From 2aaee73633ef7a6d12561859ca2d58d0e10cf297 Mon Sep 17 00:00:00 2001 From: invincibledude <> Date: Sun, 22 Jan 2023 16:00:35 +0300 Subject: Gen params paste improvement --- modules/generation_parameters_copypaste.py | 3 +++ 1 file changed, 3 insertions(+) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 46e12dc6..b8212abd 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -253,6 +253,9 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model done_with_prompt = True line = line[16:].strip() + if line.startswith("Hires prompt:"): + res["Hires prompt"] = line[1:][:-1] + if done_with_prompt: negative_prompt += ("" if negative_prompt == "" else "\n") + line else: -- cgit v1.2.3 From 1fa777c1d77556d116d39144c47715f6b1325538 Mon Sep 17 00:00:00 2001 From: invincibledude <> Date: Sun, 22 Jan 2023 16:03:42 +0300 Subject: Gen params paste improvement --- modules/generation_parameters_copypaste.py | 3 +++ 1 file changed, 3 insertions(+) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index b8212abd..67e76e30 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -256,6 +256,9 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model if line.startswith("Hires prompt:"): res["Hires prompt"] = line[1:][:-1] + if line.startswith("Hires negative prompt:"): + res["Hires negative prompt"] = line[1:][:-1] + if done_with_prompt: negative_prompt += ("" if negative_prompt == "" else "\n") + line else: -- cgit v1.2.3 From d261bec1ec5a185b6e57f73e8589b07d5d5bc4e8 Mon Sep 17 00:00:00 2001 From: invincibledude <> Date: Sun, 22 Jan 2023 16:14:28 +0300 Subject: Gen params paste improvement --- modules/generation_parameters_copypaste.py | 11 ++++------- 1 file changed, 4 insertions(+), 7 deletions(-) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 67e76e30..155ab350 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -252,13 +252,6 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model if line.startswith("Negative prompt:"): done_with_prompt = True line = line[16:].strip() - - if line.startswith("Hires prompt:"): - res["Hires prompt"] = line[1:][:-1] - - if line.startswith("Hires negative prompt:"): - res["Hires negative prompt"] = line[1:][:-1] - if done_with_prompt: negative_prompt += ("" if negative_prompt == "" else "\n") + line else: @@ -274,6 +267,10 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model res[k+"-2"] = m.group(2) else: res[k] = v + if k.startswith("Hires prompt:"): + res["Hires prompt"] = v[1:][:-1] + elif k.startswith("Hires negative prompt:"): + res["Hires negative prompt"] = v[1:][:-1] # Missing CLIP skip means it was set to 1 (the default) if "Clip skip" not in res: -- cgit v1.2.3 From fccc39834a61509a2fb60196229cbea20539aabb Mon Sep 17 00:00:00 2001 From: invincibledude <> Date: Sun, 22 Jan 2023 16:17:55 +0300 Subject: Gen params paste improvement --- modules/generation_parameters_copypaste.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 155ab350..44c8273f 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -267,9 +267,10 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model res[k+"-2"] = m.group(2) else: res[k] = v - if k.startswith("Hires prompt:"): + + if k.startswith("Hires prompt"): res["Hires prompt"] = v[1:][:-1] - elif k.startswith("Hires negative prompt:"): + elif k.startswith("Hires negative prompt"): res["Hires negative prompt"] = v[1:][:-1] # Missing CLIP skip means it was set to 1 (the default) -- cgit v1.2.3 From 3bc8ee998db5f461b8011a72e6f167012ccb8bc1 Mon Sep 17 00:00:00 2001 From: invincibledude <> Date: Sun, 22 Jan 2023 16:35:42 +0300 Subject: Gen params paste improvement --- modules/generation_parameters_copypaste.py | 4 ++-- modules/processing.py | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 44c8273f..98098cc8 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -269,9 +269,9 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model res[k] = v if k.startswith("Hires prompt"): - res["Hires prompt"] = v[1:][:-1] + res["Hires prompt"] = v[1:][:-1].replace(';', ',') elif k.startswith("Hires negative prompt"): - res["Hires negative prompt"] = v[1:][:-1] + res["Hires negative prompt"] = v[1:][:-1].replace(';', ',') # Missing CLIP skip means it was set to 1 (the default) if "Clip skip" not in res: diff --git a/modules/processing.py b/modules/processing.py index c56717f6..01c1b53c 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -790,8 +790,8 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): if self.hr_resize_x == 0 and self.hr_resize_y == 0: self.extra_generation_params["Hires upscale"] = self.hr_scale self.extra_generation_params["Hires sampler"] = self.hr_sampler - self.extra_generation_params["Hires prompt"] = f'"{self.hr_prompt}"' - self.extra_generation_params["Hires negative prompt"] = f'"{self.hr_negative_prompt}"' + self.extra_generation_params["Hires prompt"] = f'({self.hr_prompt.replace(",", ";")})' + self.extra_generation_params["Hires negative prompt"] = f'({self.hr_negative_prompt.replace(",", ";")})' self.hr_upscale_to_x = int(self.width * self.hr_scale) self.hr_upscale_to_y = int(self.height * self.hr_scale) else: -- cgit v1.2.3 From 1c1106260300ca3956d9619875e28278b148adab Mon Sep 17 00:00:00 2001 From: papuSpartan Date: Mon, 10 Apr 2023 03:37:15 -0500 Subject: add token merging options to infotext when necessary. Bump tomesd version --- modules/generation_parameters_copypaste.py | 37 ++++++++++++++++++++++++++++++ modules/processing.py | 22 ++++++++++++++---- modules/shared.py | 2 +- requirements_versions.txt | 2 +- 4 files changed, 57 insertions(+), 6 deletions(-) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 6df76858..a7ede534 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -282,6 +282,32 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model res["Hires resize-1"] = 0 res["Hires resize-2"] = 0 + # Infer additional override settings for token merging + print("inferring settings for tomesd") + token_merging_ratio = res.get("Token merging ratio", None) + token_merging_ratio_hr = res.get("Token merging ratio hr", None) + + if token_merging_ratio is not None or token_merging_ratio_hr is not None: + res["Token merging"] = 'True' + + if token_merging_ratio is None: + res["Token merging hr only"] = 'True' + else: + res["Token merging hr only"] = 'False' + + if res.get("Token merging random", None) is None: + res["Token merging random"] = 'False' + if res.get("Token merging merge attention", None) is None: + res["Token merging merge attention"] = 'True' + if res.get("Token merging merge cross attention", None) is None: + res["Token merging merge cross attention"] = 'False' + if res.get("Token merging merge mlp", None) is None: + res["Token merging merge mlp"] = 'False' + if res.get("Token merging stride x", None) is None: + res["Token merging stride x"] = '2' + if res.get("Token merging stride y", None) is None: + res["Token merging stride y"] = '2' + restore_old_hires_fix_params(res) return res @@ -304,6 +330,17 @@ infotext_to_setting_name_mapping = [ ('UniPC skip type', 'uni_pc_skip_type'), ('UniPC order', 'uni_pc_order'), ('UniPC lower order final', 'uni_pc_lower_order_final'), + ('Token merging', 'token_merging'), + ('Token merging ratio', 'token_merging_ratio'), + ('Token merging hr only', 'token_merging_hr_only'), + ('Token merging ratio hr', 'token_merging_ratio_hr'), + ('Token merging random', 'token_merging_random'), + ('Token merging merge attention', 'token_merging_merge_attention'), + ('Token merging merge cross attention', 'token_merging_merge_cross_attention'), + ('Token merging merge mlp', 'token_merging_merge_mlp'), + ('Token merging maximum downsampling', 'token_merging_maximum_downsampling'), + ('Token merging stride x', 'token_merging_stride_x'), + ('Token merging stride y', 'token_merging_stride_y') ] diff --git a/modules/processing.py b/modules/processing.py index 670a7a28..95058d0b 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -31,6 +31,12 @@ from einops import repeat, rearrange from blendmodes.blend import blendLayers, BlendType import tomesd +# add a logger for the processing module +logger = logging.getLogger(__name__) +# manually set output level here since there is no option to do so yet through launch options +# logging.basicConfig(level=logging.DEBUG, format='%(asctime)s %(levelname)s %(name)s %(message)s') + + # some of those options should not be changed at all because they would break the model, so I removed them from options. opt_C = 4 opt_f = 8 @@ -477,6 +483,14 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter "Conditional mask weight": getattr(p, "inpainting_mask_weight", shared.opts.inpainting_mask_weight) if p.is_using_inpainting_conditioning else None, "Clip skip": None if clip_skip <= 1 else clip_skip, "ENSD": None if opts.eta_noise_seed_delta == 0 else opts.eta_noise_seed_delta, + "Token merging ratio": None if not (opts.token_merging or cmd_opts.token_merging) or opts.token_merging_hr_only else opts.token_merging_ratio, + "Token merging ratio hr": None if not (opts.token_merging or cmd_opts.token_merging) else opts.token_merging_ratio_hr, + "Token merging random": None if opts.token_merging_random