules/realesrgan_model.py b/modules/realesrgan_model.py index c8d0c64f..2d27b321 100644 --- a/modules/realesrgan_model.py +++ b/modules/realesrgan_model.py @@ -5,10 +5,10 @@ from PIL import Image from basicsr.utils.download_util import load_file_from_url from realesrgan import RealESRGANer -from modules.errors import print_error from modules.upscaler import Upscaler, UpscalerData from modules.shared import cmd_opts, opts -from modules import modelloader +from modules import modelloader, errors + class UpscalerRealESRGAN(Upscaler): def __init__(self, path): @@ -35,7 +35,7 @@ class UpscalerRealESRGAN(Upscaler): self.scalers.append(scaler) except Exception: - print_error("Error importing Real-ESRGAN", exc_info=True) + errors.report("Error importing Real-ESRGAN", exc_info=True) self.enable = False self.scalers = [] @@ -75,7 +75,7 @@ class UpscalerRealESRGAN(Upscaler): return info except Exception: - print_error("Error making Real-ESRGAN models list", exc_info=True) + errors.report("Error making Real-ESRGAN models list", exc_info=True) return None def load_models(self, _): @@ -132,4 +132,4 @@ def get_realesrgan_models(scaler): ] return models except Exception: - print_error("Error making Real-ESRGAN models list", exc_info=True) + errors.report("Error making Real-ESRGAN models list", exc_info=True) diff --git a/modules/safe.py b/modules/safe.py index b596f565..b1d08a79 100644 --- a/modules/safe.py +++ b/modules/safe.py @@ -9,9 +9,10 @@ import _codecs import zipfile import re -from modules.errors import print_error # PyTorch 1.13 and later have _TypedStorage renamed to TypedStorage +from modules import errors + TypedStorage = torch.storage.TypedStorage if hasattr(torch.storage, 'TypedStorage') else torch.storage._TypedStorage def encode(*args): @@ -136,7 +137,7 @@ def load_with_extra(filename, extra_handler=None, *args, **kwargs): check_pt(filename, extra_handler) except pickle.UnpicklingError: - print_error( + errors.report( f"Error verifying pickled file from {filename}\n" "-----> !!!! The file is most likely corrupted !!!! <-----\n" "You can skip this check with --disable-safe-unpickle commandline argument, but that is not going to help you.\n\n", @@ -144,7 +145,7 @@ def load_with_extra(filename, extra_handler=None, *args, **kwargs): ) return None except Exception: - print_error( + errors.report( f"Error verifying pickled file from {filename}\n" f"The file may be malicious, so the program is not going to read it.\n" f"You can skip this check with --disable-safe-unpickle commandline argument.\n\n", diff --git a/modules/script_callbacks.py b/modules/script_callbacks.py index 6aa9c3b6..ec1469d0 100644 --- a/modules/script_callbacks.py +++ b/modules/script_callbacks.py @@ -5,11 +5,11 @@ from typing import Optional, Dict, Any from fastapi import FastAPI from gradio import Blocks -from modules.errors import print_error +from modules import errors def report_exception(c, job): - print_error(f"Error executing callback {job} for {c.script}", exc_info=True) + errors.report(f"Error executing callback {job} for {c.script}", exc_info=True) class ImageSaveParams: diff --git a/modules/script_loading.py b/modules/script_loading.py index 26efffcb..306a1f35 100644 --- a/modules/script_loading.py +++ b/modules/script_loading.py @@ -1,7 +1,7 @@ import os import importlib.util -from modules.errors import print_error +from modules import errors def load_module(path): @@ -27,4 +27,4 @@ def preload_extensions(extensions_dir, parser): module.preload(parser) except Exception: - print_error(f"Error running preload() for {preload_script}", exc_info=True) + errors.report(f"Error running preload() for {preload_script}", exc_info=True) diff --git a/modules/scripts.py b/modules/scripts.py index a7168fd1..0970f38e 100644 --- a/modules/scripts.py +++ b/modules/scripts.py @@ -5,8 +5,7 @@ from collections import namedtuple import gradio as gr -from modules import shared, paths, script_callbacks, extensions, script_loading, scripts_postprocessing -from modules.errors import print_error +from modules import shared, paths, script_callbacks, extensions, script_loading, scripts_postprocessing, errors AlwaysVisible = object() @@ -264,7 +263,7 @@ def load_scripts(): register_scripts_from_module(script_module) except Exception: - print_error(f"Error loading script: {scriptfile.filename}", exc_info=True) + errors.report(f"Error loading script: {scriptfile.filename}", exc_info=True) finally: sys.path = syspath @@ -281,7 +280,7 @@ def wrap_call(func, filename, funcname, *args, default=None, **kwargs): try: return func(*args, **kwargs) except Exception: - print_error(f"Error calling: {filename}/{funcname}", exc_info=True) + errors.report(f"Error calling: {filename}/{funcname}", exc_info=True) return default @@ -447,7 +446,7 @@ class ScriptRunner: script_args = p.script_args[script.args_from:script.args_to] script.process(p, *script_args) except Exception: - print_error(f"Error running process: {script.filename}", exc_info=True) + errors.report(f"Error running process: {script.filename}", exc_info=True) def before_process_batch(self, p, **kwargs): for script in self.alwayson_scripts: @@ -455,7 +454,7 @@ class ScriptRunner: script_args = p.script_args[script.args_from:script.args_to] script.before_process_batch(p, *script_args, **kwargs) except Exception: - print_error(f"Error running before_process_batch: {script.filename}", exc_info=True) + errors.report(f"Error running before_process_batch: {script.filename}", exc_info=True) def process_batch(self, p, **kwargs): for script in self.alwayson_scripts: @@ -463,7 +462,7 @@ class ScriptRunner: script_args = p.script_args[script.args_from:script.args_to] script.process_batch(p, *script_args, **kwargs) except Exception: - print_error(f"Error running process_batch: {script.filename}", exc_info=True) + errors.report(f"Error running process_batch: {script.filename}", exc_info=True) def postprocess(self, p, processed): for script in self.alwayson_scripts: @@ -471,7 +470,7 @@ class ScriptRunner: script_args = p.script_args[script.args_from:script.args_to] script.postprocess(p, processed, *script_args) except Exception: - print_error(f"Error running postprocess: {script.filename}", exc_info=True) + errors.report(f"Error running postprocess: {script.filename}", exc_info=True) def postprocess_batch(self, p, images, **kwargs): for script in self.alwayson_scripts: @@ -479,7 +478,7 @@ class ScriptRunner: script_args = p.script_args[script.args_from:script.args_to] script.postprocess_batch(p, *script_args, images=images, **kwargs) except Exception: - print_error(f"Error running postprocess_batch: {script.filename}", exc_info=True) + errors.report(f"Error running postprocess_batch: {script.filename}", exc_info=True) def postprocess_image(self, p, pp: PostprocessImageArgs): for script in self.alwayson_scripts: @@ -487,21 +486,21 @@ class ScriptRunner: script_args = p.script_args[script.args_from:script.args_to] script.postprocess_image(p, pp, *script_args) except Exception: - print_error(f"Error running postprocess_image: {script.filename}", exc_info=True) + errors.report(f"Error running postprocess_image: {script.filename}", exc_info=True) def before_component(self, component, **kwargs): for script in self.scripts: try: script.before_component(component, **kwargs) except Exception: - print_error(f"Error running before_component: {script.filename}", exc_info=True) + errors.report(f"Error running before_component: {script.filename}", exc_info=True) def after_component(self, component, **kwargs): for script in self.scripts: try: script.after_component(component, **kwargs) except Exception: - print_error(f"Error running after_component: {script.filename}", exc_info=True) + errors.report(f"Error running after_component: {script.filename}", exc_info=True) def reload_sources(self, cache): for si, script in list(enumerate(self.scripts)): diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py index fd186fa2..5f0ff513 100644 --- a/modules/sd_hijack_optimizations.py +++ b/modules/sd_hijack_optimizations.py @@ -9,7 +9,6 @@ from ldm.util import default from einops import rearrange from modules import shared, errors, devices, sub_quadratic_attention -from modules.errors import print_error from modules.hypernetworks import hypernetwork import ldm.modules.attention @@ -139,7 +138,7 @@ if shared.cmd_opts.xformers or shared.cmd_opts.force_enable_xformers: import xformers.ops shared.xformers_available = True except Exception: - print_error("Cannot import xformers", exc_info=True) + errors.report("Cannot