is False else opts.token_merging_random, + "Token merging merge attention": None if opts.token_merging_merge_attention is True else opts.token_merging_merge_attention, + "Token merging merge cross attention": None if opts.token_merging_merge_cross_attention is False else opts.token_merging_merge_cross_attention, + "Token merging merge mlp": None if opts.token_merging_merge_mlp is False else opts.token_merging_merge_mlp, + "Token merging stride x": None if opts.token_merging_stride_x == 2 else opts.token_merging_stride_x, + "Token merging stride y": None if opts.token_merging_stride_y == 2 else opts.token_merging_stride_y } generation_params.update(p.extra_generation_params) @@ -502,16 +516,16 @@ def process_images(p: StableDiffusionProcessing) -> Processed: sd_vae.reload_vae_weights() if (opts.token_merging or cmd_opts.token_merging) and not opts.token_merging_hr_only: - print("\nApplying token merging\n") sd_models.apply_token_merging(sd_model=p.sd_model, hr=False) + logger.debug('Token merging applied') res = process_images_inner(p) finally: # undo model optimizations made by tomesd if opts.token_merging or cmd_opts.token_merging: - print('\nRemoving token merging model optimizations\n') tomesd.remove_patch(p.sd_model) + logger.debug('Token merging model optimizations removed') # restore opts to original state if p.override_settings_restore_afterwards: @@ -954,11 +968,11 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): # case where user wants to use separate merge ratios if not opts.token_merging_hr_only: # clean patch done by first pass. (clobbering the first patch might be fine? this might be excessive) - print('Temporarily reverting token merging optimizations in preparation for next pass') tomesd.remove_patch(self.sd_model) + logger.debug('Temporarily removed token merging optimizations in preparation for next pass') - print("\nApplying token merging for high-res pass\n") sd_models.apply_token_merging(sd_model=self.sd_model, hr=True) + logger.debug('Applied token merging for high-res pass') samples = self.sampler.sample_img2img(self, samples, noise, conditioning, unconditional_conditioning, steps=self.hr_second_pass_steps or self.steps, image_conditioning=image_conditioning) diff --git a/modules/shared.py b/modules/shared.py index 568acdc4..d9db7317 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -446,7 +446,7 @@ options_templates.update(options_section(('token_merging', 'Token Merging'), { ), # More advanced/niche settings: "token_merging_random": OptionInfo( - True, "Use random perturbations - Disabling might help with certain samplers", + False, "Use random perturbations - Can improve outputs for certain samplers. For others, it may cause visaul artifacting.", gr.Checkbox ), "token_merging_merge_attention": OptionInfo( diff --git a/requirements_versions.txt b/requirements_versions.txt index 03522715..f972f975 100644 --- a/requirements_versions.txt +++ b/requirements_versions.txt @@ -28,4 +28,4 @@ torchsde==0.2.5 safetensors==0.3.0 httpcore<=0.15 fastapi==0.94.0 -tomesd>=0.1.1 \ No newline at end of file +tomesd>=0.1.2 \ No newline at end of file -- cgit v1.2.3 From a9902ca33119d6fae0a3623424bfc7ab86f2095a Mon Sep 17 00:00:00 2001 From: papuSpartan <30642826+papuSpartan@users.noreply.github.com> Date: Mon, 10 Apr 2023 04:03:01 -0500 Subject: Update generation_parameters_copypaste.py --- modules/generation_parameters_copypaste.py | 1 - 1 file changed, 1 deletion(-) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index a7ede534..ba2ca5ed 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -283,7 +283,6 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model res["Hires resize-2"] = 0 # Infer additional override settings for token merging - print("inferring settings for tomesd") token_merging_ratio = res.get("Token merging ratio", None) token_merging_ratio_hr = res.get("Token merging ratio hr", None) -- cgit v1.2.3 From e960781511eb175943be09b314ac2be46b6fc684 Mon Sep 17 00:00:00 2001 From: papuSpartan <30642826+papuSpartan@users.noreply.github.com> Date: Wed, 3 May 2023 13:12:43 -0500 Subject: fix maximum downsampling option --- modules/generation_parameters_copypaste.py | 4 +++- modules/processing.py | 1 + modules/shared.py | 5 +---- 3 files changed, 5 insertions(+), 5 deletions(-) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 34c1b860..83382e93 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -306,6 +306,8 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model res["Token merging stride x"] = '2' if res.get("Token merging stride y", None) is None: res["Token merging stride y"] = '2' + if res.get("Token merging maximum down sampling", None) is None: + res["Token merging maximum down sampling"] = '1' restore_old_hires_fix_params(res) @@ -341,7 +343,7 @@ infotext_to_setting_name_mapping = [ ('Token merging merge attention', 'token_merging_merge_attention'), ('Token merging merge cross attention', 'token_merging_merge_cross_attention'), ('Token merging merge mlp', 'token_merging_merge_mlp'), - ('Token merging maximum downsampling', 'token_merging_maximum_downsampling'), + ('Token merging maximum down sampling', 'token_merging_maximum_down_sampling'), ('Token merging stride x', 'token_merging_stride_x'), ('Token merging stride y', 'token_merging_stride_y'), ('RNG', 'randn_source'), diff --git a/modules/processing.py b/modules/processing.py index d5d1da5a..6807a301 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -495,6 +495,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter "Token merging merge mlp": None if opts.token_merging_merge_mlp is False else opts.token_merging_merge_mlp, "Token merging stride x": None if opts.token_merging_stride_x == 2 else opts.token_merging_stride_x, "Token merging stride y": None if opts.token_merging_stride_y == 2 else opts.token_merging_stride_y, + "Token merging maximum down sampling": None if opts.token_merging_maximum_down_sampling == 1 else opts.token_merging_maximum_down_sampling, "Init image hash": getattr(p, 'init_img_hash', None), "RNG": opts.randn_source if opts.randn_source != "GPU" else None, "NGMS": None if p.s_min_uncond == 0 else p.s_min_uncond, diff --git a/modules/shared.py b/modules/shared.py index 7b81ffc9..a7a72dd5 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -488,10 +488,7 @@ options_templates.update(options_section(('token_merging', 'Token Merging'), { False, "Merge mlp", gr.Checkbox ), - "token_merging_maximum_down_sampling": OptionInfo( - 1, "Maximum down sampling", - gr.Dropdown, lambda: {"choices": ["1", "2", "4", "8"]} - ), + "token_merging_maximum_down_sampling": OptionInfo(1, "Maximum down sampling", gr.Radio, lambda: {"choices": ['1', '2', '4', '8']}), "token_merging_stride_x": OptionInfo( 2, "Stride - X", gr.Slider, {"minimum": 2, "maximum": 8, "step": 2} -- 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 'modules/generation_parameters_copypaste.py') 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 550256db1ce18778a9d56ff343d844c61b9f9b83 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Wed, 10 May 2023 11:19:16 +0300 Subject: ruff manual fixes --- extensions-builtin/LDSR/sd_hijack_autoencoder.py | 10 +++++----- extensions-builtin/LDSR/sd_hijack_ddpm_v1.py | 14 +++++++------- extensions-builtin/SwinIR/swinir_model_arch.py | 6 +++++- extensions-builtin/SwinIR/swinir_model_arch_v2.py | 11 +++++++++-- modules/api/api.py | 18 ++++++++++++------ modules/codeformer/codeformer_arch.py | 7 +++++-- modules/codeformer/vqgan_arch.py | 4 ++-- modules/generation_parameters_copypaste.py | 4 ++-- modules/models/diffusion/ddpm_edit.py | 14 ++++++++------ modules/models/diffusion/uni_pc/uni_pc.py | 7 +++++-- modules/safe.py | 2 +- modules/sd_samplers_compvis.py | 2 +- modules/textual_inversion/image_embedding.py | 2 +- modules/textual_inversion/learn_schedule.py | 4 ++-- pyproject.toml | 5 ++++- 15 files changed, 69 insertions(+), 41 deletions(-) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/extensions-builtin/LDSR/sd_hijack_autoencoder.py b/extensions-builtin/LDSR/sd_hijack_autoencoder.py index f457ca93..8cc82d54 100644 --- a/extensions-builtin/LDSR/sd_hijack_autoencoder.py +++ b/extensions-builtin/LDSR/sd_hijack_autoencoder.py @@ -24,7 +24,7 @@ class VQModel(pl.LightningModule): n_embed, embed_dim, ckpt_path=None, - ignore_keys=[], + ignore_keys=None, image_key="image", colorize_nlabels=None, monitor=None, @@ -62,7 +62,7 @@ class VQModel(pl.LightningModule): print(f"Keeping EMAs of {len(list(self.model_ema.buffers()))}.") if ckpt_path is not None: - self.init_from_ckpt(ckpt_path, ignore_keys=ignore_keys) + self.init_from_ckpt(ckpt_path, ignore_keys=ignore_keys or []) self.scheduler_config = scheduler_config self.lr_g_factor = lr_g_factor @@ -81,11 +81,11 @@ class VQModel(pl.LightningModule): if context is not None: print(f"{context}: Restored training weights") - def init_from_ckpt(self, path, ignore_keys=list()): + def init_from_ckpt(self, path, ignore_keys=None): sd = torch.load(path, map_location="cpu")["state_dict"] keys = list(sd.keys()) for k in keys: - for ik in ignore_keys: + for ik in ignore_keys or []: if k.startswith(ik): print("Deleting key {} from state_dict.".format(k)) del sd[k] @@ -270,7 +270,7 @@ class VQModel(pl.LightningModule): class VQModelInterface(VQModel): def __init__(self, embed_dim, *args, **kwargs): - super().__init__(embed_dim=embed_dim, *args, **kwargs) + super().__init__(*args, embed_dim=embed_dim, **kwargs) self.embed_dim = embed_dim def encode(self, x): diff --git a/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py b/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py index d8fc30e3..f16d6504 100644 --- a/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py +++ b/extensions-builtin/LDSR/sd_hijack_ddpm_v1.py @@ -48,7 +48,7 @@ class DDPMV1(pl.LightningModule): beta_schedule="linear", loss_type="l2", ckpt_path=None, - ignore_keys=[], + ignore_keys=None, load_only_unet=False, monitor="val/loss", use_ema=True, @@ -100,7 +100,7 @@ class DDPMV1(pl.LightningModule): if monitor is not None: self.monitor = monitor if ckpt_path is not None: - self.init_from_ckpt(ckpt_path, ignore_keys=ignore_keys, only_model=load_only_unet) + self.init_from_ckpt(ckpt_path, ignore_keys=ignore_keys or [], only_model=load_only_unet) self.register_schedule(given_betas=given_betas, beta_schedule=beta_schedule, timesteps=timesteps, linear_start=linear_start, linear_end=linear_end, cosine_s=cosine_s) @@ -182,13 +182,13 @@ class DDPMV1(pl.LightningModule): if context is not None: print(f"{context}: Restored training weights") - def init_from_ckpt(self, path, ignore_keys=list(), only_model=False): + def init_from_ckpt(self, path, ignore_keys=None, only_model=False): sd = torch.load(path, map_location="cpu") if "state_dict" in list(sd.keys()): sd = sd["state_dict"] keys = list(sd.keys()) for k in keys: - for ik in ignore_keys: + for ik in ignore_keys or []: if k.startswith(ik): print("Deleting key {} from state_dict.".format(k)) del sd[k] @@ -444,7 +444,7 @@ class LatentDiffusionV1(DDPMV1): conditioning_key = None ckpt_path = kwargs.pop("ckpt_path", None) ignore_keys = kwargs.pop("ignore_keys", []) - super().__init__(conditioning_key=conditioning_key, *args, **kwargs) + super().__init__(*args, conditioning_key=conditioning_key, **kwargs) self.concat_mode = concat_mode self.cond_stage_trainable = cond_stage_trainable self.cond_stage_key = cond_stage_key @@ -1418,10 +1418,10 @@ class Layout2ImgDiffusionV1(LatentDiffusionV1): # TODO: move all layout-specific hacks to this class def __init__(self, cond_stage_key, *args, **kwargs): assert cond_stage_key == 'coordinates_bbox', 'Layout2ImgDiffusion only for cond_stage_key="coordinates_bbox"' - super().__init__(cond_stage_key=cond_stage_key, *args, **kwargs) + super().__init__(*args, cond_stage_key=cond_stage_key, **kwargs) def log_images(self, batch, N=8, *args, **kwargs): - logs = super().log_images(batch=batch, N=N, *args, **kwargs) + logs = super().log_images(*args, batch=batch, N=N, **kwargs) key = 'train' if self.training else 'validation' dset = self.trainer.datamodule.datasets[key] diff --git a/extensions-builtin/SwinIR/swinir_model_arch.py b/extensions-builtin/SwinIR/swinir_model_arch.py index 863f42db..75f7bedc 100644 --- a/extensions-builtin/SwinIR/swinir_model_arch.py +++ b/extensions-builtin/SwinIR/swinir_model_arch.py @@ -644,13 +644,17 @@ class SwinIR(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], + embed_dim=96, depths=None, num_heads=None, window_size=7, mlp_ratio=4., qkv_bias=True, qk_scale=None, 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', **kwargs): super(SwinIR, self).__init__() + + depths = depths or [6, 6, 6, 6] + num_heads = num_heads or [6, 6, 6, 6] + num_in_ch = in_chans num_out_ch = in_chans num_feat = 64 diff --git a/extensions-builtin/SwinIR/swinir_model_arch_v2.py b/extensions-builtin/SwinIR/swinir_model_arch_v2.py index 0e28ae6e..d4c0b0da 100644 --- a/extensions-builtin/SwinIR/swinir_model_arch_v2.py +++ b/extensions-builtin/SwinIR/swinir_model_arch_v2.py @@ -74,9 +74,12 @@ class WindowAttention(nn.Module): """ def __init__(self, dim, window_size, num_heads, qkv_bias=True, attn_drop=0., proj_drop=0., - pretrained_window_size=[0, 0]): + pretrained_window_size=None): super().__init__() + + pretrained_window_size = pretrained_window_size or [0, 0] + self.dim = dim self.window_size = window_size # Wh, Ww self.pretrained_window_size = pretrained_window_size @@ -698,13 +701,17 @@ 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], + embed_dim=96, depths=None, num_heads=None, 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', **kwargs): super(Swin2SR, self).__init__() + + depths = depths or [6, 6, 6, 6] + num_heads = num_heads or [6, 6, 6, 6] + num_in_ch = in_chans num_out_ch = in_chans num_feat = 64 diff --git a/modules/api/api.py b/modules/api/api.py index f52d371b..9efb558e 100644 --- a/modules/api/api.py +++ b/modules/api/api.py @@ -34,14 +34,16 @@ import piexif.helper def upscaler_to_index(name: str): try: return [x.name.lower() for x in shared.sd_upscalers].index(name.lower()) - except Exception: - raise HTTPException(status_code=400, detail=f"Invalid upscaler, needs to be one of these: {' , '.join([x.name for x in shared.sd_upscalers])}") + except Exception as e: + raise HTTPException(status_code=400, detail=f"Invalid upscaler, needs to be one of these: {' , '.join([x.name for x in shared.sd_upscalers])}") from e + def script_name_to_index(name, scripts): try: return [script.title().lower() for script in scripts].index(name.lower()) - except Exception: - raise HTTPException(status_code=422, detail=f"Script '{name}' not found") + except Exception as e: + raise HTTPException(status_code=422, detail=f"Script '{name}' not found") from e + def validate_sampler_name(name): config = sd_samplers.all_samplers_map.get(name, None) @@ -50,20 +52,23 @@ def validate_sampler_name(name): return name + def setUpscalers(req: dict): reqDict = vars(req) reqDict['extras_upscaler_1'] = reqDict.pop('upscaler_1', None) reqDict['extras_upscaler_2'] = reqDict.pop('upscaler_2', None) return reqDict + def decode_base64_to_image(encoding): if encoding.startswith("data:image/"): encoding = encoding.split(";")[1].split(",")[1] try: image = Image.open(BytesIO(base64.b64decode(encoding))) return image - except Exception: - raise HTTPException(status_code=500, detail="Invalid encoded image") + except Exception as e: + raise HTTPException(status_code=500, detail="Invalid encoded image") from e + def encode_pil_to_base64(image): with io.BytesIO() as output_bytes: @@ -94,6 +99,7 @@ def encode_pil_to_base64(image): return base64.b64encode(bytes_data) + def api_middleware(app: FastAPI): rich_available = True try: diff --git a/modules/codeformer/codeformer_arch.py b/modules/codeformer/codeformer_arch.py index 00c407de..ff1c0b4b 100644 --- a/modules/codeformer/codeformer_arch.py +++ b/modules/codeformer/codeformer_arch.py @@ -161,10 +161,13 @@ class Fuse_sft_block(nn.Module): class CodeFormer(VQAutoEncoder): 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']): + connect_list=None, + fix_modules=None): super(CodeFormer, self).__init__(512, 64, [1, 2, 2, 4, 4, 8], 'nearest',2, [16], codebook_size) + connect_list = connect_list or ['32', '64', '128', '256'] + fix_modules = fix_modules or ['quantize', 'generator'] + if fix_modules is not None: for module in fix_modules: for param in getattr(self, module).parameters(): diff --git a/modules/codeformer/vqgan_arch.py b/modules/codeformer/vqgan_arch.py index 820e6b12..b24a0394 100644 --- a/modules/codeformer/vqgan_arch.py +++ b/modules/codeformer/vqgan_arch.py @@ -326,7 +326,7 @@ class Generator(nn.Module): @ARCH_REGISTRY.register() class VQAutoEncoder(nn.Module): - def __init__(self, img_size, nf, ch_mult, quantizer="nearest", res_blocks=2, attn_resolutions=[16], codebook_size=1024, emb_dim=256, + 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() @@ -337,7 +337,7 @@ class VQAutoEncoder(nn.Module): self.embed_dim = emb_dim self.ch_mult = ch_mult self.resolution = img_size - self.attn_resolutions = attn_resolutions + self.attn_resolutions = attn_resolutions or [16] self.quantizer_type = quantizer self.encoder = Encoder( self.in_channels, diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index f1c59c46..7fbbe707 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -19,14 +19,14 @@ registered_param_bindings = [] class ParamBinding: - def __init__(self, paste_button, tabname, source_text_component=None, source_image_component=None, source_tabname=None, override_settings_component=None, paste_field_names=[]): + def __init__(self, paste_button, tabname, source_text_component=None, source_image_component=None, source_tabname=None, override_settings_component=None, paste_field_names=None): self.paste_button = paste_button self.tabname = tabname self.source_text_component = source_text_component self.source_image_component = source_image_component self.source_tabname = source_tabname self.override_settings_component = override_settings_component - self.paste_field_names = paste_field_names + self.paste_field_names = paste_field_names or [] def reset(): diff --git a/modules/models/diffusion/ddpm_edit.py b/modules/models/diffusion/ddpm_edit.py index 09432117..af4dea15 100644 --- a/modules/models/diffusion/ddpm_edit.py +++ b/modules/models/diffusion/ddpm_edit.py @@ -52,7 +52,7 @@ class DDPM(pl.LightningModule): beta_schedule="linear", loss_type="l2", ckpt_path=None, - ignore_keys=[], + ignore_keys=None, load_only_unet=False, monitor="val/loss", use_ema=True, @@ -107,7 +107,7 @@ class DDPM(pl.LightningModule): print(f"Keeping EMAs of {len(list(self.model_ema.buffers()))}.") if ckpt_path is not None: - self.init_from_ckpt(ckpt_path, ignore_keys=ignore_keys, only_model=load_only_unet) + self.init_from_ckpt(ckpt_path, ignore_keys=ignore_keys or [], only_model=load_only_unet) # If initialing from EMA-only checkpoint, create EMA model after loading. if self.use_ema and not load_ema: @@ -194,7 +194,9 @@ class DDPM(pl.LightningModule): if context is not None: print(f"{context}: Restored training weights") - def init_from_ckpt(self, path, ignore_keys=list(), only_model=False): + def init_from_ckpt(self, path, ignore_keys=None, only_model=False): + ignore_keys = ignore_keys or [] + sd = torch.load(path, map_location="cpu") if "state_dict" in list(sd.keys()): sd = sd["state_dict"] @@ -473,7 +475,7 @@ class LatentDiffusion(DDPM): conditioning_key = None ckpt_path = kwargs.pop("ckpt_path", None) ignore_keys = kwargs.pop("ignore_keys", []) - super().