import xformers", exc_info=True) def get_available_vram(): diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py index b3dcb140..8da050ca 100644 --- a/modules/textual_inversion/textual_inversion.py +++ b/modules/textual_inversion/textual_inversion.py @@ -12,9 +12,8 @@ import numpy as np from PIL import Image, PngImagePlugin from torch.utils.tensorboard import SummaryWriter -from modules import shared, devices, sd_hijack, processing, sd_models, images, sd_samplers, sd_hijack_checkpoint +from modules import shared, devices, sd_hijack, processing, sd_models, images, sd_samplers, sd_hijack_checkpoint, errors import modules.textual_inversion.dataset -from modules.errors import print_error from modules.textual_inversion.learn_schedule import LearnRateScheduler from modules.textual_inversion.image_embedding import embedding_to_b64, embedding_from_b64, insert_image_data_embed, extract_image_data_embed, caption_image_overlay @@ -219,7 +218,7 @@ class EmbeddingDatabase: self.load_from_file(fullfn, fn) except Exception: - print_error(f"Error loading embedding {fn}", exc_info=True) + errors.report(f"Error loading embedding {fn}", exc_info=True) continue def load_textual_inversion_embeddings(self, force_reload=False): @@ -643,7 +642,7 @@ Last saved image: {html.escape(last_saved_image)}
filename = os.path.join(shared.cmd_opts.embeddings_dir, f'{embedding_name}.pt') save_embedding(embedding, optimizer, checkpoint, embedding_name, filename, remove_cached_checksum=True) except Exception: - print_error("Error training embedding", exc_info=True) + errors.report("Error training embedding", exc_info=True) finally: pbar.leave = False pbar.close() diff --git a/modules/ui.py b/modules/ui.py index fb6b2498..f361264c 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -12,8 +12,7 @@ import numpy as np from PIL import Image, PngImagePlugin # noqa: F401 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, ui_common, ui_postprocessing, progress, ui_loadsave -from modules.errors import print_error +from modules import sd_hijack, sd_models, localization, script_callbacks, ui_extensions, deepbooru, sd_vae, extra_networks, ui_common, ui_postprocessing, progress, ui_loadsave, errors from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML from modules.paths import script_path, data_path @@ -232,7 +231,7 @@ def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info: except json.decoder.JSONDecodeError: if gen_info_string: - print_error(f"Error parsing JSON generation info: {gen_info_string}") + errors.report(f"Error parsing JSON generation info: {gen_info_string}") return [res, gr_show(False)] @@ -1752,7 +1751,7 @@ def create_ui(): try: results = modules.extras.run_modelmerger(*args) except Exception as e: - print_error("Error loading/saving model file", exc_info=True) + errors.report("Error loading/saving model file", exc_info=True) modules.sd_models.list_models() # to remove the potentially missing models from the list return [*[gr.Dropdown.update(choices=modules.sd_models.checkpoint_tiles()) for _ in range(4)], f"Error merging checkpoints: {e}"] return results diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py index e2ee9d72..3140ed64 100644 --- a/modules/ui_extensions.py +++ b/modules/ui_extensions.py @@ -11,8 +11,7 @@ import html import shutil import errno -from modules import extensions, shared, paths, config_states -from modules.errors import print_error +from modules import extensions, shared, paths, config_states, errors from modules.paths_internal import config_states_dir from modules.call_queue import wrap_gradio_gpu_call @@ -45,7 +44,7 @@ def apply_and_restart(disable_list, update_list, disable_all): try: ext.fetch_and_reset_hard() except Exception: - print_error(f"Error getting updates for {ext.name}", exc_info=True) + errors.report(f"Error getting updates for {ext.name}", exc_info=True) shared.opts.disabled_extensions = disabled shared.opts.disable_all_extensions = disable_all @@ -111,7 +110,7 @@ def check_updates(id_task, disable_list): if 'FETCH_HEAD' not in str(e): raise except Exception: - print_error(f"Error checking updates for {ext.name}", exc_info=True) + errors.report(f"Error checking updates for {ext.name}", exc_info=True) shared.state.nextjob() diff --git a/scripts/prompts_from_file.py b/scripts/prompts_from_file.py index 4dc24615..83a2f220 100644 --- a/scripts/prompts_from_file.py +++ b/scripts/prompts_from_file.py @@ -5,8 +5,7 @@ import shlex import modules.scripts as scripts import gradio as gr -from modules import sd_samplers -from modules.errors import print_error +from modules import sd_samplers, errors from modules.processing import Processed, process_images from modules.shared import state @@ -135,7 +134,7 @@ class Script(scripts.Script): try: args = cmdargs(line) except Exception: - print_error(f"Error parsing line {line} as commandline", exc_info=True) + errors.report(f"Error parsing line {line} as commandline", exc_info=True) args = {"prompt": line} else: args = {"prompt": line} -- cgit v1.2.3 From 89352a2f52c6be51318192cedd86c8a342966a49 Mon Sep 17 00:00:00 2001 From: Aarni Koskela Date: Mon, 29 May 2023 09:34:26 +0300 Subject: Move `load_file_from_url` to modelloader --- extensions-builtin/LDSR/scripts/ldsr_model.py | 7 +++--- extensions-builtin/ScuNET/scripts/scunet_model.py | 5 ++-- extensions-builtin/SwinIR/scripts/swinir_model.py | 8 ++++--- modules/esrgan_model.py | 4 +--- modules/modelloader.py | 29 ++++++++++++++++++++--- modules/realesrgan_model.py | 4 ++-- 6 files changed, 39 insertions(+), 18 deletions(-) (limited to 'extensions-builtin/ScuNET') diff --git a/extensions-builtin/LDSR/scripts/ldsr_model.py b/extensions-builtin/LDSR/scripts/ldsr_model.py index dbd6d331..bf9b6de2 100644 --- a/extensions-builtin/LDSR/scripts/ldsr_model.py +++ b/extensions-builtin/LDSR/scripts/ldsr_model.py @@ -1,7 +1,6 @@ import os -from basicsr.utils.download_util import load_file_from_url - +from modules.modelloader import load_file_from_url from modules.upscaler import Upscaler, UpscalerData from ldsr_model_arch import LDSR from modules import shared, script_callbacks, errors @@ -43,9 +42,9 @@ class UpscalerLDSR(Upscaler): if local_safetensors_path is not None and os.path.exists(local_safetensors_path): model = local_safetensors_path else: - model = local_ckpt_path if local_ckpt_path is not None else load_file_from_url(url=self.model_url, model_dir=self.model_download_path, file_name="model.ckpt", progress=True) + model = local_ckpt_path or load_file_from_url(self.model_url, model_dir=self.model_download_path, file_name="model.ckpt") - yaml = local_yaml_path if local_yaml_path is not None else load_file_from_url(url=self.yaml_url, model_dir=self.model_download_path, file_name="project.yaml", progress=True) + yaml = local_yaml_path or load_file_from_url(self.yaml_url, model_dir=self.model_download_path, file_name="project.yaml") try: return LDSR(model, yaml) diff --git a/extensions-builtin/ScuNET/scripts/scunet_model.py b/extensions-builtin/ScuNET/scripts/scunet_model.py index 85b4505f..2785b551 100644 --- a/extensions-builtin/ScuNET/scripts/scunet_model.py +++ b/extensions-builtin/ScuNET/scripts/scunet_model.py @@ -6,12 +6,11 @@ import numpy as np import torch from tqdm import tqdm -from basicsr.utils.download_util import load_file_from_url - import modules.upscaler from modules import devices, modelloader, script_callbacks, errors from scunet_model_arch import SCUNet as net +from modules.modelloader import load_file_from_url from modules.shared import opts @@ -120,7 +119,7 @@ class UpscalerScuNET(modules.upscaler.Upscaler): def load_model(self, path: str): device = devices.get_device_for('scunet') if "http" in path: - filename = load_file_from_url(url=self.model_url, model_dir=self.model_download_path, file_name="%s.pth" % self.name, progress=True) + filename = load_file_from_url(self.model_url, model_dir=self.model_download_path, file_name=f"{self.name}.pth") else: filename = path if not os.path.exists(os.path.join(self.model_path, filename)) or filename is None: diff --git a/extensions-builtin/SwinIR/scripts/swinir_model.py b/extensions-builtin/SwinIR/scripts/swinir_model.py index 1c7bf325..a5b0e2eb 100644 --- a/extensions-builtin/SwinIR/scripts/swinir_model.py +++ b/extensions-builtin/SwinIR/scripts/swinir_model.py @@ -3,7 +3,6 @@ import os import numpy as np import torch from PIL import Image -from basicsr.utils.download_util import load_file_from_url from tqdm import tqdm from modules import modelloader, devices, script_callbacks, shared @@ -50,8 +49,11 @@ class UpscalerSwinIR(Upscaler): def load_model(self, path, scale=4): if "http" in path: - dl_name = "%s%s" % (self.model_name.replace(" ", "_"), ".pth") - filename = load_file_from_url(url=path, model_dir=self.model_download_path, file_name=dl_name, progress=True) + filename = modelloader.load_file_from_url( + url=path, + model_dir=self.model_download_path, + file_name=f"{self.model_name.replace(' ', '_')}.pth", + ) else: filename = path if filename is None or not os.path.exists(filename): diff --git a/modules/esrgan_model.py b/modules/esrgan_model.py index 2fced999..f1a98c07 100644 --- a/modules/esrgan_model.py +++ b/modules/esrgan_model.py @@ -3,7 +3,6 @@ import os import numpy as np import torch from PIL import Image -from basicsr.utils.download_util import load_file_from_url import modules.esrgan_model_arch as arch from modules import modelloader, images, devices @@ -152,11 +151,10 @@ class UpscalerESRGAN(Upscaler): def load_model(self, path: str): if "http" in path: - filename = load_file_from_url( + filename = modelloader.load_file_from_url( url=self.model_url, model_dir=self.model_download_path, file_name=f"{self.model_name}.pth", - progress=True, ) else: filename = path diff --git a/modules/modelloader.py b/modules/modelloader.py index be23071a..a69c8a4f 100644 --- a/modules/modelloader.py +++ b/modules/modelloader.py @@ -1,3 +1,5 @@ +from __future__ import annotations + import os import shutil import importlib @@ -8,6 +10,29 @@ from modules.upscaler import Upscaler, UpscalerLanczos, UpscalerNearest, Upscale from modules.paths import script_path, models_path +def load_file_from_url( + url: str, + *, + model_dir: str, + progress: bool = True, + file_name: str | None = None, +) -> str: + """Download a file from `url` into `model_dir`, using the file present if possible. + + Returns the path to the downloaded file. + """ + os.makedirs(model_dir, exist_ok=True) + if not file_name: + parts = urlparse(url) + file_name = os.path.basename(parts.path) + cached_file = os.path.abspath(os.path.join(model_dir, file_name)) + if not os.path.exists(cached_file): + print(f'Downloading: "{url}" to {cached_file}\n') + from torch.hub import download_url_to_file + download_url_to_file(url, cached_file, progress=progress) + return cached_file + + def load_models(model_path: str, model_url: str = None, command_path: str = None, ext_filter=None, download_name=None, ext_blacklist=None) -> list: """ A one-and done loader to try finding the desired models in specified directories. @@ -46,9 +71,7 @@ def load_models(model_path: str, model_url: str = None, command_path: str = None if model_url is not None and len(output) == 0: if download_name is not None: - from basicsr.utils.download_util import load_file_from_url - dl = load_file_from_url(model_url, places[0], True, download_name) - output.append(dl) + output.append(load_file_from_url(model_url, model_dir=places[0], file_name=download_name)) else: output.append(model_url) diff --git a/modules/realesrgan_model.py b/modules/realesrgan_model.py index 2d27b321..0d9c2e48 100644 --- a/modules/realesrgan_model.py +++ b/modules/realesrgan_model.py @@ -2,7 +2,6 @@ import os import numpy as np from PIL import Image -from basicsr.utils.download_util import load_file_from_url from realesrgan import RealESRGANer from modules.upscaler import Upscaler, UpscalerData @@ -10,6 +9,7 @@ from modules.shared import cmd_opts, opts from modules import modelloader, errors + class UpscalerRealESRGAN(Upscaler): def __init__(self, path): self.name = "RealESRGAN" @@ -71,7 +71,7 @@ class UpscalerRealESRGAN(Upscaler): return None if info.local_data_path.startswith("http"): - info.local_data_path = load_file_from_url(url=info.data_path, model_dir=self.model_download_path, progress=True) + info.local_data_path = modelloader.load_file_from_url(info.data_path, model_dir=self.model_download_path) return info except Exception: -- cgit v1.2.3 From 0afbc0c2355ead3a0ce7149a6d678f1f2e2fbfee Mon Sep 17 00:00:00 2001 From: Aarni Koskela Date: Mon, 29 May 2023 09:41:36 +0300 Subject: Fix up `if "http" in ...:` to be more sensible startswiths --- extensions-builtin/ScuNET/scripts/scunet_model.py | 4 ++-- extensions-builtin/SwinIR/scripts/swinir_model.py | 4 ++-- modules/esrgan_model.py | 4 ++-- modules/gfpgan_model.py | 2 +- modules/modelloader.py | 2 +- 5 files changed, 8 insertions(+), 8 deletions(-) (limited to 'extensions-builtin/ScuNET') diff --git a/extensions-builtin/ScuNET/scripts/scunet_model.py b/extensions-builtin/ScuNET/scripts/scunet_model.py index 2785b551..64f50829 100644 --- a/extensions-builtin/ScuNET/scripts/scunet_model.py +++ b/extensions-builtin/ScuNET/scripts/scunet_model.py @@ -27,7 +27,7 @@ class UpscalerScuNET(modules.upscaler.Upscaler): scalers = [] add_model2 = True for file in model_paths: - if "http" in file: + if file.startswith("http"): name = self.model_name else: name = modelloader.friendly_name(file) @@ -118,7 +118,7 @@ class UpscalerScuNET(modules.upscaler.Upscaler): def load_model(self, path: str): device = devices.get_device_for('scunet') - if "http" in path: + if path.startswith("http"): filename = load_file_from_url(self.model_url, model_dir=self.model_download_path, file_name=f"{self.name}.pth") else: filename = path diff --git a/extensions-builtin/SwinIR/scripts/swinir_model.py b/extensions-builtin/SwinIR/scripts/swinir_model.py index a5b0e2eb..4551761d 100644 --- a/extensions-builtin/SwinIR/scripts/swinir_model.py +++ b/extensions-builtin/SwinIR/scripts/swinir_model.py @@ -27,7 +27,7 @@ class UpscalerSwinIR(Upscaler): scalers = [] model_files = self.find_models(ext_filter=[".pt", ".pth"]) for model in model_files: - if "http" in model: + if model.startswith("http"): name = self.model_name else: name = modelloader.friendly_name(model) @@ -48,7 +48,7 @@ class UpscalerSwinIR(Upscaler): return img def load_model(self, path, scale=4): - if "http" in path: + if path.startswith("http"): filename = modelloader.load_file_from_url( url=path, model_dir=self.model_download_path, diff --git a/modules/esrgan_model.py b/modules/esrgan_model.py index f1a98c07..0666a2c2 100644 --- a/modules/esrgan_model.py +++ b/modules/esrgan_model.py @@ -133,7 +133,7 @@ class UpscalerESRGAN(Upscaler): scaler_data = UpscalerData(self.model_name, self.model_url, self, 4) scalers.append(scaler_data) for file in model_paths: - if "http" in file: + if file.startswith("http"): name = self.model_name else: name = modelloader.friendly_name(file) @@ -150,7 +150,7 @@ class UpscalerESRGAN(Upscaler): return img def load_model(self, path: str): - if "http" in path: + if path.startswith("http"): filename = modelloader.load_file_from_url( url=self.model_url, model_dir=self.model_download_path, diff --git a/modules/gfpgan_model.py b/modules/gfpgan_model.py index e239a09d..804fb53d 100644 --- a/modules/gfpgan_model.py +++ b/modules/gfpgan_model.py @@ -25,7 +25,7 @@ def gfpgann(): return None models = modelloader.load_models(model_path, model_url, user_path, ext_filter="GFPGAN") - if len(models) == 1 and "http" in models[0]: + if len(models) == 1 and models[0].startswith("http"): model_file = models[0] elif len(models) != 0: latest_file = max(models, key=os.path.getctime) diff --git a/modules/modelloader.py b/modules/modelloader.py index a69c8a4f..b2f0bb71 100644 --- a/modules/modelloader.py +++ b/modules/modelloader.py @@ -82,7 +82,7 @@ def load_models(model_path: str, model_url: str = None, command_path: str = None def friendly_name(file: str): - if "http" in file: + if file.startswith("http"): file = urlparse(file).path file = os.path.basename(file) -- cgit v1.2.3 From e3a973a68df3cfe13039dae33d19cf2c02a741e0 Mon Sep 17 00:00:00 2001 From: Aarni Koskela Date: Mon, 29 May 2023 09:45:07 +0300 Subject: Add TODO comments to sus model loads --- extensions-builtin/ScuNET/scripts/scunet_model.py | 1 + modules/esrgan_model.py | 1 + 2 files changed, 2 insertions(+) (limited to 'extensions-builtin/ScuNET') diff --git a/extensions-builtin/ScuNET/scripts/scunet_model.py b/extensions-builtin/ScuNET/scripts/scunet_model.py index 64f50829..da74a829 100644 --- a/extensions-builtin/ScuNET/scripts/scunet_model.py +++ b/extensions-builtin/ScuNET/scripts/scunet_model.py @@ -119,6 +119,7 @@ class UpscalerScuNET(modules.upscaler.Upscaler): def load_model(self, path: str): device = devices.get_device_for('scunet') if path.startswith("http"): + # TODO: this doesn't use `path` at all? filename = load_file_from_url(self.model_url, model_dir=self.model_download_path, file_name=f"{self.name}.pth") else: filename = path diff --git a/modules/esrgan_model.py b/modules/esrgan_model.py index 0666a2c2..a20e8d91 100644 --- a/modules/esrgan_model.py +++ b/modules/esrgan_model.py @@ -151,6 +151,7 @@ class UpscalerESRGAN(Upscaler): def load_model(self, path: str): if path.startswith("http"): + # TODO: this doesn't use `path` at all? filename = modelloader.load_file_from_url( url=self.model_url, model_dir=self.model_download_path, -- cgit v1.2.3 From bf67a5dcf44c3dbd88d1913478d4e02477915f33 Mon Sep 17 00:00:00 2001 From: Aarni Koskela Date: Mon, 29 May 2023 10:38:51 +0300 Subject: Upscaler.load_model: don't return None, just use exceptions --- extensions-builtin/LDSR/scripts/ldsr_model.py | 13 +++----- extensions-builtin/ScuNET/scripts/scunet_model.py | 16 ++++----- extensions-builtin/SwinIR/scripts/swinir_model.py | 40 +++++++++++------------ modules/esrgan_model.py | 14 ++++---- modules/realesrgan_model.py | 33 +++++++++---------- 5 files changed, 52 insertions(+), 64 deletions(-) (limited to 'extensions-builtin/ScuNET') diff --git a/extensions-builtin/LDSR/scripts/ldsr_model.py b/extensions-builtin/LDSR/scripts/ldsr_model.py index bf9b6de2..bd78dece 100644 --- a/extensions-builtin/LDSR/scripts/ldsr_model.py +++ b/extensions-builtin/LDSR/scripts/ldsr_model.py @@ -46,16 +46,13 @@ class UpscalerLDSR(Upscaler): yaml = local_yaml_path or load_file_from_url(self.yaml_url, model_dir=self.model_download_path, file_name="project.yaml") - try: - return LDSR(model, yaml) - except Exception: - errors.report("Error importing LDSR", exc_info=True) - return None + return LDSR(model, yaml) def do_upscale(self, img, path): - ldsr = self.load_model(path) - if ldsr is None: - print("NO LDSR!") + try: + ldsr = self.load_model(path) + except Exception: + errors.report(f"Failed loading LDSR model {path}", exc_info=True) return img ddim_steps = shared.opts.ldsr_steps return ldsr.super_resolution(img, ddim_steps, self.scale) diff --git a/extensions-builtin/ScuNET/scripts/scunet_model.py b/extensions-builtin/ScuNET/scripts/scunet_model.py index da74a829..ffef26b2 100644 --- a/extensions-builtin/ScuNET/scripts/scunet_model.py +++ b/extensions-builtin/ScuNET/scripts/scunet_model.py @@ -1,4 +1,3 @@ -import os.path import sys import PIL.Image @@ -8,7 +7,7 @@ from tqdm import tqdm import modules.upscaler from modules import devices, modelloader, script_callbacks, errors -from scunet_model_arch import SCUNet as net +from scunet_model_arch import SCUNet from modules.modelloader import load_file_from_url from modules.shared import opts @@ -88,9 +87,10 @@ class UpscalerScuNET(modules.upscaler.Upscaler): torch.cuda.empty_cache() - model = self.load_model(selected_file) - if model is None: - print(f"ScuNET: Unable to load model from {selected_file}", file=sys.stderr) + try: + model = self.load_model(selected_file) + except Exception as e: + print(f"ScuNET: Unable to load model from {selected_file}: {e}", file=sys.stderr) return img device = devices.get_device_for('scunet') @@ -123,11 +123,7 @@ class UpscalerScuNET(modules.upscaler.Upscaler): filename = load_file_from_url(self.model_url, model_dir=self.model_download_path, file_name=f"{self.name}.pth") else: filename = path - if not os.path.exists(os.path.join(self.model_path, filename)) or filename is None: - print(f"ScuNET: Unable to load model from {filename}", file=sys.stderr) - return None - - model = net(in_nc=3, config=[4, 4, 4, 4, 4, 4, 4], dim=64) + model = SCUNet(in_nc=3, config=[4, 4, 4, 4, 4, 4, 4], dim=64) model.load_state_dict(torch.load(filename), strict=True) model.eval() for _, v in model.named_parameters(): diff --git a/extensions-builtin/SwinIR/scripts/swinir_model.py b/extensions-builtin/SwinIR/scripts/swinir_model.py index 4551761d..3ce622d9 100644 --- a/extensions-builtin/SwinIR/scripts/swinir_model.py +++ b/extensions-builtin/SwinIR/scripts/swinir_model.py @@ -1,4 +1,4 @@ -import os +import sys import numpy as np import torch @@ -7,8 +7,8 @@ from tqdm import tqdm from modules import modelloader, devices, script_callbacks, shared from modules.shared import opts, state -from swinir_model_arch import SwinIR as net -from swinir_model_arch_v2 import Swin2SR as net2 +from swinir_model_arch import SwinIR +from swinir_model_arch_v2 import Swin2SR from modules.upscaler