__init__(conditioning_key=conditioning_key, *args, load_ema=load_ema, **kwargs) + super().__init__(*args, conditioning_key=conditioning_key, load_ema=load_ema, **kwargs) self.concat_mode = concat_mode self.cond_stage_trainable = cond_stage_trainable self.cond_stage_key = cond_stage_key @@ -1433,10 +1435,10 @@ class Layout2ImgDiffusion(LatentDiffusion): # TODO: move all layout-specific hacks to this class def __init__(self, cond_stage_key, *args, **kwargs): assert cond_stage_key == 'coordinates_bbox', 'Layout2ImgDiffusion only for cond_stage_key="coordinates_bbox"' - super().__init__(cond_stage_key=cond_stage_key, *args, **kwargs) + super().__init__(*args, cond_stage_key=cond_stage_key, **kwargs) def log_images(self, batch, N=8, *args, **kwargs): - logs = super().log_images(batch=batch, N=N, *args, **kwargs) + logs = super().log_images(*args, batch=batch, N=N, **kwargs) key = 'train' if self.training else 'validation' dset = self.trainer.datamodule.datasets[key] diff --git a/modules/models/diffusion/uni_pc/uni_pc.py b/modules/models/diffusion/uni_pc/uni_pc.py index a4c4ef4e..6f8ad631 100644 --- a/modules/models/diffusion/uni_pc/uni_pc.py +++ b/modules/models/diffusion/uni_pc/uni_pc.py @@ -178,13 +178,13 @@ def model_wrapper( model, noise_schedule, model_type="noise", - model_kwargs={}, + model_kwargs=None, guidance_type="uncond", #condition=None, #unconditional_condition=None, guidance_scale=1., classifier_fn=None, - classifier_kwargs={}, + classifier_kwargs=None, ): """Create a wrapper function for the noise prediction model. @@ -275,6 +275,9 @@ def model_wrapper( A noise prediction model that accepts the noised data and the continuous time as the inputs. """ + model_kwargs = model_kwargs or [] + classifier_kwargs = classifier_kwargs or [] + def get_model_input_time(t_continuous): """ Convert the continuous-time `t_continuous` (in [epsilon, T]) to the model input time. diff --git a/modules/safe.py b/modules/safe.py index e6c2f2c0..2d5b972f 100644 --- a/modules/safe.py +++ b/modules/safe.py @@ -104,7 +104,7 @@ def check_pt(filename, extra_handler): def load(filename, *args, **kwargs): - return load_with_extra(filename, extra_handler=global_extra_handler, *args, **kwargs) + return load_with_extra(filename, *args, extra_handler=global_extra_handler, **kwargs) def load_with_extra(filename, extra_handler=None, *args, **kwargs): diff --git a/modules/sd_samplers_compvis.py b/modules/sd_samplers_compvis.py index 7427648f..b1ee3be7 100644 --- a/modules/sd_samplers_compvis.py +++ b/modules/sd_samplers_compvis.py @@ -55,7 +55,7 @@ class VanillaStableDiffusionSampler: def p_sample_ddim_hook(self, x_dec, cond, ts, unconditional_conditioning, *args, **kwargs): x_dec, ts, cond, unconditional_conditioning = self.before_sample(x_dec, ts, cond, unconditional_conditioning) - res = self.orig_p_sample_ddim(x_dec, cond, ts, unconditional_conditioning=unconditional_conditioning, *args, **kwargs) + res = self.orig_p_sample_ddim(x_dec, cond, ts, *args, unconditional_conditioning=unconditional_conditioning, **kwargs) x_dec, ts, cond, unconditional_conditioning, res = self.after_sample(x_dec, ts, cond, unconditional_conditioning, res) diff --git a/modules/textual_inversion/image_embedding.py b/modules/textual_inversion/image_embedding.py index ee0e850a..d85a4888 100644 --- a/modules/textual_inversion/image_embedding.py +++ b/modules/textual_inversion/image_embedding.py @@ -17,7 +17,7 @@ class EmbeddingEncoder(json.JSONEncoder): class EmbeddingDecoder(json.JSONDecoder): def __init__(self, *args, **kwargs): - json.JSONDecoder.__init__(self, object_hook=self.object_hook, *args, **kwargs) + json.JSONDecoder.__init__(self, *args, object_hook=self.object_hook, **kwargs) def object_hook(self, d): if 'TORCHTENSOR' in d: diff --git a/modules/textual_inversion/learn_schedule.py b/modules/textual_inversion/learn_schedule.py index f63fc72f..fda58898 100644 --- a/modules/textual_inversion/learn_schedule.py +++ b/modules/textual_inversion/learn_schedule.py @@ -32,8 +32,8 @@ class LearnScheduleIterator: self.maxit += 1 return assert self.rates - except (ValueError, AssertionError): - raise Exception('Invalid learning rate schedule. It should be a number or, for example, like "0.001:100, 0.00001:1000, 1e-5:10000" to have lr of 0.001 until step 100, 0.00001 until 1000, and 1e-5 until 10000.') + except (ValueError, AssertionError) as e: + raise Exception('Invalid learning rate schedule. It should be a number or, for example, like "0.001:100, 0.00001:1000, 1e-5:10000" to have lr of 0.001 until step 100, 0.00001 until 1000, and 1e-5 until 10000.') from e def __iter__(self): diff --git a/pyproject.toml b/pyproject.toml index 2f65fd6c..346a0cde 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -24,6 +24,9 @@ ignore = [ ] - [tool.ruff.per-file-ignores] "webui.py" = ["E402"] # Module level import not at top of file + +[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 -- 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 'modules/generation_parameters_copypaste.py') 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 ac83627a31daac06f4d48b0e7db223ef807fe8e5 Mon Sep 17 00:00:00 2001 From: papuSpartan <30642826+papuSpartan@users.noreply.github.com> Date: Sat, 13 May 2023 10:23:42 -0500 Subject: heavily simplify --- modules/generation_parameters_copypaste.py | 36 ------------------------- modules/processing.py | 35 +++++++++++-------------- modules/sd_models.py | 11 +++----- modules/shared.py | 42 +++--------------------------- 4 files changed, 23 insertions(+), 101 deletions(-) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index fb56254f..a0a98bbc 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -282,33 +282,6 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model res["Hires resize-1"] = 0 res["Hires resize-2"] = 0 - # Infer additional override settings for token merging - token_merging_ratio = res.get("Token merging ratio", None) - token_merging_ratio_hr = res.get("Token merging ratio hr", None) - - if token_merging_ratio is not None or token_merging_ratio_hr is not None: - res["Token merging"] = 'True' - - if token_merging_ratio is None: - res["Token merging hr only"] = 'True' - else: - res["Token merging hr only"] = 'False' - - if res.get("Token merging random", None) is None: - res["Token merging random"] = 'False' - if res.get("Token merging merge attention", None) is None: - res["Token merging merge attention"] = 'True' - if res.get("Token merging merge cross attention", None) is None: - res["Token merging merge cross attention"] = 'False' - if res.get("Token merging merge mlp", None) is None: - res["Token merging merge mlp"] = 'False' - if res.get("Token merging stride x", None) is None: - res["Token merging stride x"] = '2' - if res.get("Token merging stride y", None) is None: - res["Token merging stride y"] = '2' - if res.get("Token merging maximum down sampling", None) is None: - res["Token merging maximum down sampling"] = '1' - restore_old_hires_fix_params(res) # Missing RNG means the default was set, which is GPU RNG @@ -335,17 +308,8 @@ infotext_to_setting_name_mapping = [ ('UniPC skip type', 'uni_pc_skip_type'), ('UniPC order', 'uni_pc_order'), ('UniPC lower order final', 'uni_pc_lower_order_final'), - ('Token merging', 'token_merging'), ('Token merging ratio', 'token_merging_ratio'), - ('Token merging hr only', 'token_merging_hr_only'), ('Token merging ratio hr', 'token_merging_ratio_hr'), - ('Token merging random', 'token_merging_random'), - ('Token merging merge attention', 'token_merging_merge_attention'), - ('Token merging merge cross attention', 'token_merging_merge_cross_attention'), - ('Token merging merge mlp', 'token_merging_merge_mlp'), - ('Token merging maximum down sampling', 'token_merging_maximum_down_sampling'), - ('Token merging stride x', 