import Upscaler, UpscalerData @@ -36,8 +36,10 @@ class UpscalerSwinIR(Upscaler): self.scalers = scalers def do_upscale(self, img, model_file): - model = self.load_model(model_file) - if model is None: + try: + model = self.load_model(model_file) + except Exception as e: + print(f"Failed loading SwinIR model {model_file}: {e}", file=sys.stderr) return img model = model.to(device_swinir, dtype=devices.dtype) img = upscale(img, model) @@ -56,25 +58,23 @@ class UpscalerSwinIR(Upscaler): ) else: filename = path - if filename is None or not os.path.exists(filename): - return None if filename.endswith(".v2.pth"): - model = net2( - upscale=scale, - in_chans=3, - img_size=64, - window_size=8, - img_range=1.0, - depths=[6, 6, 6, 6, 6, 6], - embed_dim=180, - num_heads=[6, 6, 6, 6, 6, 6], - mlp_ratio=2, - upsampler="nearest+conv", - resi_connection="1conv", + model = Swin2SR( + upscale=scale, + in_chans=3, + img_size=64, + window_size=8, + img_range=1.0, + depths=[6, 6, 6, 6, 6, 6], + embed_dim=180, + num_heads=[6, 6, 6, 6, 6, 6], + mlp_ratio=2, + upsampler="nearest+conv", + resi_connection="1conv", ) params = None else: - model = net( + model = SwinIR( upscale=scale, in_chans=3, img_size=64, diff --git a/modules/esrgan_model.py b/modules/esrgan_model.py index a20e8d91..02a1727d 100644 --- a/modules/esrgan_model.py +++ b/modules/esrgan_model.py @@ -1,4 +1,4 @@ -import os +import sys import numpy as np import torch @@ -6,9 +6,8 @@ from PIL import Image import modules.esrgan_model_arch as arch from modules import modelloader, images, devices -from modules.upscaler import Upscaler, UpscalerData from modules.shared import opts - +from modules.upscaler import Upscaler, UpscalerData def mod2normal(state_dict): @@ -142,8 +141,10 @@ class UpscalerESRGAN(Upscaler): self.scalers.append(scaler_data) def do_upscale(self, img, selected_model): - model = self.load_model(selected_model) - if model is None: + try: + model = self.load_model(selected_model) + except Exception as e: + print(f"Unable to load ESRGAN model {selected_model}: {e}", file=sys.stderr) return img model.to(devices.device_esrgan) img = esrgan_upscale(model, img) @@ -159,9 +160,6 @@ class UpscalerESRGAN(Upscaler): ) else: filename = path - if not os.path.exists(filename) or filename is None: - print(f"Unable to load {self.model_path} from {filename}") - return None state_dict = torch.load(filename, map_location='cpu' if devices.device_esrgan.type == 'mps' else None) diff --git a/modules/realesrgan_model.py b/modules/realesrgan_model.py index 0d9c2e48..0700b853 100644 --- a/modules/realesrgan_model.py +++ b/modules/realesrgan_model.py @@ -9,7 +9,6 @@ from modules.shared import cmd_opts, opts from modules import modelloader, errors - class UpscalerRealESRGAN(Upscaler): def __init__(self, path): self.name = "RealESRGAN" @@ -43,9 +42,10 @@ class UpscalerRealESRGAN(Upscaler): if not self.enable: return img - info = self.load_model(path) - if not os.path.exists(info.local_data_path): - print(f"Unable to load RealESRGAN model: {info.name}") + try: + info = self.load_model(path) + except Exception: + errors.report(f"Unable to load RealESRGAN model {path}", exc_info=True) return img upsampler = RealESRGANer( @@ -63,20 +63,17 @@ class UpscalerRealESRGAN(Upscaler): return image def load_model(self, path): - try: - info = next(iter([scaler for scaler in self.scalers if scaler.data_path == path]), None) - - if info is None: - print(f"Unable to find model info: {path}") - return None - - if info.local_data_path.startswith("http"): - info.local_data_path = modelloader.load_file_from_url(info.data_path, model_dir=self.model_download_path) - - return info - except Exception: - errors.report("Error making Real-ESRGAN models list", exc_info=True) - return None + for scaler in self.scalers: + if scaler.data_path == path: + if scaler.local_data_path.startswith("http"): + scaler.local_data_path = modelloader.load_file_from_url( + scaler.data_path, + model_dir=self.model_download_path, + ) + if not os.path.exists(scaler.local_data_path): + raise FileNotFoundError(f"RealESRGAN data missing: {scaler.local_data_path}") + return scaler + raise ValueError(f"Unable to find model info: {path}") def load_models(self, _): return get_realesrgan_models(self) -- cgit v1.2.3