'token_merging_stride_x'), - ('Token merging stride y', 'token_merging_stride_y'), ('RNG', 'randn_source'), ('NGMS', 's_min_uncond') ] diff --git a/modules/processing.py b/modules/processing.py index 6828e898..32ff61e9 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -34,7 +34,7 @@ import tomesd # add a logger for the processing module logger = logging.getLogger(__name__) # manually set output level here since there is no option to do so yet through launch options -# logging.basicConfig(level=logging.DEBUG, format='%(asctime)s %(levelname)s %(name)s %(message)s') +logging.basicConfig(level=logging.DEBUG, format='%(asctime)s %(levelname)s %(name)s %(message)s') # some of those options should not be changed at all because they would break the model, so I removed them from options. @@ -496,15 +496,8 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter "Conditional mask weight": getattr(p, "inpainting_mask_weight", shared.opts.inpainting_mask_weight) if p.is_using_inpainting_conditioning else None, "Clip skip": None if clip_skip <= 1 else clip_skip, "ENSD": None if opts.eta_noise_seed_delta == 0 else opts.eta_noise_seed_delta, - "Token merging ratio": None if not opts.token_merging or opts.token_merging_hr_only else opts.token_merging_ratio, - "Token merging ratio hr": None if not opts.token_merging else opts.token_merging_ratio_hr, - "Token merging random": None if opts.token_merging_random is False else opts.token_merging_random, - "Token merging merge attention": None if opts.token_merging_merge_attention is True else opts.token_merging_merge_attention, - "Token merging merge cross attention": None if opts.token_merging_merge_cross_attention is False else opts.token_merging_merge_cross_attention, - "Token merging merge mlp": None if opts.token_merging_merge_mlp is False else opts.token_merging_merge_mlp, - "Token merging stride x": None if opts.token_merging_stride_x == 2 else opts.token_merging_stride_x, - "Token merging stride y": None if opts.token_merging_stride_y == 2 else opts.token_merging_stride_y, - "Token merging maximum down sampling": None if opts.token_merging_maximum_down_sampling == 1 else opts.token_merging_maximum_down_sampling, + "Token merging ratio": None if opts.token_merging_ratio == 0 else opts.token_merging_ratio, + "Token merging ratio hr": None if not p.enable_hr or opts.token_merging_ratio_hr == 0 else opts.token_merging_ratio_hr, "Init image hash": getattr(p, 'init_img_hash', None), "RNG": opts.randn_source if opts.randn_source != "GPU" else None, "NGMS": None if p.s_min_uncond == 0 else p.s_min_uncond, @@ -538,15 +531,15 @@ def process_images(p: StableDiffusionProcessing) -> Processed: if k == 'sd_vae': sd_vae.reload_vae_weights() - if opts.token_merging and not opts.token_merging_hr_only: + if opts.token_merging_ratio > 0: sd_models.apply_token_merging(sd_model=p.sd_model, hr=False) - logger.debug('Token merging applied') + logger.debug(f"Token merging applied to first pass. Ratio: '{opts.token_merging_ratio}'") res = process_images_inner(p) finally: # undo model optimizations made by tomesd - if opts.token_merging: + if opts.token_merging_ratio > 0: tomesd.remove_patch(p.sd_model) logger.debug('Token merging model optimizations removed') @@ -1003,19 +996,21 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): devices.torch_gc() # apply token merging optimizations from tomesd for high-res pass - # check if hr_only so we are not redundantly patching - if opts.token_merging and (opts.token_merging_hr_only or opts.token_merging_ratio_hr != opts.token_merging_ratio): - # case where user wants to use separate merge ratios - if not opts.token_merging_hr_only: - # clean patch done by first pass. (clobbering the first patch might be fine? this might be excessive) + if opts.token_merging_ratio_hr > 0: + # in case the user has used separate merge ratios + if opts.token_merging_ratio > 0: tomesd.remove_patch(self.sd_model) - logger.debug('Temporarily removed token merging optimizations in preparation for next pass') + logger.debug('Adjusting token merging ratio for high-res pass') sd_models.apply_token_merging(sd_model=self.sd_model, hr=True) - logger.debug('Applied token merging for high-res pass') + logger.debug(f"Applied token merging for high-res pass. Ratio: '{opts.token_merging_ratio_hr}'") samples = self.sampler.sample_img2img(self, samples, noise, conditioning, unconditional_conditioning, steps=self.hr_second_pass_steps or self.steps, image_conditioning=image_conditioning) + if opts.token_merging_ratio_hr > 0 or opts.token_merging_ratio > 0: + tomesd.remove_patch(self.sd_model) + logger.debug('Removed token merging optimizations from model') + self.is_hr_pass = False return samples diff --git a/modules/sd_models.py b/modules/sd_models.py index 4787193c..4c9a0a1f 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -596,11 +596,8 @@ def apply_token_merging(sd_model, hr: bool): tomesd.apply_patch( sd_model, ratio=ratio, - max_downsample=shared.opts.token_merging_maximum_down_sampling, - sx=shared.opts.token_merging_stride_x, - sy=shared.opts.token_merging_stride_y, - use_rand=shared.opts.token_merging_random, - merge_attn=shared.opts.token_merging_merge_attention, - merge_crossattn=shared.opts.token_merging_merge_cross_attention, - merge_mlp=shared.opts.token_merging_merge_mlp + use_rand=False, # can cause issues with some samplers + merge_attn=True, + merge_crossattn=False, + merge_mlp=False ) diff --git a/modules/shared.py b/modules/shared.py index 4b346585..0d96c14c 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -459,47 +459,13 @@ options_templates.update(options_section((None, "Hidden options"), { })) options_templates.update(options_section(('token_merging', 'Token Merging'), { - "token_merging": OptionInfo( - False, "Enable redundant token merging via tomesd. This can provide significant speed and memory improvements.", - gr.Checkbox - ), - "token_merging_ratio": OptionInfo( - 0.5, "Merging Ratio", - gr.Slider, {"minimum": 0, "maximum": 0.9, "step": 0.1} - ), - "token_merging_hr_only": OptionInfo( - True, "Apply only to high-res fix pass. Disabling can yield a ~20-35% speedup on contemporary resolutions.", - gr.Checkbox - ), "token_merging_ratio_hr": OptionInfo( - 0.5, "Merging Ratio (high-res pass) - If 'Apply only to high-res' is enabled, this will always be the ratio used.", + 0, "Merging Ratio (high-res pass)", gr.Slider, {"minimum": 0, "maximum": 0.9, "step": 0.1} ), - # More advanced/niche settings: - "token_merging_random": OptionInfo( - False, "Use random perturbations - Can improve outputs for certain samplers. For others, it may cause visual artifacting.", - gr.Checkbox - ), - "token_merging_merge_attention": OptionInfo( - True, "Merge attention", - gr.Checkbox - ), - "token_merging_merge_cross_attention": OptionInfo( - False, "Merge cross attention", - gr.Checkbox - ), - "token_merging_merge_mlp": OptionInfo( - False, "Merge mlp", - gr.Checkbox - ), - "token_merging_maximum_down_sampling": OptionInfo(1, "Maximum down sampling", gr.Radio, lambda: {"choices": [1, 2, 4, 8]}), - "token_merging_stride_x": OptionInfo( - 2, "Stride - X", - gr.Slider, {"minimum": 2, "maximum": 8, "step": 2} - ), - "token_merging_stride_y": OptionInfo( - 2, "Stride - Y", - gr.Slider, {"minimum": 2, "maximum": 8, "step": 2} + "token_merging_ratio": OptionInfo( + 0, "Merging Ratio", + gr.Slider, {"minimum": 0, "maximum": 0.9, "step": 0.1} ) })) -- cgit v1.2.3 From 2cfaffb239bb2b99aab06352f8c101e48e48dec9 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sun, 14 May 2023 08:30:37 +0300 Subject: updates for #9256 --- modules/generation_parameters_copypaste.py | 2 +- modules/shared.py | 4 ++-- requirements.txt | 1 + requirements_versions.txt | 2 +- 4 files changed, 5 insertions(+), 4 deletions(-) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index a0a98bbc..f1a2204c 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -311,7 +311,7 @@ infotext_to_setting_name_mapping = [ ('Token merging ratio', 'token_merging_ratio'), ('Token merging ratio hr', 'token_merging_ratio_hr'), ('RNG', 'randn_source'), - ('NGMS', 's_min_uncond') + ('NGMS', 's_min_uncond'), ] diff --git a/modules/shared.py b/modules/shared.py index a5e8d0bd..7ec9967e 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -350,8 +350,8 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "CLIP_stop_at_last_layers": OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}), "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"]}), - "token_merging_ratio_hr": OptionInfo(0, "Merging Ratio (high-res pass)", gr.Slider, {"minimum": 0, "maximum": 0.9, "step": 0.1}), - "token_merging_ratio": OptionInfo(0, "Merging Ratio", gr.Slider, {"minimum": 0, "maximum": 0.9, "step": 0.1}) + "token_merging_ratio": OptionInfo(0.0, "Token merging ratio", gr.Slider, {"minimum": 0.0, "maximum": 0.9, "step": 0.1}), + "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}), })) options_templates.update(options_section(('compatibility', "Compatibility"), { diff --git a/requirements.txt b/requirements.txt index 2423bfd2..302b3dab 100644 --- a/requirements.txt +++ b/requirements.txt @@ -29,3 +29,4 @@ torchsde safetensors psutil rich +tomesd diff --git a/requirements_versions.txt b/requirements_versions.txt index 0e03deed..17ae9484 100644 --- a/requirements_versions.txt +++ b/requirements_versions.txt @@ -26,4 +26,4 @@ torchsde==0.2.5 safetensors==0.3.1 httpcore<=0.15 fastapi==0.94.0 -tomesd>=0.1.2 \ No newline at end of file +tomesd==0.1.2 -- cgit v1.2.3 From ff0e17174f8d93a71fdd5a4a80a4629bbf97f822 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Thu, 18 May 2023 20:16:09 +0300 Subject: rework hires prompts/sampler code to among other things support different extra networks in first/second pass rework quoting for infotext items that have commas in them to use json (should be backwards compatible except for cases where it didn't work previously) add some locals from processing function into the Processing class as fields --- modules/generation_parameters_copypaste.py | 36 ++-- modules/processing.py | 261 ++++++++++++++++------------- modules/shared.py | 6 +- modules/txt2img.py | 4 +- modules/ui.py | 14 +- 5 files changed, 188 insertions(+), 133 deletions(-) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index b34046a0..d5f0a49b 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -1,5 +1,6 @@ import base64 import io +import json import os import re @@ -34,13 +35,20 @@ def reset(): def quote(text): - if ',' not in str(text): + if ',' not in str(text) and '\n' not in str(text): return text - text = str(text) - text = text.replace('\\', '\\\\') - text = text.replace('"', '\\"') - return f'"{text}"' + return json.dumps(text, ensure_ascii=False) + + +def unquote(text): + if len(text) == 0 or text[0] != '"' or text[-1] != '"': + return text + + try: + return json.loads(text) + except Exception: + return text def image_from_url_text(filedata): @@ -261,7 +269,9 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model res["Negative prompt"] = negative_prompt for k, v in re_param.findall(lastline): - v = v[1:-1] if v[0] == '"' and v[-1] == '"' else v + if v[0] == '"' and v[-1] == '"': + v = unquote(v) + m = re_imagesize.match(v) if m is not None: res[f"{k}-1"] = m.group(1) @@ -269,11 +279,6 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model else: res[k] = v - if k.startswith("Hires prompt"): - res["Hires prompt"] = v[1:][:-1].replace(';', ',') - elif k.startswith("Hires negative prompt"): - res["Hires negative prompt"] = v[1:][:-1].replace(';', ',') - # Missing CLIP skip means it was set to 1 (the default) if "Clip skip" not in res: res["Clip skip"] = "1" @@ -286,6 +291,15 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model res["Hires resize-1"] = 0 res["Hires resize-2"] = 0 + if "Hires sampler" not in res: + res["Hires sampler"] = "Use same sampler" + + if "Hires prompt" not in res: + res["Hires prompt"] = "" + + if "Hires negative prompt" not in res: + res["Hires negative prompt"] = "" + restore_old_hires_fix_params(res) # Missing RNG means the default was set, which is GPU RNG diff --git a/modules/processing.py b/modules/processing.py index dd14c486..29a3743f 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -169,6 +169,16 @@ class StableDiffusionProcessing: self.is_hr_pass = False self.sampler = None + self.prompts = None + self.negative_prompts = None + self.seeds = None + self.subseeds = None + + self.step_multiplier = 1 + self.cached_uc = [None, None] + self.cached_c = [None, None] + self.uc = None + self.c = None @property def sd_model(self): @@ -271,11 +281,15 @@ class StableDiffusionProcessing: def init(self, all_prompts, all_seeds, all_subseeds): pass - def sample(self, conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength, prompts, hr_conditioning=None, hr_unconditional_conditioning=None): + def sample(self, conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength, prompts): raise NotImplementedError() def close(self): self.sampler = None + self.c = None + self.uc = None + self.cached_c = [None, None] + self.cached_uc = [None, None] def get_token_merging_ratio(self, for_hr=False): if for_hr: @@ -283,6 +297,52 @@ class StableDiffusionProcessing: return self.token_merging_ratio or opts.token_merging_ratio + def setup_prompts(self): + if type(self.prompt) == list: + self.all_prompts = self.prompt + else: + self.all_prompts = self.batch_size * self.n_iter * [self.prompt] + + if type(self.negative_prompt) == list: + self.all_negative_prompts = self.negative_prompt + else: + self.all_negative_prompts = self.batch_size * self.n_iter * [self.negative_prompt] + + self.all_prompts = [shared.prompt_styles.apply_styles_to_prompt(x, self.styles) for x in self.all_prompts] + self.all_negative_prompts = [shared.prompt_styles.apply_negative_styles_to_prompt(x, self.styles) for x in self.all_negative_prompts] + + def get_conds_with_caching(self, function, required_prompts, steps, cache): + """ + Returns the result of calling function(shared.sd_model, required_prompts, steps) + using a cache to store the result if the same arguments have been used before. + + cache is an array containing two elements. The first element is a tuple + representing the previously used arguments, or None if no arguments + have been used before. The second element is where the previously + computed result is stored. + """ + + if cache[0] is not None and (required_prompts, steps) == cache[0]: + return cache[1] + + with devices.autocast(): + cache[1] = function(shared.sd_model, required_prompts, steps) + + cache[0] = (required_prompts, steps) + return cache[1] + + def setup_conds(self): + sampler_config = sd_samplers.find_sampler_config(self.sampler_name) + self.step_multiplier = 2 if sampler_config and sampler_config.options.get("second_order", False) else 1 + + self.uc = self.get_conds_with_caching(prompt_parser.get_learned_conditioning, self.negative_prompts, self.steps * self.step_multiplier, self.cached_uc) + self.c = self.get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, self.prompts, self.steps * self.step_multiplier, self.cached_c) + + def parse_extra_network_prompts(self): + self.prompts, extra_network_data = extra_networks.parse_prompts(self.prompts) + + return extra_network_data + class Processed: def __init__(self, p: StableDiffusionProcessing, images_list, seed=-1, info="", subseed=None, all_prompts=None, all_negative_prompts=None, all_seeds=None, all_subseeds=None, index_of_first_image=0, infotexts=None, comments=""): @@ -582,29 +642,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: comments = {} - if type(p.prompt) == list: - p.all_prompts = [shared.prompt_styles.apply_styles_to_prompt(x, p.styles) for x in p.prompt] - else: - p.all_prompts = p.batch_size * p.n_iter * [shared.prompt_styles.apply_styles_to_prompt(p.prompt, p.styles)] - - if type(p.negative_prompt) == list: - p.all_negative_prompts = [shared.prompt_styles.apply_negative_styles_to_prompt(x, p.styles) for x in p.negative_prompt] - else: - p.all_negative_prompts = p.batch_size * p.n_iter * [shared.prompt_styles.apply_negative_styles_to_prompt(p.negative_prompt, p.styles)] - - if type(p) == StableDiffusionProcessingTxt2Img: - if p.enable_hr and p.hr_prompt == '': - p.all_hr_prompts, p.all_hr_negative_prompts = p.all_prompts, p.all_negative_prompts - elif p.enable_hr and p.hr_prompt != '': - if type(p.prompt) == list: - p.all_hr_prompts = [shared.prompt_styles.apply_styles_to_prompt(x, p.styles) for x in p.hr_prompt] - else: - p.all_hr_prompts = p.batch_size * p.n_iter * [shared.prompt_styles.apply_styles_to_prompt(p.hr_prompt, p.styles)] - - if type(p.negative_prompt) == list: - p.all_hr_negative_prompts = [shared.prompt_styles.apply_negative_styles_to_prompt(x, p.styles) for x in p.hr_negative_prompt] - else: - p.all_hr_negative_prompts = p.batch_size * p.n_iter * [shared.prompt_styles.apply_negative_styles_to_prompt(p.hr_negative_prompt, p.styles)] + p.setup_prompts() if type(seed) == list: p.all_seeds = seed @@ -628,29 +666,6 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: infotexts = [] output_images = [] - cached_uc = [None, None] - cached_c = [None, None] - - def get_conds_with_caching(function, required_prompts, steps, cache): - """ - Returns the result of calling function(shared.sd_model, required_prompts, steps) - using a cache to store the result if the same arguments have been used before. - - cache is an array containing two elements. The first element is a tuple - representing the previously used arguments, or None if no arguments - have been used before. The second element is where the previously - computed result is stored. - """ - - if cache[0] is not None and (required_prompts, steps) == cache[0]: - return cache[1] - - with devices.autocast(): - cache[1] = function(shared.sd_model, required_prompts, steps) - - cache[0] = (required_prompts, steps) - return cache[1] - with torch.no_grad(), p.sd_model.ema_scope(): with devices.autocast(): p.init(p.all_prompts, p.all_seeds, p.all_subseeds) @@ -672,40 +687,25 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: if state.interrupted: break - prompts = p.all_prompts[n * p.batch_size:(n + 1) * p.batch_size] - negative_prompts = p.all_negative_prompts[n * p.batch_size:(n + 1) * p.batch_size] - - if type(p) == StableDiffusionProcessingTxt2Img: - if p.enable_hr: - if p.hr_prompt == '': - hr_prompts, hr_negative_prompts = prompts, negative_prompts - else: - hr_prompts = p.all_hr_prompts[n * p.batch_size:(n + 1) * p.batch_size] - hr_negative_prompts = p.all_hr_negative_prompts[n * p.batch_size:(n + 1) * p.batch_size] - - seeds = p.all_seeds[n * p.batch_size:(n + 1) * p.batch_size] - subseeds = p.all_subseeds[n * p.batch_size:(n + 1) * p.batch_size] + p.prompts = p.all_prompts[n * p.batch_size:(n + 1) * p.batch_size] + p.negative_prompts = p.all_negative_prompts[n * p.batch_size:(n + 1) * p.batch_size] + p.seeds = p.all_seeds[n * p.batch_size:(n + 1) * p.batch_size] + p.subseeds = p.all_subseeds[n * p.batch_size:(n + 1) * p.batch_size] if p.scripts is not None: - p.scripts.before_process_batch(p, batch_number=n, prompts=prompts, seeds=seeds, subseeds=subseeds) + p.scripts.before_process_batch(p, batch_number=n, prompts=p.prompts, seeds=p.seeds, subseeds=p.subseeds) - if len(prompts) == 0: + if len(p.prompts) == 0: break - prompts, extra_network_data = extra_networks.parse_prompts(prompts) - - if type(p) == StableDiffusionProcessingTxt2Img: - if p.enable_hr and hr_prompts != prompts: - _, hr_extra_network_data = extra_networks.parse_prompts(hr_prompts) - extra_network_data.update(hr_extra_network_data) - + extra_network_data = p.parse_extra_network_prompts() if not p.disable_extra_networks: with devices.autocast(): extra_networks.activate(p, extra_network_data) if p.scripts is not None: - p.scripts.process_batch(p, batch_number=n, prompts=prompts, seeds=seeds, subseeds=subseeds) + p.scripts.process_batch(p, batch_number=n, prompts=p.prompts, seeds=p.seeds, subseeds=p.subseeds) # params.txt should be saved after scripts.process_batch, since the # infotext could be modified by that callback @@ -716,18 +716,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: processed = Processed(p, [], p.seed, "") file.write(processed.infotext(p, 0)) - sampler_config = sd_samplers.find_sampler_config(p.sampler_name) - step_multiplier = 2 if sampler_config and sampler_config.options.get("second_order", False) else 1 - uc = get_conds_with_caching(prompt_parser.get_learned_conditioning, negative_prompts, p.steps * step_multiplier, cached_uc) - c = get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, prompts, p.steps * step_multiplier, cached_c) - - if type(p) == StableDiffusionProcessingTxt2Img: - if p.enable_hr: - if prompts != hr_prompts: - hr_uc = get_conds_with_caching(prompt_parser.get_learned_conditioning, hr_negative_prompts, p.steps, cached_uc) - hr_c = get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, hr_prompts, p.steps, cached_c) - else: - hr_uc, hr_c = uc, c + p.setup_conds() if len(model_hijack.comments) > 0: for comment in model_hijack.comments: @@ -736,15 +725,8 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: if p.n_iter > 1: shared.state.job = f"Batch {n+1} out of {p.n_iter}" - with devices.without_autocast() if devices.unet_needs_upcast else devices.autocast(): - if type(p) == StableDiffusionProcessingTxt2Img: - if p.enable_hr: - samples_ddim = p.sample(conditioning=c, unconditional_conditioning=uc, hr_conditioning=hr_c, hr_unconditional_conditioning=hr_uc, seeds=seeds, subseeds=subseeds, subseed_strength=p.subseed_strength, prompts=prompts) - else: - samples_ddim = p.sample(conditioning=c, unconditional_conditioning=uc, seeds=seeds, subseeds=subseeds, subseed_strength=p.subseed_strength, prompts=prompts) - else: - samples_ddim = p.sample(conditioning=c, unconditional_conditioning=uc, seeds=seeds, subseeds=subseeds, subseed_strength=p.subseed_strength, prompts=prompts) + samples_ddim = p.sample(conditioning=p.c, unconditional_conditioning=p.uc, seeds=p.seeds, subseeds=p.subseeds, subseed_strength=p.subseed_strength, prompts=p.prompts) x_samples_ddim = [decode_first_stage(p.sd_model, samples_ddim[i:i+1].to(dtype=devices.dtype_vae))[0].cpu() for i in range(samples_ddim.size(0))] for x in x_samples_ddim: @@ -771,7 +753,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: if p.restore_faces: if opts.save and not p.do_not_save_samples and opts.save_images_before_face_restoration: - images.save_image(Image.fromarray(x_sample), p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-before-face-restoration") + images.save_image(Image.fromarray(x_sample), p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-before-face-restoration") devices.torch_gc() @@ -788,13 +770,13 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: if p.color_corrections is not None and i < len(p.color_corrections): if opts.save and not p.do_not_save_samples and opts.save_images_before_color_correction: image_without_cc = apply_overlay(image, p.paste_to, i, p.overlay_images) - images.save_image(image_without_cc, p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-before-color-correction") + images.save_image(image_without_cc, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-before-color-correction") image = apply_color_correction(p.color_corrections[i], image) image = apply_overlay(image, p.paste_to, i, p.overlay_images) if opts.samples_save and not p.do_not_save_samples: - images.save_image(image, p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p) + images.save_image(image, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(n, i), p=p) text = infotext(n, i) infotexts.append(text) @@ -807,10 +789,10 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: image_mask_composite = Image.composite(image.convert('RGBA').convert('RGBa'), Image.new('RGBa', image.size), images.resize_image(2, p.mask_for_overlay, image.width, image.height).convert('L')).convert('RGBA') if opts.save_mask: - images.save_image(image_mask, p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-mask") + images.save_image(image_mask, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-mask") if opts.save_mask_composite: - images.save_image(image_mask_composite, p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-mask-composite") + images.save_image(image_mask_composite, p.outpath_samples, "", p.seeds[i], p.prompts[i], opts.samples_format, info=infotext(n, i), p=p, suffix="-mask-composite") if opts.return_mask: output_images.append(image_mask) @@ -879,7 +861,7 @@ def old_hires_fix_first_pass_dimensions(width, height): class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): sampler = None - def __init__(self, enable_hr: bool = False, denoising_strength: float = 0.75, firstphase_width: int = 0, firstphase_height: int = 0, hr_scale: float = 2.0, hr_upscaler: str = None, hr_second_pass_steps: int = 0, hr_resize_x: int = 0, hr_resize_y: int = 0, hr_sampler: str = '---', hr_prompt: str = '', hr_negative_prompt: str = '', **kwargs): + def __init__(self, enable_hr: bool = False, denoising_strength: float = 0.75, firstphase_width: int = 0, firstphase_height: int = 0, hr_scale: float = 2.0, hr_upscaler: str = None, hr_second_pass_steps: int = 0, hr_resize_x: int = 0, hr_resize_y: int = 0, hr_sampler_name: str = None, hr_prompt: str = '', hr_negative_prompt: str = '', **kwargs): super().__init__(**kwargs) self.enable_hr = enable_hr self.denoising_strength = denoising_strength @@ -890,9 +872,9 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): self.hr_resize_y = hr_resize_y self.hr_upscale_to_x = hr_resize_x self.hr_upscale_to_y = hr_resize_y - self.hr_sampler = hr_sampler - self.hr_prompt = hr_prompt if hr_prompt != '' else '' - self.hr_negative_prompt = hr_negative_prompt if hr_negative_prompt != '' else '' + self.hr_sampler_name = hr_sampler_name + self.hr_prompt = hr_prompt + self.hr_negative_prompt = hr_negative_prompt self.all_hr_prompts = None self.all_hr_negative_prompts = None @@ -906,14 +888,23 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): self.truncate_y = 0 self.applied_old_hires_behavior_to = None + self.hr_prompts = None + self.hr_negative_prompts = None + self.hr_extra_network_data = None + + self.hr_c = None + self.hr_uc = None + def init(self, all_prompts, all_seeds, all_subseeds): if self.enable_hr: - if self.hr_sampler != '---': - self.extra_generation_params["Hires sampler"] = self.hr_sampler + if self.hr_sampler_name is not None and self.hr_sampler_name != self.sampler_name: + self.extra_generation_params["Hires sampler"] = self.hr_sampler_name + + if tuple(self.hr_prompt) != tuple(self.prompt): + self.extra_generation_params["Hires prompt"] = self.hr_prompt - if self.hr_prompt != '': - self.extra_generation_params["Hires prompt"] = f'({self.hr_prompt.replace(",", ";")})' - self.extra_generation_params["Hires negative prompt"] = f'({self.hr_negative_prompt.replace(",", ";")})' + if tuple(self.hr_negative_prompt) != tuple(self.negative_prompt): + self.extra_generation_params["Hires negative prompt"] = self.hr_negative_prompt if opts.use_old_hires_fix_width_height and self.applied_old_hires_behavior_to != (self.width, self.height): self.hr_resize_x = self.width @@ -975,7 +966,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): if self.hr_upscaler is not None: self.extra_generation_params["Hires upscaler"] = self.hr_upscaler - def sample(self, conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength, prompts, hr_conditioning=None, hr_unconditional_conditioning=None): + def sample(self, conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength, prompts): self.sampler = sd_samplers.create_sampler(self.sampler_name, self.sd_model) latent_scale_mode = shared.latent_upscale_modes.get(self.hr_upscaler, None) if self.hr_upscaler is not None else shared.latent_upscale_modes.get(shared.latent_upscale_default_mode, "nearest") @@ -1044,16 +1035,11 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): shared.state.nextjob() - img2img_sampler_name = self.sampler_name + img2img_sampler_name = self.hr_sampler_name or self.sampler_name if self.sampler_name in ['PLMS', 'UniPC']: # PLMS/UniPC do not support img2img so we just silently switch to DDIM img2img_sampler_name = 'DDIM' - if self.hr_sampler == '---': - pass - else: - img2img_sampler_name = self.hr_sampler - self.sampler = sd_samplers.create_sampler(img2img_sampler_name, self.sd_model) samples = samples[:, :, self.truncate_y//2:samples.shape[2]-(self.truncate_y+1)//2, self.truncate_x//2:samples.shape[3]-(self.truncate_x+1)//2] @@ -1064,9 +1050,13 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): x = None devices.torch_gc() + if not self.disable_extra_networks: + with devices.autocast(): + extra_networks.activate(self, self.hr_extra_network_data) + sd_models.apply_token_merging(self.sd_model, self.get_token_merging_ratio(for_hr=True)) - samples = self.sampler.sample_img2img(self, samples, noise, hr_conditioning, hr_unconditional_conditioning, steps=self.hr_second_pass_steps or self.steps, image_conditioning=image_conditioning) + samples = self.sampler.sample_img2img(self, samples, noise, self.hr_c, self.hr_uc, steps=self.hr_second_pass_steps or self.steps, image_conditioning=image_conditioning) sd_models.apply_token_merging(self.sd_model, self.get_token_merging_ratio()) @@ -1074,6 +1064,53 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): return samples + def close(self): + self.hr_c = None + self.hr_uc = None + + def setup_prompts(self): + super().setup_prompts() + + if not self.enable_hr: + return + + if self.hr_prompt == '': + self.hr_prompt = self.prompt + + if self.hr_negative_prompt == '': + self.hr_negative_prompt = self.negative_prompt + + if type(self.hr_prompt) == list: + self.all_hr_prompts = self.hr_prompt + else: + self.all_hr_prompts = self.batch_size * self.n_iter * [self.hr_prompt] + + if type(self.hr_negative_prompt) == list: + self.all_hr_negative_prompts = self.hr_negative_prompt + else: + self.all_hr_negative_prompts = self.batch_size * self.n_iter * [self.hr_negative_prompt] + + self.all_hr_prompts = [shared.prompt_styles.apply_styles_to_prompt(x, self.styles) for x in self.all_hr_prompts] + self.all_hr_negative_prompts = [shared.prompt_styles.apply_negative_styles_to_prompt(x, self.styles) for x in self.all_hr_negative_prompts] + + def setup_conds(self): + super().setup_conds() + + if self.enable_hr: + self.hr_uc = self.get_conds_with_caching(prompt_parser.get_learned_conditioning, self.hr_negative_prompts, self.steps * self.step_multiplier, self.cached_uc) + self.hr_c = self.get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, self.hr_prompts, self.steps * self.step_multiplier, self.cached_c) + + def parse_extra_network_prompts(self): + res = super().parse_extra_network_prompts() + + if self.enable_hr: + self.hr_prompts = self.all_hr_prompts[self.iteration * self.batch_size:(self.iteration + 1) * self.batch_size] + self.hr_negative_prompts = self.all_hr_negative_prompts[self.iteration * self.batch_size:(self.iteration + 1) * self.batch_size] + + self.hr_prompts, self.hr_extra_network_data = extra_networks.parse_prompts(self.hr_prompts) + + return res + class StableDiffusionProcessingImg2Img(StableDiffusionProcessing): sampler = None diff --git a/modules/shared.py b/modules/shared.py index 9e9e8cd4..fdbab5c4 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -454,6 +454,7 @@ options_templates.update(options_section(('extra_networks', "Extra Networks"), { "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"), + "ui_extra_networks_tab_reorder": OptionInfo("", "Extra networks tab order").needs_restart(), "sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": ["None", *hypernetworks]}, refresh=reload_hypernetworks), })) @@ -481,8 +482,9 @@ options_templates.update(options_section(('ui', "User interface"), { "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(), "ui_tab_order": OptionInfo([], "UI tab order", ui_components.DropdownMulti, lambda: {"choices": list(tab_names)}).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").needs_restart(), + "ui_reorder": OptionInfo(", ".join(ui_reorder_categories), "txt2img/img2img UI item order").needs_restart(), + "hires_fix_show_sampler": OptionInfo(False, "Hires fix: show hires sampler selection").needs_restart(), + "hires_fix_show_prompts": OptionInfo(False, "Hires fix: show hires prompt and negative prompt").needs_restart(), })) options_templates.update(options_section(('infotext', "Infotext"), { diff --git a/modules/txt2img.py b/modules/txt2img.py index 3b4c985e..2e7d202d 100644 --- a/modules/txt2img.py +++ b/modules/txt2img.py @@ -9,7 +9,7 @@ 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, hr_sampler_index: int, hr_prompt: str, hr_negative_prompt, override_settings_texts, *args): override_settings = create_override_settings_dict(override_settings_texts) - + p = processing.StableDiffusionProcessingTxt2Img( sd_model=shared.sd_model, outpath_samples=opts.outdir_samples or opts.outdir_txt2img_samples, @@ -39,7 +39,7 @@ def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, step hr_second_pass_steps=hr_second_pass_steps, hr_resize_x=hr_resize_x, hr_resize_y=hr_resize_y, - hr_sampler=sd_samplers.samplers_for_img2img[hr_sampler_index - 1].name if hr_sampler_index != 0 else '---', + hr_sampler_name=sd_samplers.samplers_for_img2img[hr_sampler_index - 1].name if hr_sampler_index != 0 else None, hr_prompt=hr_prompt, hr_negative_prompt=hr_negative_prompt, override_settings=override_settings, diff --git a/modules/ui.py b/modules/ui.py index c3ff48b4..2016ed74 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -499,16 +499,16 @@ def create_ui(): hr_resize_x = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize width to", value=0, elem_id="txt2img_hr_resize_x") hr_resize_y = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize height to", value=0, elem_id="txt2img_hr_resize_y") - with FormRow(elem_id="txt2img_hires_fix_row3", variant="compact"): - hr_sampler_index = gr.Dropdown(label='Hires sampling method', elem_id=f"hr_sampler", choices=["---"] + [x.name for x in samplers_for_img2img], value="---", type="index") + with FormRow(elem_id="txt2img_hires_fix_row3", variant="compact", visible=opts.hires_fix_show_sampler) as hr_sampler_container: + hr_sampler_index = gr.Dropdown(label='Hires sampling method', elem_id="hr_sampler", choices=["Use same sampler"] + [x.name for x in samplers_for_img2img], value="Use same sampler", type="index") - with FormRow(elem_id="txt2img_hires_fix_row4", variant="compact"): + with FormRow(elem_id="txt2img_hires_fix_row4", variant="compact", visible=opts.hires_fix_show_prompts) as hr_prompts_container: with gr.Column(scale=80): with gr.Row(): - hr_prompt = gr.Textbox(label="Prompt", elem_id=f"hires_prompt", show_label=False, lines=3, placeholder="Prompt that will be used for hires fix pass (leave it blank to use the same prompt as in initial txt2img gen)") + hr_prompt = gr.Textbox(label="Prompt", elem_id="hires_prompt", show_label=False, lines=3, placeholder="Prompt for hires fix pass.\nLeave empty to use the same prompt as in first pass.") with gr.Column(scale=80): with gr.Row(): - hr_negative_prompt = gr.Textbox(label="Negative prompt", elem_id=f"hires_neg_prompt", show_label=False, lines=3, placeholder="Negative prompt that will be used for hires fix pass (leave it blank to use the same prompt as in initial txt2img gen)") + hr_negative_prompt = gr.Textbox(label="Negative prompt", elem_id="hires_neg_prompt", show_label=False, lines=3, placeholder="Negative prompt for hires fix pass.\nLeave empty to use the same negative prompt as in first pass.") elif category == "batch": if not opts.dimensions_and_batch_together: @@ -646,9 +646,11 @@ def create_ui(): (hr_second_pass_steps, "Hires steps"), (hr_resize_x, "Hires resize-1"), (hr_resize_y, "Hires resize-2"), - (hr_sampler_index, "Hires sampling method"), + (hr_sampler_index, "Hires sampler"), + (hr_sampler_container, lambda d: gr.update(visible=True) if d.get("Hires sampler", "Use same sampler") != "Use same sampler" else gr.update()), (hr_prompt, "Hires prompt"), (hr_negative_prompt, "Hires negative prompt"), + (hr_prompts_container, lambda d: gr.update(visible=True) if d.get("Hires prompt", "") != "" or d.get("Hires negative prompt", "") != "" else gr.update()), *modules.scripts.scripts_txt2img.infotext_fields ] parameters_copypaste.add_paste_fields("txt2img", None, txt2img_paste_fields, override_settings) -- cgit v1.2.3